B2B CMOs are entering a new phase of AI adoption. The first wave centered on experimentation: content generation, translation, summarization, image creation and productivity gains. Those use cases matter, but they are not enough to carry marketing through the next stage of AI-driven change.
The opportunity, and the risk, is much larger. AI is reshaping how buyers discover providers, how go-to-market teams coordinate, how content is created and delivered, how value is communicated, and how pricing and packaging are evaluated. AI is no longer just a tool inside marketing. It is becoming a force that changes the market around marketing.
To keep pace, B2B CMOs must address 10 key elements: functional processes, pipeline generation, GTM alignment, martech, data, resources and skills, relationships, awareness, brand, and pricing and packaging.
Don’t Confuse AI Activity With AI Impact
Many marketing teams are already using AI, but usage does not equal transformation. In many organizations, AI adoption remains concentrated in content and creative applications. These are useful starting points, but they can also create a false sense of progress.
If AI is used only to make existing activities faster, CMOs may achieve efficiency but miss the larger growth opportunity. The mandate is not simply to produce more content or execute campaigns more quickly. It is to rethink how marketing creates value across the customer journey.
This requires CMOs to evaluate AI use cases across two dimensions: efficiency and growth. Some applications defend the business by improving productivity or reducing manual effort. Others extend existing capabilities by improving segmentation, personalization, campaign execution or pipeline conversion. The most transformative applications create new ways to engage buyers, deliver value and scale go-to-market execution.
Start With Outcomes, Not Tools
The temptation in any AI conversation is to start with technology. Which model? Which platform? Which agent? Which vendor?
CMOs should resist that instinct. The better approach is “right-to-left” thinking: begin with the business outcome, then identify the process implications, required resources, data dependencies, governance needs and technology options.
Campaign planning and execution offer a clear example. A traditional email campaign may rely on static segmentation, manual content production, limited personalization and disconnected analysis. An AI-enabled workflow can aggregate signals in real time, identify high-intent segments, insert content based on persona and context, personalize offers, and monitor performance as the campaign runs.
The value is not just time saved. The bigger value is new action: identifying target cohorts, detecting intent signals and improving the path from engagement to opportunity.
Rebuild GTM Alignment Around the Buyer Journey
AI will expose weak go-to-market alignment. If product marketing, demand generation and sales operate in silos, AI will not solve the problem. It may accelerate the dysfunction.
B2B CMOs should use the buyer journey as the organizing framework for AI-enabled orchestration. Across awareness, consideration, decision, onboarding, renewal and expansion, marketing and sales teams need shared visibility into segments, personas, messaging, competitive intelligence, content, signals, product-qualified leads, value realization and expansion opportunities.
AI agents can eventually support much of this work: determining best-fit segments, identifying use cases, generating buyer enablement content, creating business-case materials, scoring leads, recommending next-best actions and delivering content through the right channels. But agents will only create value if the underlying GTM process is aligned.
AI readiness is not just a technology issue. It is a relationship issue.
Fix the Readiness Gap before Scaling Agents
Marketing leaders are enthusiastic about AI agents, but many organizations are not ready to deploy them at scale. That should not stop experimentation, but it should shape it.
CMOs need to assess readiness across data availability, quality, accessibility, use cases, cost and budget. They also need to rethink resources and skills. AI creates demand for people who can define outcomes, set parameters, manage agents, integrate platforms, govern models and lead change management.
Just as important, CMOs should revisit their martech stacks before deciding to build new AI applications from scratch. Many existing SaaS tools are already being AI-infused or rearchitected for specific marketing use cases. At the same time, AI-native platforms can offer capabilities that traditional products may not. The key is to understand where each approach fits.
The Importance of Human Judgment
In general, CMOs should avoid rebuilding mission-critical core functionality, such as CRM, ABM or marketing automation, in AI-native platforms unless there is a clear business case. Instead, custom or AI-native development may be better suited to white space opportunities, such as buyer persona generation, hyper-contextual content, advanced value proposition development or new forms of buyer insight.
When comparing proprietary tools with LLM-based or AI-native builds, marketing leaders need to look beyond capability and conduct a business case analysis. The question is not only whether AI can perform the work, but whether it can do so at the right cost, quality, scale and level of operational risk. Sometimes an AI-native build may unlock differentiated value. Other times, an existing marketing work management, CRM, ABM or automation platform may deliver similar outcomes with lower complexity.
AI will not replace the need for human judgment. It will increase the need for people who can design, manage and improve AI-enabled workflows, while making disciplined choices about when to build, when to buy and when to optimize what is already in place.
Prepare for AI-Influenced Buyers
The change is not only happening inside marketing organizations. It is also happening in the buying journey.
B2B buyers are increasingly open to using generative AI to gather supplier information, compare product or service specifications, and identify or confirm business needs. That means the buyer journey is becoming more self-sufficient, anonymous, conversational and fragmented across buying team members.
This changes content strategy. B2B marketers can no longer optimize only for clicks and linear nurture paths. They need to plan for discoverability and authority in AI-shaped environments by mapping personas and jobs to be done, developing structured semantic content, and amplifying content in AI-optimized formats.
The CMO Action Plan
To navigate this next phase of AI, B2B CMOs should take three actions.
- First, assess AI readiness. Map tasks, activities and workflows to the right mix of human and agentic resources. Determine whether data is available, high quality and accessible.
- Second, prioritize AI by value. Seek and measure both efficiency and growth impact. Think right to left: outcomes first, then challenges, then resources and technology.
- Third, protect brand trust. Govern internally and externally generated content, maintain consistency in messaging and pricing, and ensure AI-enabled experiences strengthen rather than dilute the brand.
The CMOs who win will not be the ones with the most AI pilots. They will be the ones who redesign marketing to create measurable value in an AI-shaped market.
David Yockelson is a Distinguished VP Analyst in the Gartner Marketing practice, specializing in go-to-market strategies for technology providers, including product marketing, marketing and sales alignment, value management, AI applications in marketing and demand generation. He presented live on this subject and others at the Gartner Marketing Symposium/Xpo, June 8-10, 2026 in Denver, CO
