Spencer Bradley, the Vice President of Business Development and Sales at Solutions Review, shares some insights and statistics on how enterprise tech vendors are helping reshape the marketing landscape in 2025 (and beyond).

Enterprise technology vendors in 2025 are navigating a complex marketing environment shaped by AI innovation, economic uncertainty, and increased buyer skepticism. As a result, their marketing budgets are being strategically reallocated toward performance-driven, measurable outcomes. Here’s how they’re spending: 

1) Content That Converts: SEO, Thought Leadership, and Product Education

• Priority Spend: Blogs, whitepapers, product comparison guides, and video explainers.
• Why: B2B buyers are self-educating more than ever before. Content must map directly to intent stages. 
• Format Trends: 
  • AI-generated and human-refined content for scale 
  • Interactive assets (ROI calculators, solution finders) 
  • First-party research reports for media outreach 

2) Account-Based Marketing (ABM) & Personalization 

• Priority Spend: Targeted LinkedIn ads, intent data platforms (e.g., Bombora, G2), and personalized content hubs. 
• Why: Broad-based demand gen is inefficient. ABM targets revenue-qualified accounts, not just MQLs. 
• Emerging Trend: Combining ABM with AI email agents for automated but highly personalized outbound.

3) Influencer and Analyst Engagement

• Priority Spend: Paid analyst relations (Forrester, Gartner alternatives), podcast guest spots, co-branded webinars 
• Why: Buyers trust third-party validation more than vendor content 
• Trend: Rise of “micro-influencers” and niche B2B creators with trusted followings 

4) Performance Marketing with a Hard Pivot to ROI

• Priority Spend: Google Search and Display, LinkedIn Lead Gen, and retargeting.
• Why: Every dollar must prove ROI fast; CMOs are under pressure to tie activity to pipeline.
• Shift: There is a smaller budget for top-of-funnel impressions and more toward bottom-funnel conversion.

5) Event Hybridization and Virtual Briefings

• Priority Spend: Custom virtual events, roundtables, and briefings with strategic accounts.
• Why: Trade show ROI is under scrutiny. Vendors prefer intimate, controlled formats.
• Trend: On-demand replays with gated CTAs for post-event lead capture.

6) AI and Automation-Driven MarTech Investments

• Priority Spend: AI content tools, intent scoring, conversational marketing, and predictive analytics.
• Why: Marketing teams are expected to do more with less. AI unlocks scale. 
• Trend: Consolidating tech stacks around platforms with native AI integration.

7) Community & Owned Media 

• Priority Spend: Branded newsletters, YouTube channels, owned media (like Solutions Review and Insight Jam).
• Why: Trust and audience access are more valuable than traffic spikes.
• Trend: Building media-like properties in-house to control reach and reduce dependency on third-party platforms.

Areas Seeing Reduced Budget: 

• Traditional PR retainers with little attribution.

• High-cost in-person trade shows, unless tied to clear revenue opportunities.

• Overly broad brand campaigns with no measurable impact on the pipeline.

Summary 

In 2025, enterprise tech vendors will be laser-focused on revenue influence, AI-powered efficiency, and content authority. Marketing budgets will be aligned with pipeline velocity, not vanity metrics.

The post From Spend to Strategy: How Enterprise Tech Vendors Are Reshaping Marketing in 2025 appeared first on Best Marketing Automation Software, Tools, Vendors & Solutions.

Chris Brownlee, the SVP of Product at Yext, explains why brands must adapt to Gen Z’s social media search habits to remain relevant and competitive. This article originally appeared in Insight Jam, an enterprise IT community that enables human conversation on AI.

Recent data has shown a fundamental change in how Gen Z discovers and evaluates products and services. More than two-thirds of Gen Z consumers now start their search journeys on social media platforms like Instagram and TikTok, bypassing traditional search engines altogether. This behavioral shift signals a broader evolution in digital habits and raises urgent questions for brands about how and where they appear online.

A Generational Shift in Information Search

The trajectory of digital interaction across generations shows a clear shift in how information is sought and processed. Generation X grew up in an era of analog technology, where information was often accessed through physical means like newspapers and directories. Millennials witnessed the advent of digital technology during their formative years, using early computers and mobile phones, which shaped their search behaviors and communication styles.

In contrast, Gen Z represents the first truly digital native generation. Now in their early to late twenties, they have grown up with high-speed internet, social media, and instant access to information. This generation is now entering the market as influential consumers with disposable incomes and purchasing power. Though Generation Alpha (born 2010 to 2024) is still emerging, it is evident that this group will be influenced by advancements in AI and voice technology.

The Rise of Social Media as a Search Tool

The rise of social media platforms as primary search tools for Gen Z is a game-changer for brands. Unlike previous generations, which primarily relied on traditional search engines like Google, Gen Z users increasingly turn to platforms like Instagram and TikTok for product recommendations, service reviews, and brand discovery. This shift highlights the need for brands to cultivate a strong presence on these platforms to capture the attention of this demographic.

Older generations are also adapting to these new search habits. With advancements in technology, users are now accustomed to receiving direct answers from AI assistants like ChatGPT and voice-activated devices rather than sifting through lists of links. This emphasizes the importance for businesses to ensure that all their online information, such as addresses, opening hours, and other factual details, is accurate and up-to-date. Inaccurate information can lead to misinformation and diminish trust, making it critical for companies to maintain control over their digital footprint.

The Multi-Platform Approach

In today’s digital landscape, information is accessible within seconds, setting high expectations for quick and accurate results. Research indicates that 50 percent of Google users, regardless of age, abandon a search result within nine seconds, and only 9 percent venture beyond the first page of results. Additionally, recent data suggests that discoverability is influenced by the breadth of platforms a brand utilizes. Brands that maintain a presence across multiple publishers see increased click-through rates from Google.

Interestingly, around 17 percent of website traffic originates from sources other than Google. This statistic highlights the importance of not relying solely on one platform for data management and visibility. Brands must ensure they are present and consistent across various digital channels to maximize their reach and engagement.

The Impact of Data Consistency

For Gen Z, authenticity and trustworthiness are pivotal factors in their purchasing decisions. They scrutinize brands based on their product offerings and how they present themselves online and engage with customers. Any inconsistencies in a brand’s digital information can lead to negative reviews and damage its reputation. This generation is especially vocal about their experiences on social media and review platforms, which can significantly influence other potential customers.

Furthermore, search algorithms like Google prioritize accuracy and consistency. Discrepancies in information, such as conflicting opening hours across various platforms, can confuse algorithms and negatively impact a brand’s search ranking. Companies that appear lower in search results are less likely to be noticed by users, regardless of age.

Navigating the Digital Landscape

Many businesses find maintaining accurate and consistent information across numerous digital platforms daunting. The complexity increases with the number of locations and information points a company needs to manage. To effectively navigate this challenge, businesses should consider employing a knowledge graph – a comprehensive tool that consolidates all data and information in one place. This allows brands to manage their digital footprint efficiently, ensuring consistency across all touchpoints.

A knowledge graph enables businesses to track and update information in real-time, ensuring that potential customers receive accurate details when they search for products or services. This proactive approach not only helps in reaching Gen Z but also caters to customers across all generations.

The evolving digital landscape requires brands to adapt their strategies to meet the expectations of a new generation of consumers. With Gen Z leading the shift towards social media as a primary search tool and the rise of multi-platform information sources, businesses must prioritize their digital presence. Ensuring data accuracy and consistency across all platforms is crucial for maintaining trust and enhancing discoverability. By leveraging advanced tools like knowledge graphs and embracing a multi-platform approach, brands can effectively engage with today’s digitally savvy consumers and stay ahead in the competitive market.

The post Embracing the Digital Shift: Why Brands Must Adapt to Gen Z’s Social Media Search Habits appeared first on Best Marketing Automation Software, Tools, Vendors & Solutions.

The editors at Solutions Review have summarized some of the most significant ways AI has impacted marketing jobs, hiring, skillsets, and more.

One of the least surprising things someone can say in 2025 is that artificial intelligence (AI) has impacted marketing jobs. What is less clear is the specific impact AI has had on those jobs and whether marketers have cause for concern. As we see AI integrated into marketing operations at unprecedented levels, the form and function of a company’s marketing team will inevitably continue changing and evolving.

To keep track of those changes, the Solutions Review editors have outlined some of the primary ways AI has changed marketing, what marketers can do to remain agile during those changes, and what the future may hold for them and the technologies they use.

Note: These insights were informed through web research using advanced scraping techniques and generative AI tools. Solutions Review editors use a unique multi-prompt approach to extract targeted knowledge and optimize content for relevance and utility.

How Has AI Changed the Marketing Workforce?

In just a few years, the integration of AI into marketing has dramatically restructured the roles, responsibilities, and required skill sets in the marketing industry. This transformation has been freeing for many, as AI has streamlined their workloads and empowered them to focus on more specialized, high-value tasks and projects. However, it’s not uncommon for marketers to feel uneasy about the rapid adoption of these technologies, as they have already proven capable of rendering some tasks and roles nearly obsolete. Here are some of the job roles that have been impacted the most by AI:

Data Analysis

Traditional market researchers and marketing data analysts have arguably seen the most disruption from AI. Where these professionals were previously responsible for collecting and analyzing large data sets, LLMs can perform the same task exponentially faster than humans. Rather than relying on historical data and analyses, AI allows marketers and data scientists to forecast trends and customer behavior accurately. These predictive marketing capabilities make it easier and more cost-effective for businesses to anticipate market shifts, prepare strategies to respond to them, and allocate resources to the priority tasks.

Content Creation

Copywriting is another area that has been hit hard by the impact of AI. While generative AI likely won’t replace copywriters entirely, these tools are restructuring how marketers create blogs, social media posts, advertising copy, and product descriptions. New generative AI tools are hitting the market all the time now, and most of them can easily reduce the time and resources it takes to get brand-specific, personalized, and targeted content out the door.

HubSpot released a report in 2024 that outlines the specific productivity gains AI can provide to marketers. In their research, they found that:

• 68 percent of marketing leaders reported ROI on their AI investment.
• 75 percent of marketers say they use AI to reduce manual task time.
• 86 percent of marketers report that AI saves them 1+ hours a day by streamlining creative tasks.

With productivity gains like that, using AI and generative AI in marketing is unlikely to go away anytime soon. There’s even potential that, as these technologies advance even further, they could eliminate some of the industry’s entry or mid-level copywriting roles, leaving content creation to a mixture of senior directors and AI tools.

Customer Management

Thanks to AI, how marketers interact with customers has also undergone significant changes. AI-powered chatbots and virtual assistants can provide immediate, 24/7 customer support while gathering valuable insights on customer needs and, when needed, route customers to a human representative or even schedule a meeting on their calendar to follow up with an active or prospective customer. AI can also automate the creation of customer journey maps with complex pattern recognition tools, enabling customer management, service, and marketing teams to track, predict, and respond to more customer behaviors on more channels and with more efficiency than before.

While these roles are less likely to disappear, they will continue to evolve in response to AI technology developments, and it will fall on the human professionals to learn how to navigate and utilize these tools to maximize productivity and ensure consistent customer satisfaction.

The Emergence of AI-Centric Marketing Roles

The impact of AI on marketing is significant, but the most dramatic effect on the industry is the influx of new, AI-specific roles that these technologies have necessitated. These specialized roles range from AI content strategists to algorithmic targeting specialists and generative AI prompt engineers, and have grown rapidly. LinkedIn’s Skills on the Rise report says as much, reporting that AI literacy is the fastest-growing skill that “professionals are prioritizing and companies are increasingly hiring for.”

However, as AI systems become increasingly sophisticated, many functions requiring human specialists could become automated features within integrated marketing platforms. This could lead to a future where the first generation of AI marketing specialists we’re seeing enter the market could ultimately be transitional figures—bridges between traditional marketing and fully algorithmic approaches that require minimal human intervention beyond initial strategic direction.

AI-centric marketing roles will remain invaluable, and traditional marketers who don’t prepare themselves for those new roles will likely face fewer career prospects and mobility. The industry’s historical pattern of absorbing new technologies suggests that we could enter a 5-7 year window where hybrid capabilities are highly sought before a new status quo is established.

Like Mike Maynard said on Forbes, “AI is data for the masses, based on masses of data. Let AI gather all the data. Your success will be determined by whether you use it intelligently, ethically, and responsibly.” That was true when he said it in 2023, and it’s just as accurate today.

Upskilling for the Future

Upskilling has been a major buzzword the last couple of years, and with good reason. For marketers specifically, the necessity of developing AI competencies goes beyond conventional professional development—it represents an imperative that will determine career viability in the coming decade. For example, Christina Inge—author of “Marketing Analytics: A Comprehensive Guide and Marketing Metrics,” and instructor at the Harvard Division of Continuing Education’s Professional & Executive Development—says that AI might not take your job, but “It will be taken by a person who knows how to use AI. So, it is very important for marketers to know how to use AI.”

The specific skills marketers must develop go beyond basic tool proficiency. For marketers to remain competitive, they should pursue more sophisticated skills, including algorithmic literacy to understand how AI systems make decisions, data architecture expertise to ensure these systems receive appropriate inputs, ethical judgment to navigate questions of privacy and manipulation, and perhaps most critically, the ability to identify the boundaries where human judgment should supersede algorithmic recommendations. These multi-dimensional competencies cannot be acquired through conventional professional development paths or weekend workshops, but require more intentional, hands-on experiences.

For marketing leaders, this reality will demand a fundamental reconsideration of team structures, hiring criteria, and developmental pathways. The organizations that treat AI competency as merely another skill to be added to job descriptions will have a harder time navigating this transition than businesses that invest the time and resources necessary to reimagine their marketing departments as learning organizations explicitly designed to absorb, evaluate, and integrate emerging capabilities while preserving the human judgment that remains the core of marketing.

AI Will Augment Marketing Jobs, Not Replace Them

Narine Galstian—the CMO at SADA, an Insight company—sums up the impact of AI on marketing jobs like this: “To truly harness AI’s potential, marketers must adopt a human-centric approach. This means focusing on how AI can augment human capabilities rather than replace them. By combining the power of human creativity with the efficiency of AI, marketers can create truly innovative and effective campaigns.”

The AI impact on marketing jobs is an evolving, fluid thing. As clear as its repercussions have already proven to be, the continued development and integration of new AI technologies will result in the impact being an ongoing, ever-changing reality for professionals to reckon with. However, as dramatic as the effects might be, the expertise marketing professionals bring to the industry will never go out of style. They might need to pivot their skillsets to adapt to new or emerging needs, but the creativity of a human mind will remain an essential piece of marketing.

Want more insights like this? Register for Insight Jam, Solutions Review’s enterprise tech community, which enables human conversation on AI. You can gain access for free here!

The post What Will the AI Impact on Marketing Jobs Look Like in 2025? appeared first on Best Marketing Automation Software, Tools, Vendors & Solutions.

The editors at Solutions Review are exploring the emerging AI application layer with this authoritative list of the best AI agents for marketing teams to consider working with as they streamline marketing processes.

The proliferation of generative AI has ushered in a new era of marketing automation, and AI agents are at the forefront of this transformation. From embedded copilots that analyze spreadsheets to autonomous agents that track customer behavior, answer questions, or automate marketing tasks, AI agents are shaping and reshaping how forward-thinking organizations understand and act on their marketing information.

In this up-to-date and authoritative guide, our editors will spotlight some of the top AI agents and agent platforms available today for marketing teams to help you find the right tool for your specific needs—whether you’re an email marketer looking to automate your outreach, a sales professional who wants to streamline the handoff between departments, or a customer service agent who is augmenting their team’s capabilities with AI.

This resource is designed to help you:

• Understand what makes AI agents different from traditional automation tools
• Explore the capabilities and limitations of each available agent or agent platform in the marketplace
• Choose the best solution for your team based on use case, skill level, and scalability options

Note: This list of the best AI agents for marketing was compiled through web research using advanced scraping techniques and generative AI tools. Solutions Review editors use a unique multi-prompt approach to employ targeted prompts to extract critical knowledge and optimize content for relevance and utility. Our editors also utilized Solutions Review’s weekly news distribution services to ensure the information is as close to real-time as possible. The list is organized in alphabetical order.

The Best AI Agents for Marketing Teams

AirOps

Use For: This AI workflow platform is built for content teams and blends human expertise with AI automation to drive demand at scale.

The AirOps feature suite can help marketing teams win customer attention across SEO and Answer Engine Optimization (AEO) with custom, purpose-built content. It aims to augment a company’s team and future-proof them in the “AI age” by equipping them with the resources they need to remain relevant and competitive.

Key Features:

• Automate the process of building detailed briefs that meet customer search intent.
• Define brand attributes in customizable Brand Kits that AirOps’ AI agents can use to create custom content automatically.
• Ground content with real-time data from Google Search and web scraping.
• Keep content fresh and up-to-date with tools for autonomously updating copy, links, and structure.

Get Started: Since its launch in 2023, AirOps has expanded its capabilities to help its marketing and agency users improve their SEO and AEO efforts, launch programmatic campaigns, and more. Its three pricing models—Solo, Scale, and Agency—aim to cater to different use cases and team sizes.

Conversica

Use For: Bring human-like conversational experiences to each stage of the marketing and sales funnel with Conversica’s Revenue Digital Assistants (RDAs).

Conversica’s RDAs are fueled by “billions of interactions and exchanges” and use proven skills and strategies to deliver personalized, conversational marketing experiences across channels and languages and at scale. Other use cases include personalized lead follow-ups, AI-powered lead nurturing, and GPT-powered web chats.

Key Features:

• Two-way, tailored dialog systems drive leads, prospects, and customers toward business objectives.
• Optimized fact collection ensures accurate and relevant information from a brand’s website and knowledge bases.
• RDAs can validate and schedule meetings with inbound leads.
• Out-of-the-box integrations with CRM, MAP, and Customer Success platforms.

Get Started: Conversica’s AI agents are included in its broader Conversation Automation Software for Revenue Teams suite. Companies can request a free demo to see firsthand how Conversica’s capabilities can help their marketing, sales, and customer success teams.

Gumloop

Use For: Automate your team’s search engine optimization (SEO) efforts, create custom social media workflows, capture real-time brand sentiment, analyze documents, and more.

Gumloop’s AI workflows and agents can be created and configured for multiple marketing automations, all from a user-friendly visual interface. For example, marketers can set up AI workflows to search Google for keywords, scan competitor sites, monitor content performance, and stay ahead of search trends.

Key Features:

• Connect to the latest models of ChatGPT, Claude, Gemini, Grok, DeepSeek, and more.
• Build customized SEO tooling based on custom use cases.
• Gumloop’s AI can filter through comments about a brand to track customer sentiment and inform relevant users when a situation requires their attention.
• Integrate with leading SEO, analytics, and social media tools without paying for an extra subscription.

Get Started: Gumloop offers several models to provide users or teams with the necessary capabilities to automate their work. The platform is growing rapidly—it started 2025 with a successful Series A funding round and has released new features and updates for its toolset every month.

Lyzr AI

Use For: Automate content creation, campaign management, customer engagement, and other marketing efforts with over 40 unique AI agents.

Lyzr’s AI agents can help your team automate dozens of marketing functions across departments and campaigns. Teams can also build reliable, private, and self-learning AI agents with the Lyzr Agent Studio. If needed, the team at Lyzr can even help their users build custom agents over a call.

Key Features:

• Automate campaign scheduling and execution efforts.
• Generate SEO blogs, articles, newsletters, and ad copies with Lyzr’s Content Generation Agent.
• Use agents through Lyzr’s SaaS platform or host them within your own infrastructure
• Connect smoothly with the CRM, 
ERP, LLMs, and cloud platforms your team already uses.

Get Started: In addition to Lyzr’s AI agent builder, companies can utilize Skott, a fully private AI marketer that runs locally on the client’s cloud. Skott can generate blogs, perform market research, publish content across channels, and ensure information is protected in the cloud.

Salesforce

Use For: Salesforce’s Agentforce suite includes AI-powered, agent-driven tools for launching marketing campaigns, creating targeted content, and driving unified customer conversations.

Users have multiple avenues for creating agents with Salesforce. For example, they can customize an out-of-the-box agent to a specific industry or use case, use natural-language instructions to tell Agentforce the tasks they want an agent to manage, or start by assigning a goal to the agent and adding guardrails or further instructions as needed.

Key Features:

• Create custom, predictive AI models in several clicks, with no coding required.
• Scale content personalization by having Agentforce automatically generate on-brand content for each target audience.
• Use agents to create target audience segments in minutes.
• Connect customers to AI agents for service requests (i.e., appointment booking, offer redemptions, etc.).

Get Started: Agentforce is an AI-powered, low-code agent builder that streamlines the process of creating and customizing agents. Users can simply write a description of the agent they want to develop, and the system will help them build it. Pro-code tools are also available to teams who need to take their agents even further.

Zapier

Use For: Build and deploy intelligent AI agents with plain English prompts in just a few minutes. The agents can process leads in seconds, answer emails, help sales teams manage calendars, and more.

When configuring a behavior trigger or action field with Zapier’s Agents, users can instruct the agent to always use the same value, pick from a specific set of values, have it guess the value, or not set any value. For example, users can create agents for multiple use cases, including sales, internal meetings, customer support, or email marketing.

Key Features:

• Zapier Agents automatically sync with the latest data from other platforms in a tech stack.
• Set up behaviors to handle everything from sending your team reminders to updating your CRM.
• Personalize outreach with agents that study customer profiles and use the data to create personalized emails.
• Qualify inbound leads with an agent that researches new leads and enriches them with key details.

Get Started: Zapier Agents are currently in beta. The free option allows users to experiment with AI agents, while the paid plans enable them to scale as their team and goals change over time.

Want the full list? Register for Insight Jam, Solutions Review’s enterprise tech community, which enables human conversation on AI. You can gain access for free here!

The post 13 of the Best AI Agents for Marketing Teams to Consider in 2025 appeared first on Best Marketing Automation Software, Tools, Vendors & Solutions.

Solutions Review’s listing of the best marketing automation software companies is an annual look into the solution providers included in our Buyer’s Guide and Solutions Directory. The Solutions Review team participates in affiliate programs and may make a small commission from products purchased through this resource.

Manual management of marketing campaigns is becoming an increasingly lofty task, especially since customers use more channels than ever. Each channel creates new areas for data to be collected and harnessed. Keeping up with the competition takes much more than a superior product; it comes down to effective marketing strategies. A marketing automation tool can help your company eliminate the monotony of campaign management while keeping your valuable customers engaged. 

However, choosing the best marketing automation software vendor can be complicated, as it requires constant market research and often comes down to more than technical capabilities. With that in mind, Solutions Review editors compiled the following list to spotlight some of the best marketing automation providers for 2025 (and beyond!).

Our editors gathered this information via online materials, reports, product demonstrations, conversations with vendor representatives, and free trial examinations. Companies are listed in alphabetical order.

The Best Marketing Automation Software Companies for 2025

Act!

Description: The Act! platform provides CRM and marketing automation capabilities for small to medium-sized businesses across industries. Its capabilities include sales pipeline management, visual dashboards, customer management, centralized customer data, business insights, opportunity tracking, real-time metrics, personalized marketing campaigns, automated workflows, landing pages, and integrations with other leading marketing tools. The provider also has an extensive library of support resources such as software tutorials, video training, and a ticket system for in-depth issues. 

ActiveCampaign

Description: ActiveCampaign provides email marketing, marketing automation, CRM, and Sales Automation solutions to clients across industries. Its Customer Experience Automation (CXA) platform has email marketing, marketing automation, CRM, and sales automation solutions for businesses across industries. Their marketing automation tool offers a simple visual overlay, showing users how automations connect and the features of each campaign. The platform also provides social media analysis and deep site tracking tools. Enterprise customers can also access an “expert level” team member to consult or help with the platform. 

Act-On

Description: Act-On provides a marketing solution suite capable of streamlining or eliminating many tasks marketers are responsible for managing. It tracks and collects analytics automatically and uses the information to improve marketing techniques. Users gain complete visibility into unknown and known activity on their website. With the collected data, Act-On then automates nurturing based on user preference. It even segments customers and leads into specified categories for you. The platform is an integrated tool for many CRMs and provides professional services to clients who need help building an effective marketing strategy. 

Adobe

Description: With Adobe Campaign, companies can use customer data to create, deliver, and manage B2B cross-channel marketing campaigns. The software includes central workflow management, personalized email marketing tools, customer data management, cloud services, and learning tools to help you and your team stay on top of their email marketing skills. Multi-channel site design is simple and synchronized to maintain its brand image across platforms. Adobe allows marketers to follow each step in the customer journey. They also collect deep and predictive analytics to enhance marketing campaigns.

Blueshift 

Description: Blueshift offers an AI-driven platform for cross-channel marketing solutions for email marketing, marketing automation, mobile marketing, audience targeting, predictive intelligence, audience segmentation, and more. With the ability to segment customers based on real-time data and predict their future actions, the tool provides a unique solution for organizations looking to take advantage of artificial intelligence and machine learning across their email, SMS, mobile, website, advertising, and other channels.

Dotdigital

Description: Dotdigital has spent over twenty years helping brands across industries improve their marketing strategies, boost engagement, and maintain customer connections. Its cross-channel digital engagement and marketing platform equips businesses with multi-channel capabilities for communicating with customers, targeting leads, and using analytics to power data-driven campaigns that resonate with audiences. The company can also work directly with users via managed, creative, training, and customer support services. The company is based in London, and its platform is used in over 150 countries. 

GetResponse

Description: GetResponse offers a suite of simple and robust solutions that can be scaled and customized for small and large organizations. The company’s marketing solutions include automation, CRM, webinar software, email design, and other tools to help businesses create customer journey scenarios. GetResponse’s workflow designer uses simple block arrangements for conditions, actions, and filters. Customer profiles include tagging and scoring so that users can build detailed segmentations. The company is headquartered in Poland and has offices around the world. 

HubSpot

Description: HubSpot offers a variety of capabilities centered around marketing, sales, and customer service. HubSpot’s free CRM connects all the data users need to run effective marketing campaigns, and their marketing hub comes with easy-to-use customization options. Users can modify their website or mobile site without coding knowledge; they can drag-and-drop pages, posts, landing pages, and more. The marketing hub automatically tracks and reports on customer interactions. This data helps measure a campaign’s effectiveness or build new automations.

Insightly

Description: Insightly is a vendor that offers both a CRM platform and a robust marketing automation platform. This solution provides in-depth customer journey management, an intuitive drag-and-drop email and newsletter creator, and more. Users can open up two-way communication with their customers through embedded forms and landing pages while analyzing and visualizing customer insights with Insightly’s advanced analytics and reporting engine. CRM features include visual relationship webs, easy sale-to-project transition, and mobile application access.

Iterable

Description: Iterable is a cross-channel marketing platform that emphasizes the customer experience by giving users the tools to interact with customers on various channels. Marketers can harness data for campaign activation and behavior-based personalization, and the dashboard lets marketers drag-and-drop workflows and activate customer data. Its other AI-powered capabilities include real-time behavioral data, A/B testing, customizable predictive goals, customer data tracking, audience segmentation, and an extensive network of over one hundred partner integrations with leading marketing providers.

Keap

Description: Keap offers small businesses access to a marketing automation platform and CRM. The small business approach is emphasized as it only includes one user account in the base product. Keap offers collaboration with an onboarding expert to initiate setup for clients new to marketing tools. The platform provides a centralized view of customer data that enhances campaign automation and reporting. Keap helps users understand how audiences respond to campaigns so modifications can be made when necessary. They also provide hundreds of business apps, so you can craft the platform that fits your needs.

Klaviyo

Description: Klaviyo provides growth-focused e-commerce brands with a marketing automation platform designed to help drive sales with targeted and relevant email, Facebook, and Instagram marketing campaigns. The platform includes segmentation, web tracking, autoresponders, automated email flows, reporting, A/B testing, email content creation, and more. Klaviyo also tracks important data from whichever e-commerce platform a company uses, thanks to its integrations with leading platforms like Shopify, BigCommerce, and Magento. Klaviyo uses flexible pricing models that don’t involve annual contracts, so companies only pay for the tools and features they use. 

Lead Liaison

Description: Lead Liaison offers cloud-based marketing and sales automation solutions to businesses of all sizes. Their Lead Management Automation platform combines lead capture, content creation, social media engagement, and more. Prospects can be targeted based on engagement, demographics, and social info. This data is also used to trigger responsive marketing techniques. Due to the focus on lead generation, Lead Liaison reveals critical moments of a buyer’s journey to the sales team. Salespeople also receive daily lead reports, including “Buy Signals, ” indicating the right time to contact a prospect. 

LeadSquared

Description: LeadSquared brings marketing automation to key time-consuming areas so marketers and salespeople have time to focus on significant projects. This is accomplished through automating engagement with leads and customers. Their software easily captures lead and activity data across channels, making each engagement meaningful and targeted. LeadSquared helps more than just marketers since salespeople can easily access critical data to find sales-ready leads to target. The platform uses machine learning to forge a deeper understanding of conversion attributes.

Maropost

Description: Maropost Marketing Cloud provides tools for building complex customer journeys. The platform allows marketers to connect with customers across email, web, mobile, and social media channels. Users can create and automate workflows from a simple dashboard on every channel and lifecycle stage. Event-driven workflows nurture visitors on a path that reflects their behavior. Machine learning tools utilize data to make personalized recommendations on your website and include a single customer view combining all available data on a customer. This creates deep segmentation functionality based on both manual and automatic data. 

Oracle

Description: Oracle offers a variety of cloud marketing products, including Bronto, Eloqua, Responsys, and more, each with unique strengths and customization tools. For example, Eloqua is the B2B marketing option, and Bronto is for B2C. Each provides campaign management tools to deliver relevant content to target audiences. These two equip marketers with lead and campaign management tools to engage the right audience at the right time in their purchasing journey. This can be accomplished across multiple channels like email, display search, web, video, and mobile.

Ortto

Description: Ortto, previously known as Autopilot, is a customer journey and data platform that uses marketing automation and artificial intelligence (AI) technologies to help e-commerce, non-profit, SaaS, and B2B businesses develop meaningful connections and experiences with their audiences. Its solution suite offers tools for website tracking, lead managing, email marketing, business intelligence, artificial intelligence (AI), Facebook retargeting, sales dashboards, SMS marketing, automation, audience segmentation, and more.  

Salesforce

Description: Salesforce’s marketing automation platform, formerly Pardot, can directly integrate with its CRM system to harness all available data and use it to align sales and marketing efforts, generate leads, and maintain engagement. Salesforce’s Marketing Cloud Account Engagement Capabilities include lead scoring, real-time sales alerts, email marketing campaigns, lead segmentation, multi-channel engagement, account-based marketing, lead management, reporting, predictive analytics, and more. It tends to focus on mid-market and enterprise organizations in B2B, including financial and high-tech markets. 

SharpSpring

Description: SharpSpring, from Constant Contact, offers a marketing automation platform for businesses and agencies. Their behavioral-based tracking tool helps users understand what motivates each click. It also enhances email automation, as customers are tracked after the click for increased personalization. SharpSpring’s visual workflow builder includes branching logic to engage leads correctly. Users can customize buyer personas to improve segmentation. Detailed data collection allows critical marketing decisions to be made with logic and efficiency. 

Upland Adestra

Description: Adestra, a Upland product, is a multi-channel marketing automation solution designed to drive conversions, engage audiences with AI-powered personalization, equip teams with automation tools, and provide marketing teams with advanced data enrichment tools. Other capabilities include AI data-driven persona segmentation, multi-layer account structures, a dynamic content editor, automated customer journeys, a drag-and-drop journey builder, customizable email delivery times, email data visualizations, and connectivity with a suite of technical integrations. As an email marketing company first, Adestra includes a variety of templates with mobile and web optimization. 

VBOUT

Description: VBOUT is a multi-channel marketing automation solution for collecting leads with a customer-centric approach. The company provides a variety of marketing automation capabilities in its flagship platform. Marketers save time using VBOUT, as everything they need is in one place. Its dashboard uses drag-and-drop tools for creating landing pages, customer journey builders, and social media management. Users can add automation to their campaigns, track analytics in critical areas, send reports in user-defined intervals, and more. It begins segmenting leads from the moment their email address is obtained. 

Zeta Global

Description: The Zeta Marketing Platform (ZMP) can be activated on every offline and online marketing channel—including social media, SMS, websites, and email—and uses advanced artificial intelligence (AI) technology to analyze billions of customer data signals to predict intent, create personalized experiences, accelerate brand growth, and more. The company works with enterprises across the retail, telecommunications, travel, hospitality, automotive, financial services, consumer packaged goods (CPG), and other industry sectors. 

Zoho

Description: Zoho is a multinational company specializing in software development, cloud computing, and web-based business tools across significant business categories. Its solution suite includes Zoho Marketing Automation, a multi-channel software platform designed to help marketers generate sales-ready leads. The platform comes equipped with capabilities for lead generation, customer journey management, lead qualification, customer behavior tracking, real-time analytics, lead nurturing, multi-channel automation, personalized campaigns, e-commerce marketing, and more.

The post 23 of the Best Marketing Automation Software Companies for 2025 appeared first on Best Marketing Automation Software, Tools, Vendors & Solutions.

As part of this year’s Insight Jam LIVE event, the Solutions Review editors have compiled a list of predictions for 2025 from some of the most experienced professionals across the Enterprise Resource Planning (ERP), Business Process Management (BPM), and broader WorkTech marketplaces.

As part of Solutions Review’s annual Insight Jam LIVE event, we called for the industry’s best and brightest to share their ERP, BPM, CRM, and Marketing Automation predictions for 2025 and beyond. The experts featured represent some of the top WorkTech solution providers with experience in these marketplaces, and each projection has been vetted for relevance and ability to add business value.

WorkTech Predictions for 2025 and Beyond

Thomas Butta, Chief Strategy and Marketing Officer at Airship

Data willingly and simply provided will be key to unifying customer experiences.

“While walled gardens are nothing new, the walls keep getting higher—fortified by data deprecation and growing privacy regulations. In 2025, industry giants like Meta and Google will continue to tighten their grip on audiences, keeping more traffic on their pages while scraping content for large language models without an equitable value exchange. The result: plummeting referral traffic and soaring acquisition costs.

“Now more than ever, brands must prioritize direct customer relationships or risk being disintermediated. Data willingly and simply provided and purposefully solicited will be key to unifying experiences everywhere customers choose to interact–on the web, in apps, and everywhere in between.”

Murray Campbell, Global Product Manager (Regulatory) at AutoRek

Compliance demands drive the rise of automation  

“Regulatory pressures aren’t just tightening the screws—they’re turbocharging the case for compliance automation. For example, the Securities and Exchange Commission (SEC) is expanding its budget and workforce to unprecedented levels. As global authorities enforce increasingly complex mandates, businesses are drowning in a sea of audits, filings, and reporting requirements. The old-school, manual approach to compliance is officially obsolete.

“Regulators are increasingly favoring firms that adopt advanced technology, recognizing that automated processes provide a level of traceability and precision unattainable with manual methods. As the digital economy grows, transaction volumes surge, and regulatory demands evolve, sticking to outdated methods for critical processes becomes an inefficient and costly approach.

“In this high-stakes landscape, automation isn’t a luxury—it’s an essential component of doing business today. By automating tasks like validations and cash transfers, firms can achieve greater speed and precision in handling data-related processes. This also frees resources to focus on activities that benefit from human expertise and creative problem-solving.”

Mehdi Daoudi, CEO of Catchpoint

DevOps Supercharges AI-First Infrastructure in 2025

“DevOps will evolve to meet the unique demands of AI-driven infrastructure, where complex ecosystems of data, machine learning models, and interconnected systems power nearly every industry. This AI ecosystem involves managing vast amounts of data, training and deploying machine learning models, and supporting scalable compute resources—all requiring specialized infrastructure. DevOps teams will expand their role, going beyond workflow automation to fully owning and optimizing these AI-first infrastructures. They’ll set best practices for managing the speed, scale, and reliability of AI applications, helping organizations harness AI efficiently and securely as it becomes central to operations.”

Edge Compute: The New Frontier in 2025

“Edge computing will emerge as the new frontier, enabling real-time data processing closer to where it’s generated—whether in autonomous vehicles, IoT devices, or remote facilities. By minimizing latency and reducing the load on centralized cloud resources, edge computing will transform industries like manufacturing, healthcare, and retail with faster, more reliable data-driven insights. This shift empowers applications that demand ultra-low latency, increased security, and local processing capabilities, pushing businesses toward a future where edge intelligence enhances user experiences, operational efficiency, and scalability like never before.”

Bill Buckley, the SVP of Engineering at CloudZero

Damantha Boteju, Chief Product and Technology Officer at Configit

Manufacturers Will Lean into Generative AI for Augmentation and Employee Enablement

“One of the significant business benefits of Generative AI is reducing time to market while giving employees time back to work on bigger, more creative projects. Generative AI helps accelerate business processes and reduce mundane work, enabling employees to focus on being creative and putting more effort into better human interactions and collaboration. The most competitive companies in 2025 will be those who understand the power of artificial intelligence and copilots to build on the strength of their employees.”

Daniel Joseph Barry, Vice President of Product Marketing at Configit

The Concept of the Digital Configuration Thread Gains Prominence   

“The digital thread approach is rapidly becoming the data foundation for managing both standard and configurable products. As we move into 2025, we see this concept playing an even more prominent role. That’s because a digital thread can help manufacturers by providing end-to-end insight and traceability, enabling analysis and optimization of product portfolios, and supporting digital twins. However, achieving this approach often requires manufacturers to cobble together information from multiple bills of material (BOMs) in varying formats that reside in disparate systems–typically under the purview of multiple departments. That can lead to misunderstandings, inconsistencies, control issues, and maintenance concerns, but Configuration Lifecycle Management (CLM) produces a ‘digital configuration thread’ that can help manufacturers manage product configurations better.”

Manufacturers Will Look to Configuration to Help with Workforce Challenges

“Demands on manufacturers have never been higher, but U.S. manufacturers are struggling with a workforce gap. As seasoned workers hit retirement age, manufacturers will need to ensure they can capture the institutional knowledge of these employees in a more efficient way. That means moving away from a document- and experience-driven process to capture information from individual contributors. A configuration lifecycle management approach is one approach to doing this, laying the foundation for better collaboration and innovation by centralizing product configuration information so it can be shared among multiple departments. This capability lessens the sting of retiring pros and the fear of losing a company’s ‘brain trust.'”

Henrik Hulgaard, Vice President of Product Management at Configit

Configurability Will Become a Bigger Priority 

“As we saw in a recent survey of Product Lifecycle Management (PLM) professionals conducted by CIMdata, configurability has become a bigger priority, and we anticipate that trend will continue in 2025. This will drive the need for new ways to support customization, as traditional processes and tools won’t suffice. Many manufacturers still try to manage configurable products and product variants as if they were standard products, but managing configurable products requires a different approach. This leads to the next prediction.”

The Adoption of Modularity Will Rise 

“We’ll see an increase in modularity due to the expanded demand for customization and increased regulations and compliance mandates. For instance, sustainability regulations that require reuse and recyclability, such as those we see in the U.S. and EU, are easier to meet with a modular approach. Many early adopters have already implemented a modular approach to their products, and we’ll see more adoption in the new year, as modularity benefits manufacturers by reducing time, effort, and costs. It enables them to meet customization demands more cost-effectively by reusing modules (collections of features or pre-assembled parts) rather than custom engineering.

“Adopting modularization can be demanding, as it requires process changes, but with the combined compelling events of regulations and competition, manufacturers can justify the investment and reap the benefits. Forward-thinking manufacturers have already recognized this and are adopting new approaches centered on modularity and transitioning from engineer-to-order (ETO) to more customize-to-order (CTO) approaches that better meet their customers’ needs and enable faster response and delivery of solutions with minimal impact on engineering resources.”

Rahul Pradhan, Vice President of Product and Strategy at Couchbase

Agentic AI Poised to Power Next Wave of AI Innovation in 2025

“In 2025, the trajectory of AI will be shaped by the rise of agentic AI—proactive, intelligent agents that go beyond basic chatbots in an evolution promising a profound transformation for both consumer and enterprise landscapes, accelerating the world into a new era of AI capabilities. With capabilities such as understanding context, setting goals, and adapting actions, agentic AI can complete tasks previously thought impossible by AI.

“For this to be made possible, agentic systems require a compound AI system using multiple models that are moved closer to data sources within security parameters. The systems also need to handle both structured and unstructured data at low latency—all in real-time — to make meaningful, context-aware decisions on the fly. This requires seamless integrations across unstructured data processing, vector databases, and transactional systems for efficient storage and retrieval of diverse data types.

“The companies that will excel in providing these robust integrations and infrastructures will be uniquely positioned to drive the next wave of innovation and value in the AI sector.”

Edge AI Agents: Autonomous Decision-Makers

“As the maturity of Agentic AI advances, edge devices will start to adopt agents that can act autonomously based on real-time data. Edge AI agents, powered by integrated databases, will be able to make decisions in milliseconds, bypassing the need for centralized processing. These autonomous agents will perform tasks like controlling robotic arms in manufacturing, adjusting energy consumption in smart grids, and ensuring patient safety in healthcare facilities. The combination of AI models, local data processing, and autonomous agents will make edge devices intelligent participants in broader ecosystems.”

Steve Rotter, Chief Marketing Officer at DeepL

AI will accelerate hyper-personalized, more consistent marketing.

“We live in a hyper-personalized world—custom coffee, made-to-order clothing, and on-demand news feeds. Brands are even now tailoring their marketing messages and language to every customer in their preferred language, style, and tone. Along with personalization, consistency of language across all streams is central to successful marketing. Research shows that it boosts revenue by 20 percent or more.

“However, achieving this consistency across borders and languages is tough, requiring not only linguistic translation but also cultural adaptation to ensure that messages resonate the right way in different markets. If advertisers and marketers don’t get this right, they’ll open themselves up to misunderstandings, wasted resources, and missed growth opportunities. 2025 will be an exciting year for the marketing world as we start seeing a better understanding of how AI can strengthen customer relationships and help businesses’ bottom lines.”

Jim Palmer, the Chief AI Officer at Dialpad

The AI trust divide will reshape market dynamics in 2025. 

“Organizations that address customer concerns and ensure human oversight to prioritize transparency and ethical governance will gain a competitive edge. Companies that proactively address customer concerns and maintain human oversight will excel in customer retention and navigate regulated markets more effectively than those rushing to market without proper ethics. As consumer awareness grows and regulatory frameworks evolve, the market will increasingly reward businesses that demonstrate responsible AI practices while fostering innovation, leading to a more mature competitive landscape.”

Businesses will grow increasingly skeptical of AI offerings. 

“We’ll see a shift towards industry-specific AI tools as businesses grow weary of generic solutions that fail to deliver on their promises. This skepticism will be fueled by the proliferation of rushed AI products that create more challenges than they solve, leading to stalled adoption and investment among wary buyers.”

The human element of customer service will be redefined.

“As AI handles routine inquiries and administrative tasks, customer service roles will evolve to focus on complex problem-solving and relationship building. This shift will attract and retain more skilled professionals who can dedicate time to nuanced customer needs, leading to improved job satisfaction and career advancement opportunities. Organizations that successfully blend AI efficiency with meaningful human interactions will see higher customer satisfaction and loyalty, while those maintaining traditional high-volume, low-value service models will lag behind.”

Alan Samuels, the Vice President of Data and Product at Encompass Corporation

In 2025, AI Will Move Beyond The Hype and into Practical Application

“As artificial intelligence (AI) matures, 2025 marks a pivotal shift in how the financial industry leverages its potential. Gone are the days of embracing AI for its novelty. In the coming year, financial organizations will focus on pragmatism, problem-solving, and creating measurable value.”

• Solutions-focused AI: Financial firms will focus on scalable solutions that deliver clear, measurable outcomes. AI applications are now subject to rigorous scrutiny regarding their origins, training data, and compliance with security standards.
• Accelerating Digital Transformation: Advances in natural language processing (NLP) and computer vision are enabling AI to process non-digital information, bridging the gap for businesses reliant on legacy systems.
• The Arms Race in Financial Crime: AI is transforming how institutions detect and prevent fraud, leveraging its ability to uncover patterns and connections hidden in vast datasets while staying ahead in an arms race against increasingly sophisticated bad actors.
• Rethinking Product Development: AI serves as a “co-pilot” for developers, assisting in coding and accelerating the translation of vision into actionable requirements. AI-powered tools are reshaping how financial firms deliver customer experiences, blending efficiency with personalization to meet evolving demands.
• Enhancing CX: AI-powered tools are reshaping how financial firms deliver customer experiences, blending efficiency with personalization to meet evolving demands.
• Corporate Digital Identity (CDI): CDI leverages multiple advanced technologies, including AI, security frameworks, and robotic process automation (RPA), by pulling information from both public and private domains, ensuring it adheres to regulatory requirements, such as documenting sources and demonstrating the provenance of data.

Alexandros Siskos, the SVP of Customer Success and Marketplace Strategy at Everseen

More than Half of Retailers Will Invest in AI Platform Technology.

“As retailers recognize the value of unified AI solutions over piecemeal approaches, we predict that over half of them will adopt AI platform technology to support a growing range of business applications. This platform approach will enable retailers to apply AI-driven insights across business functions such as loss prevention, inventory management, and customer experience. With the tech industry increasingly focused on this market, retailers are well-positioned to integrate foundational AI with tailored applications.”

Casey Ciniello, Reveal and Slingshot Senior Product Manager, Infragistics

Implementing AI Will be a Top Priority in 2025

“By 2025, generative AI will become more integrated into technology, including content creation, software development, and automated decision-making. The shift towards AI will be a top priority and present transformative challenges in 2025, including workforce concerns about job security and resistance among employees hesitant to embrace AI-driven interactions. Traditional mentoring and learning pathways could be disrupted, resulting in limited development opportunities for junior staff and leaving a critical gap in skill-building and career growth.

“To address these challenges, we must adopt a proactive approach to collaboration between human employees and AI tools, emphasizing the unique skills that humans bring to the table, such as creativity, critical thinking, and emotional intelligence. By fostering an environment where employees view AI as a partner rather than a replacement, organizations can alleviate fears and enhance morale.”

JJ McGuigan, App Builder Product Manager at Infragistics

“Industries like healthcare and finance, where compliance with strict regulatory standards is critical, often face extended development timelines due to the rigorous testing required. However, the growing adoption of low-code tools is poised to revolutionize the time needed to adhere to these standards. Low-code platforms not only accelerate app development but also ensure that applications are built in alignment with legal and regulatory requirements. By integrating industry best practices into the development process, low-code solutions will streamline compliance, enabling faster delivery of secure, compliant apps without sacrificing quality or oversight.”

Security-related attacks on AI agents will soon emerge as a critical threat.

“Technology leaders will need “Guardian Agents” to autonomously monitor, manage, and contain AI actions as they work to establish standards for AI oversight. With enterprise interest in AI agents intensifying, next-generation GenAI agents are rapidly reshaping strategic planning for product leaders. Guardian Agents will bring a holistic approach to AI security, integrating compliance assurance, ethics, data filtering, log analysis, and advanced observability. As we move through 2025, the number of product releases deploying multiple agents will rise, supporting increasingly sophisticated use cases. Guardrails, security filters, and human oversight alone won’t be enough to guarantee the safe and appropriate use of autonomous agents.”

Daniel Lereya, the Chief Product and Technology Officer at monday.com

Productization Fuels AI Business Transformation in 2025

“AI has moved beyond the hype and is now a fundamental force transforming business operations. As we move into 2025, the primary challenge won’t be the technology but adopting and integrating AI into existing workflows. Companies must focus on how AI can be embedded directly into platforms, including new and existing processes while extracting real and material business value to enhance and scale operations.

“For AI to truly drive value, it must be accessible, predictable, and trustworthy—solutions that provide clear ROI while seamlessly aligning with how companies already work. Businesses will prioritize AI tools that grow with them and can tackle a wide range of issues, from automating routine processes to solving complex problems across areas like customer service, supply chain optimization, and data analysis—all with minimal disruption and cost.

“Ultimately, success in 2025 will hinge on adopting AI and ensuring its implementation is smooth, scalable, and impactful within existing infrastructures. This will unlock new business opportunities, accelerate growth, and encourage companies to build a unique competitive edge in an increasingly AI-driven world.”

Enterprise Work Management: The Key to Scaling Success

“In 2025 and beyond, enterprise work management will be a cornerstone of business success as companies realize that seamless execution at scale is essential for growth. With hybrid teams spread across offices and remote locations, orchestrating workflows across departments, time zones, and geographies is no longer optional—it’s vital. Businesses that master this alignment will drive innovation and agility and stay ahead in an increasingly digital-first world.”

Unified Platforms Are the Future of Enterprise Tech

“Platforms will reign supreme as businesses consolidate their tech stacks into unified systems for greater efficiency and strategic advantage. With all company data in one place, decision-making becomes faster and smarter, unlocking insights that fuel growth. Companies looking to achieve a complete AI transformation will find it more effective to implement an AI platform as an integrated platform essential for unlocking its full potential across all aspects of the business. In a data-driven world, a holistic platform isn’t just nice; it will be a must-have for organizations looking to establish a unique competitive edge.”

Amol Dalvi, the VP of Product of Nerdio

Demand for Cost Efficiency and Resiliency in VDI and DaaS 

“Looking into 2025, we’ll see an increase in demand for cost efficiency coupled with robust business continuity and resiliency in virtual desktop solutions. These themes are echoed consistently by our customers who are asking questions like, ‘How do I ensure my AVD desktops remain accessible at all times?’ and ‘How can I meet stringent continuity requirements?’ The shift to cloud VDI solutions has brought many benefits, yet with the growing focus on uninterrupted access, we expect to see an evolving approach to meet both budget and reliability needs.”

Resurgence of On-Premises VDI Solutions 

“I anticipate a resurgence of on-premises VDI solutions in 2025. Azure Stack HCI could offer a VDI option for organizations that require specific data residency or regulatory control, face bandwidth challenges, or may not be fully comfortable relying solely on the public cloud. This trend would be especially significant for highly regulated sectors like healthcare, financial services, and federal government agencies, where tight control over data location and access can be critical. We’re even seeing an uptick in interest for environments where a completely disconnected setup—think submarine-level isolation from the internet—is a real business requirement.”

Stabilization of AVD as a Cloud VDI Leader 

“In the cloud arena, AVD continues to stabilize as a technology, which may encourage broader adoption by businesses that have been slower to make the shift. The improved reliability and usability of AVD, along with the integration of Microsoft 365 into the DaaS landscape, adds interesting new layers of choice. Organizations will need to weigh the flexibility and maturity of AVD against the growing adoption of Windows 365 to determine the best fit for their needs.”

Balancing AVD’s Versatility with Windows 365 Integration 

“As we look ahead, it will be fascinating to see how the market balances these options—whether enterprises lean more into the maturity and flexibility of AVD or focus on the pre-packaged option of Windows 365 for their evolving workforce needs. The decision will hinge on each organization’s unique needs for both flexibility and operational continuity.”

Jonathan Rhyne, CEO and co-founder of Nutrient

“As we embark on the journey of understanding AI’s impact on productivity, particularly in how we create, interact with, and experience documents, we find ourselves at an exciting crossroads. Currently, generative AI is revolutionizing content creation, enabling us to produce new material with unprecedented ease. Additionally, AI’s capability to access and summarize text from images has transformed our interactions with documents, making them more intuitive than ever.

“Looking ahead, I anticipate a significant evolution in how we experience these documents. One of AI’s groundbreaking advancements is its ability to establish a direct interface between humans and computers. While the popularity of natural language chatbots is currently capturing attention, they serve as a preliminary step in demonstrating the potential of transformer models.

“In the coming year, we can expect this new human-computer interface to facilitate real-time personalization of document content. This means that interactions will become dynamic, tailored to individual preferences and past experiences, all while leveraging the most current information available. Over time, the conveniences brought by AI will become so integrated into our daily lives that they will be taken for granted, much like our constant connectivity to the internet today.”

Steve Fenton, Principle DevEx Researcher at Octopus Deploy

Platform Engineering will be thinner.

“Platform engineering has become a path towards DevOps efficiency and developer productivity. In 2025, organizations will realize they can achieve the goals of platform engineering with fewer lines of bespoke code. Instead of trying to build a grand unifying platform, existing tools will provide solutions that reduce fragmentation, apply standards, and integrate security into software delivery.”

Continuous delivery is dead… Long live continuous delivery!

“As organizations shift to platform-as-a-service, Kubernetes, and serverless offerings, they often lose good practices along the way. The solid continuous delivery pipelines they created for traditional self-hosted and IaaS environments had solid practices that should be transferred to new environments.”

Paul Laudanski, Director of Security Research at Onapsis

Cloud migration delays will trigger security emergencies

“As organizations face pressure to migrate their business-critical data to the cloud, many are still dragging their feet. Once migration becomes urgent, especially as we approach deadlines such as SAP’s 2027 cutoff to move to S/4HANA, the rush to transition will lead to mistakes such as leaving remaining vulnerabilities in the code or data you are bringing over. These mistakes could lead to costly delays or re-dos. Organizations still on legacy systems need to modernize their applications immediately to survive in the digital world that is already surpassing them. In 2025, we must prioritize addressing this migration before the risk compounds by way of proper cross-functional planning and execution.”

Lalitha Rajagopalan, co-founder of ORO Labs

Integrating GenAI and no-code solutions into procurement processes will be integral to remaining agile in the face of global changes.

“With natural disasters, geopolitical tensions, and economic shifts on the rise, traditional, pre-built procurement solutions can no longer adapt fast enough to avoid disruptions. GenAI-powered procurement orchestration breaks free from ‘hard-coded’ limitations, allowing companies to dynamically respond as situations evolve. This will be key to eliminating complex systems, improving visibility, and unlocking hyper agility, inherently enabling teams to react faster to potential disruptions, keeping operations not only on track but ahead in an unpredictable world.”

GenAI investments will shift from generic, broad use cases to more specialized, strategic applications.

“As GenAI technologies mature, companies will prioritize tools with clear ROI and targeted use cases. Procurement is especially ripe for transformation, given its exposure to frequent disruptions from global instability and complex third-party networks. By implementing GenAI in this space, companies can replace cumbersome systems with streamlined solutions that enhance visibility, adaptability, and resilience, making it a clear area where specialized GenAI investment can drive tangible results.”

Itamar Golan, Co-Founder and CEO at Prompt Security

The Future of Work with AI

“Contrary to widespread concerns, I don’t expect AI to eliminate jobs in 2025. Instead, it will serve as a powerful tool to enhance human capabilities. Agentic AI systems will work alongside humans, such as in customer service, sales outreach, marketing content creation, software development, and healthcare applications, among others. This means that very soon, 30 percent of our tedious and repetitive tasks will be automated, giving us more time to focus on creative, innovative, and interesting pursuits.

“I believe we will also see a significant shift as the multimodality of AI becomes more mainstream (video, audio, etc.), as opposed to the majority of its use, which has been text-based. This creates new opportunities for human-AI collaboration.”

Organizational AI Adoption

“The democratization of LLM access, driven by ever-decreasing prices, is enabling broader adoption across organizations. Additionally, specialized AI solutions will increasingly be moving away from OpenAI’s dominance, with alternatives like Claude gaining traction in specific domains such as coding, which is something we’re already starting to see.”

Agentic AI

“AI chatbots use generative AI to provide responses based on a single interaction. A person makes a query, and the chatbot uses natural language processing to reply. In my opinion, the next frontier of artificial intelligence will be agentic AI, which employs sophisticated reasoning and iterative planning to autonomously solve complex, multi-step problems. It is poised to enhance productivity and operations across various industries.

“Agentic AI systems process vast amounts of data from multiple sources to independently analyze challenges, develop strategies, and execute tasks such as supply chain optimization, cybersecurity vulnerability analysis, and assisting doctors with time-consuming tasks. I believe that by 2025, we will see a significant increase in resources shifting from single-interaction procedures with LLMs to this multi-step approach of agentic AI, which will gradually solve complex problems for us autonomously.”

Nitesh Bansal, CEO and Managing Director of R Systems

Organizations Must Take A Practical Approach to Generative AI Usage

“It’s no secret that generative AI has already had a significant impact on digital product engineering. It has fundamentally changed the way companies optimize the design and functionality of their products–everything from accelerating ideation and prototyping to user experience and product performance.

“In 2025, we will see more of this, but we will also see organizations take a more practical approach to how they leverage AI. AI has had a lot of hype–and that will continue–but more and more tech leaders will place a higher emphasis on ensuring measurable ROI–especially what can be achieved in the same fiscal year or under 12 months. For example, if an organization requires complex coding to enhance a new product, using AI to automate routine development tasks can free up needed time and gain an immediate benefit.”

There Will Be Continued Innovation Challenges In Digital Product Engineering if Organizations Don’t Embrace Upskilling and Outsourcing

“Innovation in digital product engineering will continue to flourish, but it will not come without challenges. On the technical side, a growing reliance on data, AI, and the cloud will require robust security measures and compliance with industry, state, and federal regulations. Additionally, ensuring AI-driven products are fair, transparent, and free from harmful biases will require ongoing vigilance and mitigation strategies.

“In the face of these challenges, it will be more important than ever to engage with those with deep technology expertise and know-how. However, finding and retaining professionals with the right mix of AI, data science, and product engineering skills will continue to be a challenge in itself.

“In 2025, we will see an increased focus on upskilling and outsourcing in an attempt to keep pace with the rapidly evolving technology landscape. Internal teams will become keepers of industry and company expertise, engaging with external resources that can help them choose and leverage the right emerging technologies while also bringing outside thinking and experience to problem-solving.”

Pieter Danhieux, co-founder and CEO of Secure Code Warrior

Rewriting the AI Equation: Not AI Instead of Developer, but AI + Developer

“As companies are prompted to take drastic cost-cutting measures in 2025, it would be to no one’s surprise that developers are replaced with AI tooling. But as was the situation when Generative AI first made its debut, and now, with years of updates and more to come, it is still not a safe, autonomous productivity driver, especially when creating code. AI is a highly disruptive technology with many amazing applications and use cases, but it is not a sufficient replacement for skilled human developers. I agree with Forrester’s prediction that this shift towards AI/human replacement in 2025 is likely to fail, especially in the long term. I think the combination of AI + developer is more likely to achieve this than AI alone.”

Bulent Cinarkaya, GM of Field Service Management at ServiceNow

“Over the past year and a half, field service organizations have been running a lot of GenAI pilot programs. Now, they’re working out whether to build solutions in-house, buy off-the-shelf options, or go with a mix of both. Next year, we’ll likely see a big increase in GenAI rollouts, with the technology expanding beyond just text-based tools. We’re talking about smarter, multi-turn conversations and new image and video intelligence features that can handle more advanced tasks. These developments will help companies operate more efficiently and open up fresh ways to improve service and engage customers.”

Dorit Levy-Zilbershot, VP of AI and Innovation at ServiceNow

“Over the next year, we will witness the evolution of enterprise AI agents as they become increasingly sophisticated in their reasoning and comprehension capabilities. Emerging use cases will transform the way businesses leverage these agents, and the nature of human interaction with them will evolve as they take on more complex tasks and decision-making roles. Watch for the rise of AI-powered ‘supervisors’ that will have the ability to move past simply automating tasks to truly orchestrating the interaction of all AI agents throughout an entire organization. This will make it exponentially easier for humans to administrate teams of AI agents across their entire business.

“By the end of 2025, AI agents will cross the chasm from tools that require more hands-on supervision to fully autonomous systems. Expect to see AI agents independently automating complex, multi-step processes without a human in the loop. This will undoubtedly transform how executives view AI adoption, positioning it as a powerful engine for unprecedented growth and innovation.”

Heather Jerrehian, VP of Product Management – Employee Workflows at ServiceNow

“To build an AI-capable workforce, organizations need visibility into the day-to-day tasks people perform and a plan for how to free up that time for more impactful work. Task intelligence will be the new frontier in 2025, enabling AI-driven automation and workforce agility so leaders can make informed decisions about upskilling, reskilling, and redeploying talent.

“In 2025, organizations will embrace autonomous agents, pairing humans and AI agents to streamline operations while cultivating new skill pathways for the workforce. This enables humans and machines to co-create the future of work—harnessing what each does best in a seamless partnership.”

Terence Chesire, VP of Product Management – Customer and Industry Workflows at ServiceNow

“In customer service, the ongoing transition from on-premise to the cloud for contact center will continue to accelerate–driven by the need to adopt AI quickly. This may come as a surprise to many. While most other software stacks have already moved to the cloud, the contact center has remained on-prem. The implication of this shift is a greater need to integrate cloud contact center systems with cloud-based CRM to both orchestrate interactions and the work that needs to happen during and after the call.”

Mark Mader, President and CEO at Smartsheet

Generative AI (GenAI) is ushering in a renaissance age for the generalist.

“Organizations have spent a disproportionate amount of capital hiring hyper-specialized talent with deep technical knowledge for years. Now, with the democratization of GenAI, the value offered by hiring ‘capable generalists’ is on the rise. People who articulately frame their thoughts, pose well-formed questions (prompts), and exercise AI tools to their advantage stand to benefit greatly.

“The demand for specialized AI talent—model developers, AI ops talent, and engineers to build and maintain infrastructure—will persist in 2025. However, we will also see the demand for non-technical talent shift to a more balanced state. Organizations will place as much worth on employees with the skills to extract value from platforms as those who build them.”

Future of Work 

“Over the past year, many of us have started experimenting with GenAI to work smarter and faster, raising questions about how this new technology will impact knowledge workers’ roles. In the coming year, organizations will apply GenAI to reduce and even replace repetitive tasks. This will allow knowledge workers to shift their focus, freeing their time to work on the aspects of their roles that are more strategic and creative. As a result, we’ll start to see more innovation. Businesses will also be expected to move faster and deliver more for their customers. Those who adopt GenAI now will have a competitive edge as these expectations shift.”

In 2025, AI will start to become part of the everyday fabric of our work.

“This year, an unbelievable amount of software came online that enables people to take advantage of AI in the context of their daily work. In 2025, AI will become part of the everyday fabric of work. Adoption will increase dramatically. More people will experience AI within the software they currently use. This removes the friction of switching to another app and staring at a blank prompt window. People will know where to start, and when they see results generated, they’ll usually have a better sense of whether the result is accurate.”

Greg Benson, Professor of Computer Science at the University of San Francisco and Chief Scientist at SnapLogic

Agents will Flourish with Human Oversight

“Agents have the potential to automate the grunt work of many human activities in the enterprise. However, the near-term success of Agents will depend on the harmonious interaction between autonomous processing and human approval of critical, consequential decisions. In this way, Agents are an accelerator to human workflows, but the human still has the final say. Future Agent systems will seamlessly incorporate a human in the loop.”

Increased Focus on Copyright and Data Provenance

“As AI-generated content proliferates, questions about copyright infringement and data lineage will intensify. The industry will see a push toward ‘provenance-aware’ AI models that provide transparency about the sources of their training data. Legal and regulatory developments in this area will be closely monitored and could redefine how AI models are trained and deployed.”

Nitin Singhal, VP of Engineering (Data, AI, and Integrations) at SnapLogic

AI Agents Will Empower Data Engineers To Deliver More Value

“In 2025, enterprise AI agents will fundamentally transform workplace operations, not just by automating repetitive tasks but by reimagining the way teams collaborate, innovate, and deliver value. Far beyond assisting humans, AI agents will optimize decision-making, reduce operational overhead, and empower employees to focus on creativity and strategic initiatives. This evolution will redefine roles like data engineers and software developers, transitioning their work from repetitive processes to managing AI systems, shaping data ecosystems, and unlocking new avenues of value.”

The Real Work Behind Building Responsible AI Systems Will Come to Light in 2025

“The adoption of generative AI will necessitate robust data integration and validation technologies. Organizations will prioritize data lineage, cataloging, and context-sensitive processing to reduce risks like hallucinations in AI outputs. Regulatory compliance frameworks around data privacy, security, and transparency will evolve, and we will see brand new AI regulations driven by global attention to responsible AI usage.”

Charles Ruffino, Fellow, Cloud Architecture at SoftIron

IT talent shortage will force radical workforce reimagination.

“The IT talent landscape is about to experience a tectonic shift that makes previous skill shortages look like a gentle tremor. The quantum of offshore talent is contracting faster than a startup’s runway during a funding drought, forcing organizations into a high-stakes game of technological musical chairs. Onshore talent acquisition will become a bloodsport, with compensation packages climbing like hyperscaler stock prices and the true cost of technical expertise revealing itself in brutal economic clarity.

“This talent crunch isn’t just a staffing problem—it’s an existential forcing function for IT infrastructure reimagination. While AI won’t magically replace human expertise overnight, it will accelerate a Darwinian evolution in how technical teams are structured, skills are developed, and complex systems are conceived. Organizations will be compelled to architect more resilient, self-documenting, and intrinsically manageable infrastructure, transforming a potential crisis into a strategic inflection point for technological innovation. The silver lining? Those who adapt fastest will emerge not just surviving but fundamentally redesigning the future of enterprise technology.”

J-M Erlendson, Global Evangelist at Software AG

Shadow AI is here to stay

“Even as companies push towards developing proprietary AI models, shadow AI will remain pervasive. People tend to favor their own way of doing things, so it’s incumbent on business leaders to evolve in how they address unsanctioned AI use. Blanket bans may have the unintended effect of discouraging innovation, while a failure to lay out policies will bring security and compliance risks. The focus from a governance standpoint should be to make sure company tools are the best available options, as well as educate workers about the inherent risks of shadow AI.”

AI-powered predictive analytics will evolve, driving timely decision-making for businesses.

“Right now, AI’s capabilities in predictive analytics are still mediocre, with machine learning falling short of delivering the deep insights businesses need. While AI today mainly identifies trends, significant advancements will begin to emerge in 2025 and beyond. Over the coming years, AI will continue to evolve to provide more accurate, preemptive decision-making support, empowering organizations to act on business practices proactively and in real-time rather than giving counsel based on older context.”

Aurélien Caye, Solution Specialist at Sprinklr

The Rise of AI-Powered Customer Support

“In 2025, traditional chatbot experiences will fall short as customer expectations evolve. Businesses will increasingly adopt autonomous, AI-powered agents capable of delivering more adaptable, responsive, and personalized support. Generative AI, especially through conversational AI copilots, will enhance both customer and agent interactions by enabling faster, more insightful responses that feel human. While this shift opens vast opportunities, it also brings challenges in responsible AI implementation. As organizations scale up AI adoption, they’ll need to establish guardrails, ensure transparency, and focus on regulatory compliance. Ethical considerations and transparency in AI decision-making will be essential to building customer trust.”

Optimizing AI Efficiency and ROI in 2025

“As organizations move beyond the initial generative AI hype, 2025 will see a focus on optimizing AI model efficiency. Companies will prioritize ‘smaller LLMs’ or open-source, in-house models to improve ROI and manage costs effectively. Multi-modal capabilities in AI will gain traction, allowing systems to interpret diverse content formats and provide more comprehensive support. Success will come from blending AI’s capabilities with human input to create meaningful customer experiences, ensuring that AI-driven transformations remain both sustainable and valuable.”

Ryan Tierney, SVP of Product Management at TrueCommerce

“As we move into 2025, many of the challenges supply chain leaders face today are likely to persist. While the obstacles themselves might not change dramatically, we can expect businesses to sharpen their focus in key areas, particularly around automation. Streamlining supply chain processes will continue to be a priority as companies look for ways to operate faster, more efficiently, and with fewer resources. Another area that will remain critical is data analytics. Supply chains are made up of complex, disparate systems, and getting smarter with data will be key to making informed decisions. Leaders will increasingly rely on internal intelligence to drive operational improvements.”

Claus Jepsen, the Chief Product and Technology Officer at Unit4

Out With Generative AI, In With Automation

“In 2025, IT leaders will pull back from applying generative AI to enterprise use cases amid growing data privacy and intellectual property concerns. While generative AI will fail to gain immediate traction, I expect its human-like quality and prevalence in public discourse will warm more enterprises up to the use of automation. Greater understanding and adoption of automation will transform the user experience for enterprise software. We’ll see the era of ‘self-driving ERP, where more intuitive and conversational software enables users to have less and less direct interaction with the user interface.”

Chris Wysopal, the Chief Security Evangelist and Founder of Veracode

Development and Security Teams Will Redirect Their Secure Coding Training Budget Toward Auto-Remediation

“Developers will learn less about secure coding because they’ll rely more on generative AI to remediate flaws automatically. This progression is analogous to the task of calling someone on the phone. While a few decades ago, we all needed to remember someone’s number to reach them, today, all we need to do is tap a contact on our phone. For developers, the equivalent will be to produce secure code without learning how to code securely from scratch. Instead, they will adopt processes to find, test, and fix vulnerabilities automatically, meaning it won’t be as important to know about secure coding—or even to know if generative AI has learned how to write secure code.”

For consideration in future news round-ups, send your announcements to wjepma@solutionsreview.com.

The post 61 WorkTech Predictions from Industry Experts for 2025 appeared first on Best Marketing Automation Software, Tools, Vendors & Solutions.

Samantha Miller, the GM and Senior Vice President at IDC, outlines the power that accurate data can have in a company’s sales planning efforts. This article originally appeared in Insight Jam, an enterprise IT community that enables human conversation on AI.

In today’s highly competitive tech market, sales and revenue operation leaders face increasing pressure to optimize their strategies for maximum efficiency and revenue generation. A key component of this role is ensuring that their sales planning and account segmentation are powered by accurate data. At the highest level, sales and operations leaders face challenges accessing reliable market intelligence and lack data-driven solutions to address these issues.  

The Challenge of Disparate Data Sources 

Enterprise sales teams are often faced with making agile decisions based on unreliable market intelligence from disparate sources of internal and external accounts and market data. They often fall victim to the “swivel chair effect,” where teams constantly switch between multiple data sources and then manually transfer between processes. This leads to inefficiencies and an incomplete—or incorrect—view of the opportunities that could have led to significant revenue wins. The traditional approach of manually collecting and consolidating data is time-consuming, error-prone, and can delay decision-making.  

The Power of Data-Driven Sales Planning 

Access to any run-of-the-mill data is no longer sufficient. Sales and operation leaders must leverage accurate and up-to-date information to gain a competitive advantage through advanced sales planning and targeting. To overcome this challenge, sales teams need access to a single source of truth and relevant data and insights.  

First, to approach sales and account planning faster and more effectively, sales leaders need trusted data and insights at the core of their analysis, planning, and strategy development. “Garbage in, garbage out” applies now more than ever, especially in a world of AI. As mentioned, a lot of data used in the sales planning process comes from disparate sources, which means that not everything ticks and ties together. How did this data source define a segment vs. that one? Do the geography definitions line up? What is included in the revenue projection? Often, these don’t line up, and that means sales leaders fill in those gaps with assumptions that may not be accurate. 

Second, they need fast, insight-driven workflows to accelerate growth planning. The speed with which sales leaders can move is directly linked to how fast strategic sales analysis and insight gathering occur, and today’s competitive environment demands that it happen faster. We know that sales professionals live in CRM and are surrounded by other sales tools. It’s imperative to integrate and build upon the workflow of these existing tools to provide an experience that supports their workflow.  

Lastly, sales leaders need the ability to adapt their plans and strategies iteratively, which often means being able to go back to the analysis phase to adjust the data. This will reduce the long wait during the analysis phase and allow them to edit their plans instead of starting over with each revision. True data-driven sales planning leads to enhanced decision-making, improved forecasting, optimized account segmentation, and accelerated sales cycles.  

Future Directions 

As technology continues to evolve, so too will the tools available to sales and operations leaders, especially AI. The feedback from early research showed that 95 percent of the Revenue & Sales leaders surveyed were interested in learning more about creating prospect lists faster and tips on finding and validating adjacent markets to expand their revenue opportunities. AI can be leveraged to collect, analyze, and prioritize accurate data quicker and easier than ever, extracting meaningful insights that power meaningful conversations, allowing sales leaders to improve forecasting accuracy and competitive comparisons, validate adjacent markets, and increase confidence around target accounts.  

Sales leaders who understand and capitalize on this next era of technology will create and benefit from a long-standing competitive advantage. These teams will reduce the often-heavy administrative burden of dealing with disparate and broken data sets. They will also enjoy a higher level of productivity and drive account growth. 

But perhaps most of all, organizations that offer this unified approach to accelerate growth will have a leg up due to providing sales and revenue operation teams with actionable content to discover new opportunities and prioritize key accounts. The importance of this cannot be overstated. Growth efficiency has become one of the most important factors for sales teams as they continue to adopt a more strategic role in the company. Accurate, up-to-date centralized data is the key to advancing the next generation of sales teams, and smart organizations will want to pay attention to this emerging opportunity.  

The transition from chaos to clarity in sales planning and account segmentation requires a commitment to data-driven strategies. Sales leaders can embrace their rapidly changing roles by leveraging accurate data, advanced analytics, and emerging technologies like AI while driving efficiency and sustainable growth. As we continue to see this landscape evolve, organizations that embrace data-driven approaches will be well-positioned to succeed.

The post From Chaos to Clarity: The Power of Accurate Data in Sales Planning appeared first on Best Marketing Automation Software, Tools, Vendors & Solutions.

Choosing the right artificial intelligence (AI) solution for your organization is a critical decision that can significantly influence operational efficiency and customer satisfaction. Thousands of AI companies worldwide are marketing hundreds of AI-driven products—each with a different purpose and use case. In this vast sea of AI options, it can often feel like it’s sink or swim to drive actual return from such a huge investment. As tech leaders face mounting pressure to increase profitability, using AI effectively can be the differentiator on which business is gained or lost.

A 2024 Genesys study confirmed this urgency, with more than 50 percent of customer experience (CX) leaders agreeing that adopting AI is the key to improving customer loyalty, boosting financial outcomes, and outpacing the competition in the next five years. 

Today, AI is forging new opportunities for brands to connect with customers. Organizations can offer instant, 24/7 support tailored to each person’s needs and resolve common issues without human intervention. Powered by sophisticated natural language processing, virtual assistants can engage customers in friendly conversational interactions that mimic the familiarity of a real employee. AI-driven analytics enable companies to analyze vast amounts of customer data, uncovering insights into their preferences, behaviors, and pain points. AI copilots that surface knowledge and automate tasks allow human agents to resolve complex and high-value customer inquiries more efficiently and quickly.   

A well-chosen AI solution can scale with the business by supporting growth and adapting to changing needs. However, AI products have stark differences, especially concerning data integrity, privacy, and ethics. To unlock AI’s full potential, tech leaders need a secure, unified platform that’s easy to deploy and allows them to innovate and tailor features for their customers’ needs.  

When investing in AI, here are four essential criteria brands should evaluate to make a strategic and intelligent decision: 

Is it secure?   

According to a Genesys study, 64 percent of CX leaders are concerned that data privacy and security will be their top obstacle when adopting more AI-based solutions. Furthermore, 75 percent worry that trust and privacy issues may prevent their business from making future AI investments. 

Protecting data integrity is paramount to a secure AI solution. Native AI that is purpose-built into a platform speeds up time to value for businesses. It is also a fundamental attribute that helps organizations adhere to strict AI and data ethics requirements, offering the best way to safeguard data and ensure ownership rights are respected. 

When AI services depend on complex, multi-vendor integrations, it’s harder to guarantee customer data security. This could result in data being used without proper consent, unauthorized data access, and potential exploitation of sensitive information. It’s also important to review service agreements thoroughly to ensure data is only used as you expect it to be used. 

In a secure AI solution, training data is carefully vetted. Whether it comes from customers under a data-sharing agreement with consent or another source, this vetting process builds trust, adheres to data privacy regulations, and retains data ownership. All data should be anonymized, stripping away personally identifiable information to safeguard organizational privacy. Human data validation ensures accuracy and reduces the risk of biases and errors that could affect the AI’s performance. Additionally, every AI model should undergo rigorous testing to verify its results. This comprehensive approach prevents data misuse and enhances an AI solution’s quality and trustworthiness. 

Is it compliant?   

Non-compliant AI poses significant risks to businesses. In a non-compliant solution, an organization’s data can exist outside of allowed geographic jurisdictions, which can violate data privacy laws. Companies can face legal repercussions and reputational damage if data operations do not abide by national, local, or global regulations. A responsible AI solution should ensure compliance by obtaining and heeding global and regional compliance regulations and certifications.  

Two new EU regulations that impact AI are making headlines: the Digital Operational Resilience Act (DORA), which will take effect in 2025, and the Artificial Intelligence Act (AI Act), which passed in May 2024. Although they are now limited to companies doing business in the EU, these regulations will likely be a model for future AI regulations worldwide.   

DORA and the AI Act are descendants of similar compliance laws like the General Data Protection Regulation, FedRAMP, and others, which exist to protect fundamental data rights and provide cloud security. Adherence to these regulations demonstrates an organization’s commitment to data security and privacy. These certifications also build customer trust, mitigate risks, and give companies a competitive edge.  

Is it contextual? 

AI that is purpose-built and deeply embedded across an entire platform is integral for addressing customer and employee needs. Working in unison, an end-to-end architecture of conversational, predictive, and generative AI capabilities allows it to continuously learn for smarter outcomes, better results, and clearer context. With this type of iterative learning process, an AI’s responses are highly informed and aligned with specific actions being performed at any moment to provide the most personalized and empathetic outcome. 

Driven by AI, contextual experiences show consumers that their wants and needs matter to a business. This means virtual and human agents already know a customer’s name and information regardless of their contact method. Companies can anticipate customers’ needs, understand their preferences, and resolve issues effectively at the first point of contact and on the channel of a customer’s choice.  

AI without context and journey awareness creates frustration and disconnected experiences and erodes operational efficiency. When disparate AI solutions are leveraged to solve multiple needs, broken customer journeys will follow. This ultimately results in unsatisfactory experiences where historical information about the customer is not carried forward, and customer intent and preferences are not understood. Lack of context further extends to the employee experience, forcing agents to spend additional time and effort to respond accurately and appropriately. 

Is it effortless? 

AI that allows organizations to achieve impactful results is deployed effortlessly and guides customers through building, implementing, and optimizing it out of the box. Customers can also be self-sufficient, minimizing IT involvement in day-to-day maintenance and support. 

Effortless AI solutions are turnkey and ready to use from day one. A single, unified platform with built-in AI does not require skilled resources or data scientists and is more accessible to organizations of all sizes and with technical proficiencies. Companies can quickly reap the rewards of their AI investment without the prolonged wait typically associated with complex integrations, enabling faster time to value. 

Harnessing the Power of Your AI solutions 

Not all AI is created equal, and tech leaders must be vigilant when selecting an AI solution. When chosen correctly, AI products can transform your business into a digital powerhouse by elevating employee effectiveness and customer satisfaction. By focusing on these essential criteria, organizations everywhere can harness AI to drive innovation and consumer loyalty.

The post The Top Questions for Tech Leaders to Ask When Selecting an AI Solution appeared first on Best Marketing Automation Software, Tools, Vendors & Solutions.

Amplitude’s Franciska Dethlefsen offers insights on lessons learned from launching a self-serve plan as a sales-led company. This article originally appeared on Solutions Review’s Insight Jam, an enterprise IT community enabling the human conversation on AI.

In recent years, more companies have implemented product-led growth (PLG) strategies. And it’s no surprise: PLG and self-serve offerings can lower customer acquisition costs, reduce sales spend, and match the market trends giving end users the ability to try something before they buy it. Now, self-serve isn’t for every company, but for those who are looking to build out this go-to-market motion, there are a few things to keep in mind.

Launching a self-service plan can be tricky, especially for traditionally sales-led companies. It is resource-intensive, can cause internal friction, and, to be completely honest, often fails. Amplitude’s self-service offering, Amplitude Plus, took years of trial and error. Not to mention the countless hours it took to build the business case and secure internal buy-in from executives. Here are a few things we learned from launching a self-serve offering – and what you should consider before launching one, too.

Invest in Testing and Set Expectations Early

When launching a self-service offering, you must set proper internal expectations from the beginning. Don’t run any experiments without setting goals and communicating them to your team. And to get anywhere, you’ll need to get buy-in and alignment from company leadership, which requires explaining the why behind your self-serve plan, not just the what. When launching Amplitude’s PLG strategy, we took a risk. Without enough built-in monetization awareness of the product, we set the clear expectation that the experiment wouldn’t hit benchmarks, but it would indicate whether or not we were headed in the right direction. This transparency helped leadership feel comfortable enough to move forward with a trial run.

Once you’ve got the approval to start testing, I recommend creating an initial alpha test in a closed environment. This allows your team to determine if the resources, time, and energy it will take to launch it publicly are worth it. This also helps your leadership team see that customers can and will invest in a product. But beware: those initial numbers may not be what you want to see. Our alpha, which launched over a year before our official launch, saw just 14 purchases. Not a number that makes leaders jump out of their seats. However, we learned a lot from this experience and used these learnings to completely overhaul our positioning, pricing, and packaging before launching in October 2023.

A full alpha test can be a big investment. So if you’re not ready for that, try smaller, lower lift tests, such as featuring the self-serve offering on your pricing page on your website to test a self-serve plan, known as a “painted door test.” You could also conduct email testing to a smaller subset of accounts to understand their reactions.

Look Critically at Pricing & Packaging 

Structuring your product’s packaging and pricing across self-serve and sales-led is critical to its overall success. You want to set up everyone to operate where they do best: at the bottom of the market for self-serve offering, and at the top of the market for your sales team. At Amplitude, our sellers offer volume discounts that aren’t available on self-serve once a customer has reached a certain volume threshold. This helps us drive self-serve customers to sales if they might actually be better off on another plan.

Once you’ve established clear playgrounds for product and sales, it’s time to nail the details of pricing. When structuring your pricing tiers, understanding how customers progress through product features is key. Instead of only making specific features available on specific paid plans, the customer journey should dictate when features are unlocked. For example, all Amplitude users can create a cohort analysis for free, but only those on a paid plan can save or sync it. A progressive method of unlocking features allows for a more natural movement between plans that aligns with the customer journey. Customers on a given plan can experience certain features, and then if they’d like to explore a feature more, they can unlock additional functionality within a paid plan. The bottom line is that new value should be unlocked within each tier, and the best way to do that is to expose that value on the previous tier.

Get Ready to Become a Churn Expert

Launching a self-serve plan is truly a company-wide effort. This kind of change touches everyone from marketing and sales to engineering and product – and everyone in between. Unlike in traditional, sales-led organizations, growth marketing and product teams are now responsible for reducing churn. To be effective, teams need to understand why customers churn, including identifying certain customer benchmarks and being able to define where each customer stands. Marketing and product teams’ understanding of business metrics like revenue and churn is fundamental to the long-term success of the self-service plan. Getting ahead of churn requires company-wide support and proper staffing, including defining team roles.

Mastering a self-service product strategy comes with challenges and considerations, but the potential for monetization and increased customer satisfaction is significant. However, the most important and basic consideration of all is ensuring your product is actually ready for self-serve. Make sure you have healthy adoption and retention rates – and if you don’t, invest there first. Naturally, it can be overwhelming to begin this journey. Introducing a self-serve model when your company has historically been sales-led can be difficult, but embrace it with a growth mindset – find experts internally or externally, conduct research, and most importantly, talk to your customers. And keep talking to them – you learn something new every single time.

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Chris Todd, a Principal of Marketing Operations at CallTrackingMetrics, provides a one-year retrospective on the Google Analytics 4 (GA4) launch and shares his insights on how it’s changed marketing strategies. This article originally appeared in Insight Jam, an enterprise IT community that enables human conversation on AI.

On July 1, 2023, a significant shift occurred in the world of website analytics. Google sunsetted its long-standing platform, Universal Analytics (UA), and debuted its next-generation platform, Google Analytics 4 (GA4), with advanced capabilities and a focus on user privacy. Though Google had been promoting GA4 for some time, the official sunsetting of UA spurred businesses to accelerate their migration to the new platform. But this wasn’t just a platform update but a fundamental change in how website user data is collected and analyzed.

After a year of using GA4, marketers have gained valuable insights into its enhanced data-tracking capabilities, user-centric approach, and the challenges involved in transitioning platforms. GA4 allows marketers to understand their audience better, optimize campaigns for improved results, and stay ahead of the competition.

The Big Picture: Overall GA4 Takeaways

One of the most notable improvements resulting from the shift from UA to GA4 has been flexibility: charts are customizable, events can include significantly more parameters, and it’s easier to build visuals and analyze complex segments. This increased flexibility is not without its challenges, however. The myriad customizations available require a more thoughtful measurement strategy than was necessary with UA.

Though many of GA4’s insights are similar to those from UA, such as which pages are doing well and which sources drive the most traffic, marketers can dig deeper with GA4. Its event structure allows marketers to analyze a segment’s site behavior more closely, resulting in more thorough insights to inform campaigns.

GA4 is still a work in progress as Google adds improvements and updates, so marketers cannot “set it and forget it.” Some metrics aren’t yet available in reports, but they are available through Explorations. Though it may require setting aside some designated time to become better acquainted with the platform, marketers can get creative by learning how their audience interacts with their campaigns and websites.

The Nitty-Gritty: GA4’s Platform Improvements

Google designed GA4 to be the analytics software of the future by focusing on two key areas significantly limited in UA: machine learning (ML) and data visualization. Benefits of these new capabilities include:

• Improved predictive analytics. Since GA4 can predict future user behavior based on historical data and trends, businesses can better anticipate customer needs and personalize experiences proactively.
• Deeper insights. ML algorithms can analyze vast amounts of data to uncover hidden patterns and user journeys that traditional methods might miss. These insights empower businesses to make data-driven decisions and optimize their marketing strategies.
• Enhanced data visualization. GA4 offers richer data visualizations, making complex data sets easier to understand and allowing marketers to identify trends and patterns in user behavior.
• Streamlined data tracking. GA4 simplifies data tracking by replacing UA’s multiple disparate data views with a single data stream for all related properties. This provides a more holistic picture of visitor behavior across different touchpoints,  including mobile devices, desktops, and apps.

Users switch between devices throughout their customer journey. GA4’s ability to track user behavior across these touchpoints offers a complete picture of a visitor’s online presence, allowing businesses to tailor their marketing strategies to address the specific needs of users at each stage of the journey.

However, the migration from UA to GA4 did have some hiccups. For example, comparing UA user metrics to GA4 user metrics created an “apples-to-oranges” situation; GA4’s primary metric is “active users,” measuring the number of distinct website or app visitors, while UA tracked total users. Since the calculations for these measurements differed, the comparisons were rife with discrepancies.

GA4’s Solutions to Legacy Issues and Privacy Concerns

The limitations of UA’s decade-old architecture presented challenges for scalability and adherence to evolving data privacy regulations like GDPR and CCPA. This spurred Google to encourage user migration to GA4, which offers several privacy-centric features:

• Default IP anonymization. GA4 anonymizes user IP addresses by default, enhancing user privacy.
• Shorter data storage. Data is stored for a shorter duration in GA4, minimizing the amount of user data retained.
• Enhanced data controls. GA4 gives users more control over their data, such as requesting deletion of personal information.
• Consent mode. GA4 operates in a consent mode, ensuring user data is collected only after obtaining explicit consent where required.

By prioritizing user control and anonymization, GA4 ensures compliance with evolving regulations while fostering trust with website visitors. This commitment to user privacy positions GA4 as a future-proof analytics platform that empowers businesses to gather valuable insights without compromising user trust. As data privacy continues to be a top priority, GA4’s focus on user control positions it as a worthwhile tool for businesses wanting to stay compliant and ethical in their data collection practices.

GA4 represents a paradigm shift in website analytics. By leveraging ML, advanced data visualization, and a focus on user privacy, GA4 empowers businesses to gain a deeper understanding of their audience, optimize user experiences, and stay ahead of the curve.

The post GA4 One Year Later: A Marketer’s Insights and Learnings appeared first on Best Marketing Automation Software, Tools, Vendors & Solutions.