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Drew Neisser is the founder of CMO Huddles and a globally recognized authority on B2B marketing. He’s an AdAge columnist, LinkedIn TopVoice, leading CMO coach, podcast host & friend of penguins everywhere.
HumanX is quickly becoming a must-attend AI event for CMOs who need to understand how AI is reshaping marketing, customer experience, brand, security, and go-to-market strategy. Drew Neisser reflects on his experience at HumanX, from asking basic questions about inference to visiting vendor booths, talking with CMOs, attending sessions with leaders including Al Gore and Alex Stamos, and discovering that the biggest CMO opportunity is not chasing AI hype but translating complexity into clarity.
I went to HumanX expecting to come home with a tidy set of AI takeaways for CMOs. Instead, I spent much of the first day realizing I did not fully understand the language being spoken around me, which is both humbling and oddly useful when you make your living helping marketers translate complexity into clarity.
In the opening keynote, AI was described as a five-layer cake. One of the layers was inference. Everyone around me seemed to nod knowingly, while I sat there wondering whether this was something I was already supposed to know. So I did what more marketers probably need to do right now: I found a booth using the word "inference" and asked them to explain it.
There is something powerful about putting yourself in a room where you do not speak the language. It is like traveling to a foreign country where you catch every third word and fill in the rest with context and guesswork. You can either pretend you get it or you can get curious. I chose curiosity.
That, more than any single session, may be the real lesson for CMOs right now. AI is moving too quickly, and the vocabulary is changing too fast, for any marketing leader to fake fluency for long. But the job is not to become an AI engineer. The job is to ask better questions, translate technical possibility into business value, and make sure the brand does not disappear into a sea of sameness.
And at HumanX, there was plenty of sameness. AI-native. AI-driven. AI-powered. AI-everything. Different logos, same language, very little clarity. Then one booth broke through. Sentry's line was simple: "Someone's gotta babysit the bots." Finally, a problem I understood, a point of view I could remember, and a reason to stop.
That moment stuck with me because it captured the marketing challenge hiding inside the AI conversation. The winners will not be the companies that say "AI" the loudest. They will be the companies that make the problem clear, the value concrete, and the buyer a little less confused than they were before.
Before we get to the lessons, let me say this clearly: HumanX is absolutely worth adding to your calendar. For anyone trying to understand where AI is going, especially from a business leadership perspective, it is about as close as I have seen to a one-stop shop for the conversation. The speaker roster, vendor density, investor presence, technical depth, and executive-level energy make it a rare chance to see the AI ecosystem in one place.
The San Francisco edition did not have quite the same spark as the Las Vegas launch, at least to my eye. That may be why I was not surprised to hear HumanX is returning to Las Vegas March 7-10, 2027. If you are a CMO trying to separate AI signal from AI theater, I would strongly consider going. Just bring comfortable shoes, a full phone battery, and a willingness to ask questions that may make you feel briefly underqualified.
I also ran into several Huddlers, including Mark Abramowitz, CMO of Dataiku, and partners including 1mind and Findem. That matters because the best part of a conference like this is rarely just the stage content. It is the hallway conversation, the booth detour, the unexpected peer exchange, and the moment when someone says out loud what you were quietly wondering.
One of the clearest themes from HumanX coverage is that AI itself is no longer a differentiator. Walker Sands put it plainly in its HumanX 2026 recap: The market has moved beyond experimentation, and execution is now what matters. That tracks with what I saw on the floor, where the phrase "AI-powered" appeared so often it started to function less like a value proposition and more like wallpaper.
For buyers, "AI-powered" often creates more questions than answers. What does the product actually do? What workflow does it improve? What business outcome changes? Why should I believe you? In a skeptical market, category language is not enough.
HumanX even had a session called "How to Market Your AI Tools Successfully," which, according to Walker Sands, emphasized that buyers are prioritizing measurable outcomes like cost reduction and revenue impact. That should be a wake-up call for every CMO marketing anything with AI inside it. The question is no longer, "How do we tell the market we use AI?" The better question is, "What pain do we make easier to understand, easier to solve, or easier to act on?"
Sentry's "babysit the bots" line worked because it did not ask me to admire the technology. It named the anxiety. In a market flooded with abstractions, that is a gift.
I visited at least 20 vendor booths, including 1mind, UserGems, Plaud, Optimizely, Storylane, and Sentry. My question was simple: "What should CMOs know about your brand?" Then I listened for whether the answer sounded like a strategy, a demo script, or a pile of category words wearing a lanyard.
This is a worthwhile exercise for any CMO attending a major industry event. You learn which companies can explain themselves at the executive level, which can only list features, and which have a real point of view about the problem they solve. You also learn something slightly uncomfortable: The booth staff are not always as prepared as they need to be for an executive conversation.
That matters because B2B CMOs are spending more on events, and events are too expensive to treat as logo visibility with snacks. If your team is investing six or seven figures into a conference presence, the people working the booth need to do more than scan badges and repeat product copy. They need to know how to diagnose, qualify, provoke, and translate. Otherwise, the brand experience collapses at the exact moment a serious buyer finally stops to talk.
The booth is not just a booth. It is a live test of your positioning.
Another theme that deserves CMO attention is the way AI is changing discovery itself. Walker Sands reported that HumanX conversations focused heavily on generative engines and the shift from keyword search to more complex, natural-language questions. Buyers are not just typing terms into Google and clicking through a linear path. They are asking AI systems to explain categories, compare vendors, summarize reputations, and recommend next steps.
That changes the marketer's job. For years, we have optimized around funnel stages: Awareness, consideration, decision, loyalty. That model still has value, but it is starting to feel too tidy for how buyers actually behave. In an AI-mediated journey, discovery, evaluation, education, and even support can collapse into a single conversational experience.
This came up in a conversation I recorded with a CMO at the event, who described a major shift from selling into a familiar customer experience buyer to engaging AI leaders and technologists. "It's a completely different set of buyers," this CMO told me. That sentence should stop a lot of marketers in their tracks, because a different buyer is not just a campaign adjustment. It is a positioning, content, sales enablement, analyst relations, and board-level expectation challenge.
The implication for CMOs is enormous. It is not enough to rank for keywords. Brands need to be understood by the systems that summarize markets and shape consideration sets. The content strategy question gets bigger. It is not just "Are we findable?" It is "Are we understandable? Are we credible? Are we described accurately when we are not in the room?"
That last question should make every brand leader sit up a little straighter.
There is a tempting but dangerous assumption that AI makes brand less important because it makes content easier to produce. I think the opposite is true. When everyone can generate more content, the scarce asset is not volume. It is coherence. It is knowing what the brand would say, what it would never say, and what it should stop saying even if the machine can produce it efficiently.
Walker Sands' recap of HumanX highlighted comments from AB InBev's Marcel Marcondes on the need for focus, consistency, and brand discipline in an AI-scaled world. That is exactly right. The risk for CMOs is not underproduction. It is brand fragmentation at machine speed.
The anonymous CMO I spoke with was wrestling with exactly this issue: How to move a legacy perception into an AI-forward story without losing the credibility of the company's heritage. That is the brand challenge many enterprise CMOs are facing right now. They need to modernize the narrative quickly, but they also need to bring the CEO, board, sales team, customers, and employees along for the ride.
This is where marketing leaders need to rethink how they define brand governance. Too often, governance is treated as a brake: The thing that slows work down after creative teams have done their part. In the AI era, good governance has to become creative infrastructure. It should help teams move faster because they know the guardrails. It should make the brand easier for humans and machines to apply. It should reduce ambiguity before a thousand off-brand variations enter the world.
Bad governance slows people down. Good governance gives people permission to move.
The more I read the post-event coverage, and the more I think back on the conversations I had, the more one pattern stands out: The most serious AI conversations are no longer about isolated tools. They are about operating models. The Cox Business reflection from Martin Jones is useful here, even allowing for its self-promotional tilt. The core idea is strong: AI transformation is not about giving a few people access to tools. It is about changing how the marketing organization works.
That means workflows, data, approvals, training, measurement, brand standards, agency relationships, field marketing, corporate marketing, sales handoffs, and customer support loops. In other words, all the messy stuff that does not fit neatly into a demo. It is also the work that determines whether AI becomes a durable advantage or just another shiny object that made a big entrance and left quietly through the side door.
GTMnow's HumanX recap made a related point in a different way: Agents do not simply replace people; they replace processes. That is a critical distinction for CMOs. The near-term opportunity is not to imagine a marketing department with no humans. It is to identify the workflows where humans are currently trapped in mechanical effort and redesign those workflows around better judgment, faster learning, and clearer ownership.
The CMO's job, then, becomes less about managing channels and more about orchestration: People, data, agents, brand memory, customer intent, and measurement all working together. That is not a tool rollout. That is a management challenge.
One of the sessions that really caught my attention was "Is AI Eating Security?" featuring Alex Stamos, Chief Product Officer at Corridor. His argument was not subtle, and that was the point. The threat level created by enterprise AI usage is extraordinarily high, and very few businesses are as prepared as they think they are.
CMOs should not treat this as an IT sidebar. Marketers have already played an accidental role in too many enterprise vulnerabilities because of sprawling, insecure martech stacks. We love tools. We love speed. We love experiments. We love signing up for the promising platform that might give the team an edge next quarter.
That impulse now comes with bigger consequences. Every AI tool that touches customer data, campaign data, product data, employee data, or proprietary content needs a security conversation before it becomes part of the workflow. This does not mean marketers should stop experimenting. It means CMOs need a stronger partnership with CISOs, legal teams, procurement, and data leaders before the stack becomes a collection of unsupervised AI endpoints.
Yes, someone has to babysit the bots. But someone also has to secure the crib.
One of the sharper ideas from the GTMnow recap was that execution is becoming less scarce while taste and judgment become more valuable. For marketers, this is both exciting and uncomfortable. AI can already draft, summarize, version, personalize, analyze, and recommend. It will get better at all of that.
But AI does not know what is strategically important unless we teach it. It does not know which customer tension matters most. It does not know when a message is technically accurate but emotionally dead. It does not know when "more content" is the wrong answer.
That is where humans still matter enormously. The marketers who thrive will not be the ones who simply produce more with AI. They will be the ones who know what is worth producing. They will know when to push, when to simplify, when to stop, and when to ask the question everyone else is pretending they already understand.
This is why I keep coming back to that moment on the HumanX floor. Asking "What is inference?" felt mildly embarrassing. But it was also the right move. Confusion, handled honestly, is often the doorway to better thinking. CMOs need to create teams where that kind of curiosity is allowed. Maybe even expected.
For all my emphasis on the floor, the booths, and the hallway conversations, the main-stage content mattered too. I particularly enjoyed the opening night session with former Vice President Al Gore, who remains remarkably articulate and deeply informed on both AI and complex environmental issues. His presence was a reminder that AI is not just a marketing technology conversation, or even a business transformation conversation. It is also a societal, regulatory, ethical, and environmental conversation.
That broader context matters for CMOs. We are often tempted to narrow AI to efficiency, personalization, content velocity, or pipeline impact. Those things matter, of course. But AI is also changing labor expectations, information quality, trust, energy usage, customer privacy, and public discourse. The CMO may not own all of those issues, but the CMO will absolutely have to communicate through them.
That is another reason HumanX is useful. It puts marketing leaders in proximity to conversations they might not otherwise seek out. You may come for GTM insights and leave thinking about power consumption, national competitiveness, cybersecurity, synthetic media, and whether your current brand language can survive a buyer asking an LLM to summarize your category.
HumanX was not really about whether AI matters. That question is settled. The more useful question is whether marketing leaders are willing to stand inside the confusion long enough to make better decisions.
That means learning enough of the technical language to avoid being snowed. It means resisting the urge to slap "AI-powered" onto every message. It means pushing vendors for proof. It means rebuilding workflows instead of decorating old ones with new tools. It means treating brand as a system, not a slogan. And it means remembering that the buyer is probably just as overwhelmed by the language as you are.
The opportunity for CMOs is not to become the smartest AI expert in the room. The opportunity is to become the clearest translator. Because when every company starts to sound the same, clarity becomes a competitive advantage. And when everyone else is nodding along, the leader willing to ask the basic question may be the one who actually learns something useful.
That was my biggest HumanX takeaway. Go where you do not understand the language. Ask the question that makes you feel a little dumb. Listen for the vendor who can explain the problem without hiding behind jargon. And when you see a hundred companies saying the same thing, do not just call it a branding problem.
Call it your opportunity.
Yes. HumanX is one of the most useful AI events for CMOs because it brings together business leaders, technologists, investors, vendors, policy voices, and practitioners in one place. The value is not just in the sessions, but in the combination of main-stage thinking, vendor demos, peer conversations, and exposure to the technical vocabulary shaping the next phase of marketing.
The biggest takeaway is that AI advantage is shifting from tools to operating models. CMOs should think beyond content generation and start redesigning workflows, governance, brand systems, data practices, and measurement around AI-enabled work.
"AI-powered" has become category wallpaper. Buyers now want to know what problem a company solves, what workflow changes, what outcome improves, and why the claim is credible. The more crowded the AI market becomes, the more important it is for brands to use specific, problem-led positioning.
AI makes brand more important, not less. When content production becomes easier, coherence becomes the scarce asset. CMOs should establish brand guardrails, clear positioning, and governance systems that help humans and machines create consistently without flattening the brand into generic output.
A useful question is, "What should CMOs know about your brand?" Strong vendors will answer with a clear problem, a specific point of view, and a business outcome. Weaker vendors will default to feature lists, category jargon, or generic AI claims.
Marketing teams often adopt new tools quickly, and modern martech stacks already create security and data risks. AI increases those risks because tools may touch customer data, campaign data, proprietary content, and employee information. CMOs should work closely with CISOs, legal, procurement, and data teams before adding AI tools to the stack.
The CMO's role is increasingly one of translation and orchestration. Marketing leaders need to translate technical complexity into customer value, orchestrate humans and AI agents across workflows, protect brand coherence, and help the organization make better decisions faster.
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