Back to Blogs
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 made one thing clear: AI marketing has moved from experimentation to operating discipline. Since March, conversational search, AI agents, and GEO have only accelerated. For B2B CMOs, the priority is no longer “go play.” It is choosing the right problems, testing measurable use cases, and preserving human judgment where it matters most.
Back in March, after three full days at HumanX, the big takeaway was clear: AI had moved far beyond “fancy email helper.” The event was a blizzard of insights about how AI is reshaping marketing, leadership, search, personalization, productivity, and organizational design.
A few months later, that conclusion looks less like event enthusiasm and more like the new operating reality.
Google has continued pushing search toward AI-generated and conversational answers. Its AI Mode lets users ask complex, multi-part questions and follow-ups inside Search, while AI Overviews are now a normal part of the search experience for huge numbers of users. Recent research has also found that AI Overviews can reduce traffic to source pages, which makes the old SEO playbook look about as current as a fax machine wearing sunglasses.
Meanwhile, AI agents are moving from demos to workflows. Google, Adobe, OpenAI, Salesforce, and others are all leaning into agentic systems that can take action, not just generate copy. The implication for CMOs is simple: This is no longer a side experiment. It is a management discipline.
Here are the HumanX takeaways that still matter, updated for what B2B CMOs should do differently now.
In 2024, many marketing teams were told to “go play” with AI. That was a reasonable starting point. Curiosity mattered. Familiarity mattered. Getting over the blank-page terror of a prompt box mattered.
But “go play” has outlived its usefulness.
The better instruction now is: Go solve a real problem.
That means CMOs should stop asking, “How can we use AI?” and start asking:
The winning teams are moving from tool tourism to use-case discipline. They are identifying specific pain points, applying AI with intent, and measuring whether it improves speed, quality, conversion, or customer experience.
Despite all the sophisticated technology at HumanX, one message kept surfacing: Storytelling still matters. Maybe more than ever.
AI can help draft, summarize, remix, and personalize. It can accelerate content production. It can even help identify patterns in customer language that humans might miss. But it does not automatically create trust.
The companies breaking through are the ones connecting technical capability to human impact. Buyers do not want a lecture on model architecture. They want to know what changes for them, their teams, their customers, and their careers.
That is why founder voices, customer stories, expert POVs, community conversations, and authentic executive communication still matter. In a market increasingly flooded with AI-assisted sameness, human specificity becomes a differentiator.
The CMO job is not to produce more AI-generated content. It is to make the company more credible, useful, and memorable.
One of the most useful frameworks from HumanX came from Amazon’s approach to categorizing AI applications:
This framework is useful because it prevents every AI idea from competing in the same messy pile.
For CMOs, workplace productivity might include campaign briefs, meeting summaries, content repurposing, research synthesis, and sales enablement updates. Business workflows might include lead routing, content operations, customer journey orchestration, website conversion, and partner marketing. Innovation and research might include new market analysis, customer insight mining, concept testing, and AI-assisted product marketing.
Each bucket needs different governance, metrics, and executive expectations. Productivity tools may be judged by time saved. Workflow automation should be judged by throughput and business impact. Innovation use cases should be judged by learning velocity and decision quality.
HumanX made clear that AI agents are coming fast. The most useful agents do not merely answer questions. They decompose high-level objectives into executable steps, take action across systems, and return with useful outputs.
Since March, the agentic AI conversation has only intensified. Google has expanded AI experiences across search and advertising. Adobe has framed customer experience around agentic AI. OpenAI’s Operator preview showed how agents can navigate websites and perform browser-based tasks. None of this means agents are ready to run marketing while the CMO takes up pickleball professionally.
It does mean CMOs should start redesigning workflows now.
Good agent use cases have a few things in common:
Bad agent use cases are vague, high-risk, poorly governed, or dependent on taste without human review.
The practical move: Pick one workflow that is painful but bounded. Build a pilot. Keep a human in the loop. Measure the before and after.
One of the most important HumanX themes was that the future of search is conversational, not keyword-based.
That future has arrived faster than many expected. Google’s AI Mode is designed for complex questions and follow-up exploration. AI Overviews synthesize answers before users click. Recent studies have found that AI-generated search summaries can reduce traffic to source pages, while other research suggests AI systems may select sources differently than traditional rankings.
For CMOs, this means SEO is not dead, but it is no longer enough.
Content needs to be:
The old question was, “Can we rank for this keyword?” The new question is, “Can an AI answer engine confidently use us as a source?”
That is a different game. CMOs should start tracking visibility in ChatGPT, Gemini, Perplexity, Claude, Google AI Overviews, and other answer environments. The measurement will be imperfect for a while, which is another way of saying marketing will remain marketing.
HumanX also surfaced a persistent truth: The line between cool and creepy is thin.
AI makes personalization easier, but easier does not mean better. The best personalization helps buyers feel understood. The worst makes them feel watched.
Context-based personalization remains a safer starting point than invasive hyper-personalization. Device language, geography, time of day, behavior on your site, declared interests, role, industry, and buying-stage signals can all be useful when handled responsibly.
But CMOs should be careful with anything that feels too private, too predictive, or too presumptuous.
A good personalization test is simple: Would the buyer say, “That was helpful,” or “How exactly do you know that?” If it is the second one, step away from the creepy penguin cliff.
One of the better HumanX comments was that LLMs are ideal for tedious and rote work that does not require taste. Summarizing years of call transcripts? Wonderful. Creating the 47th bland LinkedIn post about “unlocking growth”? Less wonderful.
AI should free marketers to do more valuable work, not bury buyers under more average content.
Use AI to:
Keep humans in charge of:
AI can be a bicycle for the mind. It should not become a scooter for strategic laziness.
The last HumanX takeaway may be the simplest: Daily users win.
Teams that use AI every day build fluency. They learn what works, what fails, what needs review, and where the real leverage is. Monthly users stay stuck in novelty mode. They keep rediscovering the same beginner lessons.
CMOs should create small daily habits across the marketing team:
The goal is not to make everyone a prompt engineer. The goal is to make AI part of the operating rhythm.
The AI revolution is no longer a future-tense conversation. It is already changing how buyers search, how teams work, how content gets discovered, how workflows run, and how customer experiences are built.
The winners will not be the companies with the shiniest tools. They will be the companies that use AI to solve real business problems while preserving the human judgment that makes marketing worth trusting.
For B2B CMOs, the priorities are clear:
HumanX was not a reminder to chase every AI tool waddling across the ice. It was a reminder to lead.
Start by identifying one or two high-value business problems where AI could improve speed, quality, conversion, or customer experience. Avoid broad “AI transformation” projects until the team has proven smaller use cases.
Conversational search has become more central. Google AI Mode and AI Overviews are pushing users toward synthesized answers and follow-up questions, which means CMOs need content that is structured, credible, and easy for AI systems to cite.
Some agentic workflows are ready for testing, especially repeatable tasks with clear inputs, bounded risk, and human review. CMOs should avoid handing agents vague, high-stakes work without governance.
No. AI increases the supply of generic content, which makes strong storytelling, founder voice, customer proof, and original insight more valuable.
Measure business outcomes, not tool usage. Useful metrics include time saved, conversion lift, content quality, customer experience improvements, answer-engine visibility, workflow throughput, and pipeline impact.
CMO Huddles helps B2B marketing leaders win by bringing together peers, fresh perspectives, and opportunities to build stronger personal brands. Want to join the huddle? Learn more about CMO Huddles and apply to join the community.