Why I’m betting on experience-led growth and using AI to prep my teams

For the last few years, AI has been great for boosting individual seller productivity by automating workflows, summarizing calls, drafting emails, etc. That was the easy win. Now, it's the bare minimum.

The transformative value of AI is no longer in shaving minutes off a task. It's in creating entirely new capabilities for customer engagement and pipeline management.

I predict that over the next 12 months, the AI battleground will shift to experience-led growth. In this new model, revenue AI won’t just optimize internal workflows, it will drive hyper-personalized engagement with buyers and coaching from leaders. To succeed in that environment, revenue leaders have to figure out how to use revenue AI to automate productivity and augment their people. This two-fold approach will separate companies into winners and those bound for stagnation.

The urgency here is real. If companies want to pull ahead, they have to do more than leverage AI to return valuable selling time to their AEs. Giving them back 10–15 percent of their time is only a direct growth lever if they apply that newfound time to having higher-quality customer conversations.

So how do we automate the mechanics of a deal without sacrificing the human judgment required to close it?

The answer lies in drawing a hard line between automation and human growth right at the point of face-to-face, strategic conversations. Automation should handle all the mechanical components of selling, but it must defend the sacred space of human relationships, be they between reps and managers or reps and buyers.

This core philosophy is what guides my team’s process: Technology handles the mechanics while people focus on the deal mastery.

To put that philosophy into practice, you need a foundation of unassailable data. This is the critical caveat: The strategy of elevating your reps only works if you first eliminate the single most significant trust killer in sales: the reliance on gut feelings and what I call "story time” in pipeline reviews. Neither one is based on clean, hard data.

If you want to eliminate weak deals and the stories they’re built on, use a non-negotiable inspection routine:

1. Instrumentation: Build your sales methodology directly into an AI-powered solution. For us, this was Gong’s Deal Board. We defined opportunity vitals, like qualification criteria, and trained AI Tracker on them.
2. AI as the unbiased mirror: The Gong Revenue AI Operating System now assesses the quality of our reps’ discovery and execution against those vitals. It gives managers and reps an unbiased view of opportunity health that’s backed by conversational data. This is the new foundation for our pipeline reviews and coaching meetings.
3. The human overlay: This process doesn't replace the seller, rather, it equips the manager. The AI signals where there might be a weakness, like a critical step missed or a stakeholder not engaged. The manager uses this to ask high-quality, prescriptive questions and coach the seller, who then provides an action plan.

The resulting data hygiene and predictability are the output of an AI system that augments, rather than overrides, human insight. This weekly, consistent cadence, combined with executive leadership using the same inspection routine in their reviews, will drive success. It’s how we’ve been able to land our forecasts within a couple of percent in recent months.

Achieving peak predictability through data is crucial, yet the ultimate goal is ensuring that the time returned to our sellers and managers, and the insights we've given them, are used to drive genuine excellence.

As agentic AI capabilities mature and features like AI Briefer ingest data from our entire revenue tech stack, information sharing is becoming hyper-personalized and scalable. The days of a manager listening to 20 hours of calls to find one coaching moment are over.

This paradoxically makes the work of coaching more important than ever.

AI excels at data and mechanics, but it’s a long way from being able to creatively problem-solve, negotiate, or build the political capital necessary for an enterprise sale. In other words, information can be automated, but empathy, strategic insight, and human connection are much harder to replicate. That’s why sales enablement needs to focus deeply on training these selling skills.

So, for example, when we teach every new seller on our team to diagnose before they prescribe, we’re really teaching them to ask questions that surface and quantify buyers’ challenges, listen more than speak, and take ownership over the value they create. When AI has your back so both your sellers and managers can focus on that type of skill-building, you’re primed for growth.

It’s a given that top-tier teams are using AI for productivity boosts. In this next phase, our success won't be measured by the number of AI Agents we deploy, but by how well those agents enable our sellers to focus on and master the art of strategic, high-value conversations.

The era of choosing between spending time and resources on rep talent and digital efficiency is over. The future will belong to leaders who successfully merge them. Experience-led growth gives us a mandate to ensure that AI makes business more predictable and elevates the quality of our managers’ and sellers’ engagement with each other and buyers. It’s time to let AI handle the data while reps close the deals.