From AI Hype to Impact: How GTM Leaders Can Shape the Future

The AI boom isn’t slowing down, but the real challenge starts now—delivering value that sticks.

Sequoia Capital 's recent insights call this “Generative AI’s Act Two”—a shift from flashy demos to building products that people rely on every day. While ChatGPT may have hit 100M users faster than any app in history, the reality is that many AI applications struggle to keep users coming back. Sequoia points out that the average daily active user rate for these apps is around 14%, exposing a major gap between what AI promises and what it actually delivers. The great wave of AI App churn is coming if not addressed.

David Cahn from Sequoia digs deeper in his piece, "AI’s $600B Question", emphasizing that the challenge is no longer just attracting users—it’s converting massive infrastructure investments into real, sustained business outcomes. He calls this phase the “primordial soup” of AI—where potential is high, but the hard work of turning that potential into enduring value has only just begun. I couldn't agree more.

McKinsey’s latest report reinforces this shift. Today, 65% of organizations are using generative AI, but the biggest gains are still in internal productivity—reducing costs in areas like supply chain and customer service—rather than unlocking new revenue streams.

This reveals a key challenge for GTM leaders: it’s not enough to just adopt AI or sell the flashy capabilities; we need to align its capabilities with real customer needs, turning those capabilities into solutions that generate consistent, reliable value.

So, what will it take to succeed in this next chapter? Here’s my take for how GTM Leaders can bridge the gap from AI technology to enduring, tangible customer value.

Understand User Needs Deeply: Why Users Stay Matters More Than Why They Try

It’s not enough to build sophisticated models or structuring unstructured data—if you’re not understanding why users come back, you’re missing the mark. Low retention rates show a gap between tech and what users truly value. Successful SaaS (and AI) is about solving pain points that keep users engaged long-term. When building the mid-market segment at Vanta, we spent countless hours with customers, learning how their needs differed from SMBs. It meant developing a new approach to pricing, tied to what these mid-market personas truly valued, and required deep collaboration across sales, customer success, and product to redefine messaging, the sales playbook, and ultimately the product. The companies that foster this kind of partnership will create enduring value.

Retention Over Reach: Avoid the Churn Tsunami by Delivering Everyday Value

As McKinsey points out, the value of AI lies in building products that solve ongoing user problems, not just creating the latest shiny object. The new revenue growth from $0-$10M in AI applications appears to be around the 18 month mark. While that kind of growth is exciting, it means there's an extremely limited view into renewal cycles, and if customer adoption and retention isn't a core pillar of GTM teams aligned across Sales/CS, then we're setting ourselves up for a wave of churn. The lines between sales and service continue to blend, and the GTM teams of the future will be built around value delivery beyond contract signature. This means different compensation plans, what it means to be an AE, how customer success operates, etc.

Create Differentiated Use Cases: Depth Beats Breadth in the AI Era

The initial wave of generative AI saw broad applications, but the next step is carving out specific, high-value use cases. Vertical SaaS is booming in the AI age so far, and while yes a piece of that is because AI has opened up some of these legacy markets for new technology (healthcare, insurance, etc), I believe it's because these vertical organizations are uniquely positioned to laser focus on the specific value delivery they bring to their customer. By specializing in a market these vertical AI applications can go deep into value cases and ROI value delivery for their customers that are challenging insights to bring for a horizontal broad application.

Master Monetization: Sell Impact, Not Just Efficiency

Too many AI projects have focused on productivity without a path to revenue. With the $600B question looming, GTM leaders need to prioritize business models that align with customer willingness to pay—whether through subscription models, usage-based pricing, or upsell opportunities tied to clear productivity gains. Usage based pricing is hot in AI right now, because effectively you’re selling a form of labor. The challenge here though lies in under-utilized products (see above) and hesitancy from CFOs to lock into an unknown spend on the year that could balloon ,without tangible value other than efficiency gains. Spend time on your monetization strategy and don’t do it in a silo without customer feedback.

Leverage AI for Customer Insights: From Gut Feel to Data-Driven Strategy

Use AI not just as a product feature but as a tool to refine your go-to-market strategies—segmenting customers more precisely and tailoring offerings to different needs. Data is more accessible than ever, so there’s no need for guesswork when analyzing segmentation strategies or closed-lost themes. Teams that analyze this data and use AI to accelerate insights into action will create the most value. This allows GTM leaders to focus on segments that deliver the highest value, helping prioritize resources and refine positioning.

Embrace Collaborative Innovation: The Real Power of Unlocking AI Value Is in Partnership

AI applications aren’t just another SaaS playbook—it requires deeper collaboration between data scientists, industry experts, and end users. Companies that leverage open-source tools and fine-tune models for specific needs will outpace those trying to build in isolation. GTM teams working alongside product and obsessing over the customer will build sustaining value for customers and the market.

AI’s next chapter isn’t about who has the flashiest tech or AI enabled features—it’s about who can turn potential into real, lasting value.

For GTM leaders, the path forward is clear but demanding: understanding users deeply, focusing relentlessly on retention, crafting precise use cases, mastering monetization, leveraging data for sharper insights, and fostering true collaboration across teams. The stakes are high, and the window for proving AI’s worth is narrowing. Those who can blend technology with a deep understanding of customer needs will not just survive but thrive, setting new standards in the market. We need to move beyond experimentation budgets and create defined lasting value.

The GTM playbook of the past won't cut it anymore—it’s time to deliver results that endure. GTM leaders need to step up, adapt, and turn AI’s potential into the new gold standard. Those who do will set the pace for the entire industry.