Key Takeaways:
- B2B CMOs must create structured, evidence-based content that serves both human buyers and AI agents involved in vendor research and recommendations.
- Marketing leaders should redesign workflows around AI-human collaboration, with people owning strategy, ethics, brand voice, privacy and customer trust.
Artificial intelligence (AI) is no longer just a back-end productivity tool in B2B marketing. It is becoming an active participant in how buyers research, evaluate and narrow their options. That shift is forcing marketing leaders to rethink how they build messaging, structure content and create experiences that can satisfy both human decision-makers and the AI systems increasingly shaping their choices.
As AI takes on a greater role in filtering information, surfacing recommendations and accelerating execution, the stakes for marketers are rising. Content must be clearer, more credible and more context-rich, while strategy must protect what machines cannot replicate: trust, relevance, empathy and sound judgment. For B2B organizations, the challenge is not simply to move faster with AI, but to use it in ways that strengthen customer relationships and improve marketing effectiveness.
In this Q&A, Tom Kaneshige, Chief Content Officer at the CMO Council, explores what that new reality means for modern B2B marketers. He discusses how teams should adapt AI-ready messaging and content strategy, how they can redesign workflows for stronger AI-human collaboration, and why human oversight remains essential in areas such as brand voice, privacy, bias and customer trust.
Demand Gen Report (DGR): How should B2B CMOs evolve messaging, content strategy and buyer engagement as AI agents become active participants in buying groups?
Tom Kaneshige: B2B messaging has to be built for two audiences now. That’s because the buying team has a new member, an AI agent that filters and recommends. B2B marketers have to make sure content is more structured, more evidence-based and context-rich. Thought leadership fluff and vague value props won’t survive the agent gatekeeper.
But if marketers get it right, AI will reward them. The world is a noisy place. Human buyers need an AI agent to cut through this noise and give them confidence when making complex, expensive decisions. The winning play is content that satisfies the machine’s need for clarity and the human’s need for trust.
DGR: What strategic changes should B2B CMOs make to ensure AI strengthens human judgment rather than becoming just a faster productivity tool?
Kaneshige: Stop treating AI like a content factory. That’s the fastest way to scale sameness. The real advantage comes when AI and humans are integrated into redesigned workflows, not when AI is bolted onto old processes.
That dynamic surfaced repeatedly in the new CMO Council and WongDoody report, Marketing’s Power Partners: AI and the Human Essence. In our report, nearly 70% of high-performing organizations say they are prepared to redesign workflows around AI-human collaboration, compared to just 7% of less integrated organizations.
Adjusting to the AI Era
DGR: What human oversight should B2B CMOs treat as non-negotiable?
Kaneshige: Human oversight cannot be an approval checkbox at the end of the process. It has to be built into the workflow. CMOs should treat ethical data use, privacy, bias checks, brand voice and cultural context as non-negotiable human marketer responsibilities.
AI can optimize for engagement, but it does not understand the cost of getting trust wrong. It cannot feel when personalization becomes invasive. It cannot know when a message is emotionally tone-deaf. It’s not held accountable. Human marketers must protect the customer relationship.
DGR: What are the most common barriers to stronger AI-human partnerships?
Kaneshige: AI-data readiness matters but the deeper barrier is human in the form of fear, uncertainty and unclear roles. Marketers wonder whether AI is there to help them or replace them. Given the layoff headlines, that concern isn’t fiction.
Senior leaders overcome this by proving value, not preaching adoption. Build internal AI champions. Show real use cases. Define human-versus-AI responsibilities. Train teams continuously. Most important, make it clear that human judgment is not being written out of the operating model. It’s actually becoming more valuable.
DGR: How should B2B CMOs redesign workflows so AI drives speed and scale while people remain accountable for empathy, nuance and judgment?
Kaneshige: Start by mapping how work actually gets done, not how the org chart pretends it gets done. Then redesign workflows around the strengths of each partner. AI should handle volume, pattern detection, optimization and repetitive execution. Humans should handle strategy, relevance, emotional resonance, ethics and final judgment.
Our report shows high-performing organizations are far more prepared to redesign workflows for AI-human collaboration. That’s the difference. The winners are not sprinkling AI over broken processes. They are rebuilding the process so AI and humans work together by design.
Here’s another relevant report finding: 94% of high-performing marketing organizations have defined collaborative processes for AI-assisted content creation, compared to just 42% of less integrated ones.
The Key Metrics to Concentrate On
DGR: What separates companies that turn AI-human collaboration into personalization at scale from those that struggle?
Kaneshige: Personalization at scale does not happen because a company buys an AI tool. It happens when customer data is clean, accessible and actionable, and when humans define what “good personalization” actually means.
The laggards confuse automation with relevance. They flood customers with more messages at a faster rate without solving the judgment problem underneath it. That’s how personalization becomes noise. Humans decide whether it feels useful, creepy, generic or genuinely valuable.
Our report has a section covering personalization specifically. Among high-performing organizations, 60% report major gains in personalization compared to just 10% of less integrated organizations.
DGR: Which metrics should B2B CMOs prioritize to tell whether AI is improving marketing effectiveness?
Kaneshige: Output metrics are not enough. More content, more tests and faster campaign launches are all well and good, but they don’t prove effectiveness. The real question is not “Did AI make us faster?” It’s “Did AI make us better?” If AI increases activity but does not improve revenue impact or customer lifetime value, then you’re just spinning your wheels.
DGR: How does AI change A/B testing and experimentation in enterprise marketing?
Kaneshige: AI lowers the cost of experimentation while quickening the pace. Testing no longer has to be limited or episodic. That said, CMOs need discipline. More testing does not necessarily mean better learning. Human marketers still need to define the hypothesis, interpret the results and decide what is strategically meaningful.
Another way to put this: AI can tell you what performs, but humans have to decide what matters.
What CMO’s Should be Focused Looking Forward
DGR: If a B2B CMO can invest in only one or two AI-driven changes next year, where should they start?
Kaneshige: Start with AI-ready data and workflow redesign. Boring? Maybe. Essential? Absolutely. Without trusted data, AI is just guessing at scale. Without redesigned workflows, AI gets trapped in legacy processes and creates faster dysfunction.
The companies seeing measurable gains are not necessarily spending more. They are building stronger operational foundations. Our research found organizations with stronger AI-human integration are nearly three times more likely to report measurable ROI from AI initiatives. Yeah, you might want to read that again. I just buried the lede.
DGR: What capabilities will set the next generation of B2B market leaders apart?
Kaneshige: Our report underscores how the next generation of B2B marketing leaders will be defined by AI-human orchestration. As AI takes over more execution, the human marketing skills rising in value are strategic thinking, performance measurement, AI expertise, data storytelling and emotional intelligence.
In practical terms, the laggards will use AI to crank out more content and automate more tasks. The leaders will use AI to make smarter decisions, move faster and deepen customer relevance. That’s the real divide emerging in marketing. AI scales execution. Human marketers create the advantage.
