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Fully 91% of B2B marketers are already using AI for account-based GTM, so we’re well past the point of AI adoption being hypothetical. Even so, there’s great variance in how it’s being used and where it’s headed.
Because so much is in flux and the potential grows more vast every day, the next frontier holds both uncertainty and promise, which is why Demandbase and ForgeX launched their recent AI+ABM Inflection Point report.
The research found that ultimately, getting the most from the technology is not just about more tools but also about smarter orchestration, stronger integration, and preparation for the rise of agentic AI.
Here’s a deeper look.
The Present: AI as a Task Assistant
In B2B organizations today, AI is largely being used as an executor, helping with tasks like copywriting (68%) and research (47%). It’s not surprising that those are two of the biggest use cases: They’re easy to implement, they’re powered by readily available large language models, and they cause minimal disruption to existing workflows.
If anything, such tools expedite task completion and improve productivity. They thrive because they fit cleanly into an organization’s daily processes and leverage user-friendly tools like ChatGPT.
Although adoption today favors immediacy and familiarity over transformation, as in those examples, there are some signs of increasing sophistication.
For instance, 46% of B2B marketers are using AI to help with predictive analytics (account selection and prioritization), which is much more than a basic use case.
The Plateau: Why More Ambitious Use Cases Are Lagging
Although the application of AI in predictive analytics is a sign of progressively growing comfort with the technology, B2B marketers still have a long way to go.
Most organizations aren’t ready to weave advanced AI use cases into their organization’s ongoing GTM efforts, unsure how to prepare for optimization, measurement, or next-best-action recommendations.
Although barriers to action vary from one company to the next, there are some commonalities among B2B marketers.
The top factors holding teams back from incorporating more ambitious use cases are a lack of internal AI expertise, inadequate training, and integration challenges. It’s worth noting that two of those three deal directly with a workforce that may be willing—but ill-equipped—to do more than use AI as a task assistant.
The integration of AI into GTM efforts isn’t merely tool-centric; it’s every bit as much process-centric, training-centric, and team-centric. Mindsets toward the tech matter, including a foundational trust in AI, transparency into the data and agentic decision-reasoning, and full visibility into the technological infrastructure that’s powering it.
Without organizational readiness, especially around data systems and team coordination, AI will remain underutilized, isolated, and unable to scale or connect meaningfully to an organization’s ABM strategy.
The Future: Personalization, Asset Creation, and Agentic AI
As B2B marketers continue to test the waters with various AI applications in their GTM, and leaders hopefully offer more opportunities for training, use cases will expand.
In the next six to 12 months, it’s reasonable to assume that copywriting and research will remain high on the list of AI-initiated tasks. Asset creation and personalization will likely be hot on their heels, becoming part of the Top 3 before too long.
In the longer term, the industry will embrace agentic AI more and more. These systems that act independently, synthesize data, and make decisions take the foundational technology from assistance to orchestration. Instead of simply fulfilling tasks it’s been programmed to fulfill, agentic AI can handle initiatives like dynamic campaign orchestration, tailored content generation, deal-stage recommendations, and beyond.
Why Agentic AI Matters for ABM
What’s exciting about agentic AI is that it naturally aligns with core account-based principles. ABM centers on personalization at scale, timely signal-driven responses, and close sales and marketing alignment, all of which agentic AI can strengthen.
The technology won’t just support these strategies; it could actually coordinate entire GTM motions—from interpreting buyer signals to optimizing campaign flows, adjusting touchpoints in real-time, and beyond.
Early adopters are likely to gain outsized advantages in deal velocity and pipeline impact.
Steps Marketers Can Take Now
Whether you’re a B2B marketing practitioner or leader, there’s a lot you can do to maximize the AI you’re already using and to progress toward more advanced use cases that will further your goals.
To start, invest in foundational capabilities if you haven’t yet. Teams should have access to ample training and become fluent in working with AI; otherwise, additional adoption and sophistication will never be achieved.
It’s also critical that your organization be ready for strong data integration and governance, and that cross-functional collaboration, especially with sales and IT, be part of the process from the beginning. Your collective mindset should move from isolated efficiency wins to systemwide orchestration goals. After all, AI’s value is greatest when connected across tech, teams, and tactics.
The same is true for trustworthy data that is connected; if you don’t have visibility into the entire GTM’s data, you are missing part of the picture and making misinformed decisions. The agents will do the same if the data is not connected.
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AI is already reshaping ABM, but we’re still early in the journey. B2B marketers who treat it as a strategic capability, not just a tactical helper, will be best positioned for what’s next.
The future of AI and ABM isn’t just smarter content; it’s smarter coordination.
More Resources on AI use in ABM
How AI Is Impacting Account-Based GTM Programs [research]
How to Use Generative AI for Personalized B2B Outreach
