Last year at HumanX, much of the conversation centered on AI’s novelty, with many organizations still in a wait-and-see mode. In 2026, that tone has shifted.
In San Francisco, the epicenter of the AI conversation, it was clear the market has moved beyond experimentation. The hype around flashy capabilities has given way to a more grounded focus on adoption, trust and ultimately, driving real business outcomes.
Across sessions and conversations on the show floor, from enterprise CMOs to AI founders, a consistent message emerged: AI is no longer a differentiator — execution is.
Here are some of the key themes shaping how marketing, sales and GTM leaders should be thinking about AI over the next year.
Key Takeaways
- AI is no longer a differentiator — execution is. HumanX 2026 made clear the market has moved past experimentation into a grounded focus on adoption, trust and business outcomes.
- Go-to-market (GTM) teams must operate as one. AI is breaking down silos between marketing, sales, product and support teams.
- Generic “AI-powered” messaging is dead. Buyers want proof of business outcomes.
- Brand matters more, not less. As AI scales content production, the risk is brand fragmentation.
1. AI Is Forcing GTM Teams to Operate as One
AI isn’t just changing how go-to-market teams execute — it’s reshaping how they’re structured.
In Powering the Full Customer Journey, both Kate Prouty, SVP and CIO at Akamai, and Bill Gross, CEO at ProRata AI, emphasized that AI is breaking down traditional boundaries between marketing, sales, product and customer support teams. Siloed teams are no longer just inefficient. They actively create friction in the customer experience.
Prouty noted that disconnected systems and teams often lead to missed opportunities and inconsistent brand stories. At the same time, product is becoming increasingly central to GTM, serving as a core driver of both acquisition and retention. Gross reinforced this shift, arguing that organizations must “flatten” operations around the customer.
AI requires shared data, integrated workflows and top-down organizational change to become effective in an organization. AI doesn’t just optimize GTM — it forces companies to rebuild it around their customer.
2. “AI” Messaging Is Dead: Prove Business Outcomes or Risk Credibility
At this point, “AI-powered” has become a buzzword in the B2B market, not a differentiator. Buyers no longer reward vague AI positioning. They expect clear, measurable business impact.
In the session, How to Market Your AI Tools Successfully, Aliisa Rosenthal, general partner at Acrew Capital and former OpenAI leader, made that shift explicit. Buyers are prioritizing cost reduction and revenue impact above all else. Joleen Liang, founder of Squirrel AI Learning, reinforced that point, emphasizing that real-world outcomes are what ultimately drive adoption with AI tools.
This dynamic is playing out across industries. In manufacturing, for example, AI adoption is driven by measurable reductions in downtime and maintenance costs rather than AI model sophistication.
The underlying shift is a move from curiosity to skepticism. The market is saturated with similar AI messaging. Buyers want proof your tool drives meaningful results. If your brand narrative doesn’t clearly connect to tangible business outcomes, it will no longer resonate.
3. The Customer Journey Is No Longer Linear
AI is fundamentally reshaping the customer journey — from initial discoverability through sales and post-purchase engagement. What was once considered a linear funnel is now a dynamic, intent-driven system.
In Powering the Full Customer Journey, Gross pointed to a critical behavioral shift: Users are moving from keyword searches to complex, natural language questions. This evolution unlocks deeper intent signals and is redefining how brands are discovered and evaluated within generative engines.
That shift was echoed in our roundtable, Building Visibility and Shaping Perception in Generative Engines, where marketing leaders discussed how AI is rapidly becoming a core discovery channel. The focus is no longer just traditional SEO, but how brands show up across LLMs.
Prouty reinforced that journeys are no longer sequential but conversational. As a result, marketing, sales and support teams must operate as a single, coordinated system rather than siloed functions. With access to real-time data, teams can respond in the moment — not after the fact.
The implication is significant: the competitive advantage is no longer a more efficient funnel, but a more accurate, real-time understanding of customer intent. Teams that can act on those signals as they emerge will outperform those still optimizing for a traditional, linear journey.
4. As AI Scales Execution, Brand Becomes the Differentiator
As AI accelerates execution, it’s easy to assume branding becomes less important. However, the opposite is true.
In Building Brands That Matter in the Age of AI, Marcel Marcondes, Global CMO of AB InBev, made the case that human creativity and brand discipline are becoming more critical — not less. While AI enables faster content creation and personalization at scale, it doesn’t replace the need for clear, consistent brand building.
Marcondes emphasized that strong brands are built through focus and consistency. In a landscape where AI can generate endless variations of content, the risk isn’t underproduction, but brand fragmentation. AI should remain an enabler of your brand voice and storytelling, not the centerpiece of your marketing strategy.
For CMOs, the role is evolving. Marketing executives are increasingly acting as a bridge between business objectives and human needs while protecting brand authenticity in an AI-driven ecosystem.
In a market saturated with AI-driven content, brand clarity and human connections are becoming true differentiators.
5. The Hardest Part of AI Right Now? Adoption
While much of the AI conversation still focuses on innovation, the bigger challenge is far more practical and something we’ve been touching on throughout this blog — getting people to actually use it.
In How to Market Your AI Tools Successfully, Mada Seghete and Joleen Liang both underscored that adoption is the primary barrier to success. Even the most advanced or flashy tools fail if users don’t understand how to integrate them into their workflows.
Seghete pointed to a common issue: Users struggle with prompting and need more structured guidance. Templates, predefined workflows and embedded best practices are critical to reducing user friction. Liang reinforced that companies often fail to scale their AI services because they don’t fully understand the day-to-day needs and behaviors of their users.
The implication is clear. Winning companies won’t be those with the most advanced models, but those that make AI intuitive and usable.
That means simplifying complexity, productizing use cases and reducing cognitive load at every step. The future of AI GTM isn’t better models — it’s better usability.
What HumanX 2026 Made Clear
If last year’s conversation was about what AI could do, this year was about what it actually takes to drive ROI.
Across HumanX 2026, the shift was hard to miss. AI is no longer novel, experimental or even particularly differentiating on its own. The real work, and the real opportunity, lies in how organizations apply it: operationalizing it across teams, building trust with buyers and delivering outcomes that matter.
That’s a more complex challenge than building a new tool or launching a new feature. It requires rethinking how teams are structured, how your brand shows up and how customers are reaching your brand.
In other words, AI certainly didn’t get less important. It just got more practical.
And for companies willing to do the harder, less flashy work, that’s where the advantage now lives.
Check out our webinar with HumanX, Winning Mindshare at AI Conferences, from earlier this year!
