The ascending impact of AI: a three-level framework

Most leaders I talk to are under the same mandate: hit bigger targets with the same or fewer resources, and use AI to bridge the gap.

The pressure is real, but so is the confusion. Most executives know AI matters — they just aren't sure what actually works versus what’s noise. And that uncertainty is costly.

According to Stanford HAI's 2025 AI Index, 78% of organizations have adopted AI — and PwC's 29th Global CEO Survey finds that 42% of CEOs say their number one concern is whether they're transforming fast enough, ahead of every other business risk. Yet only 12% say AI has delivered both cost efficiencies and revenue lift.

What I’ve seen working with exec leaders across hundreds of large enterprise AI customers and early adopters is that most have fallen into what I describe as the AI efficiency trap: using AI to do more work, instead of using it to change how the business actually operates. They achieve real benefits through efficiency and productivity, but they are missing the even bigger opportunity to transform. They optimized tasks without changing the operating rhythm.

What’s possible today for companies is dramatically different than just a year ago. Understanding where that innovation edge is helps us design our team’s revenue journey to take advantage of the transformation possible and build for the future. I don’t think doing anything short of this is an option any longer.

The organizations pulling ahead have made a different choice. They moved past thinking about AI as an efficiency play and started treating it as the operating system for their entire revenue journey. That shift, from AI as a feature to AI as a foundation, is what separates the organizations seeing real transformation from the ones still experimenting at the edges.

Here’s a framework I designed to help enterprise leaders think about what’s possible with AI and design their vision. There are three levels of ascending impact. Each has real value, and that value increases as we ascend up the inverted pyramid. This has been helpful for leaders to put into context where they are and where they want to lead their company.

This is where most AI initiatives begin. The goal here is efficiency. It uses a valuable base layer of AI functionality to help people do things more easily and quickly. It’s often essentially a task automation play when you look at how it’s run. AI helps with tasks like drafting summaries, writing emails, and updating fields in systems like a CRM. At this level, AI handles the administrative burden and gives people time back. It’s genuine value, but it’s an efficiency gain, not a performance gain.

That’s your Level 1 opportunity, and it’s a reasonable place to start. It’s just not a reasonable place to stop.

This is where AI starts to move the needle on performance, not just efficiency. Getting there requires something Level 1 doesn’t: AI that deeply understands what “good” looks like in your specific business. What behaviors separate your top people from everyone else? What do your best-run processes have in common? Where are the narratives, playbooks or product releases falling flat?When AI can answer those questions and guide your team accordingly, each team member is automatically guided toward your best standard. You now know what defines your top performers and how to up-level others with those key behaviors. Everyone knows how to execute using your best practices playbook.

According to Gong’s State of Revenue AI 2026 report, organizations embedding AI as a core driver of their GTM strategy are 65% more likely to increase win rates than their peers. And sellers that frequently use AI generate 77% more revenue than those not using it at all.

Getting to Level 2 requires AI with a deep understanding of your specific business and revenue motion. To do this well, it needs full context, intelligence that is intentional for the use case, and a robust data graph foundation. Without these, AI can help individuals do things faster. These get you to better.

This is where AI transforms your business, and it is a level most organizations haven’t reached yet. At Level 3, your entire team operates in a cohesive AI-powered operating rhythm. The AI now orchestrates the entire team to execute the individual best practices in level 2, in a seamless flow from insights to actions. As a leader, now I’m getting full consistency and scale.

Importantly, AI is embedded directly into the workflows where the teams are operating. It powers, guides, and orchestrates their actions where they’re living. For the enterprise customers I work with, this is often the biggest unlock to driving sustainable adoption and value realization.

At Level 3, AI begins to realize the vision of an AI operating system. It becomes a continuous, context-aware intelligence layer woven throughout the entire journey, connecting signals, insights, and actions at every step. 

The companies winning the next era of go-to-market are redesigning how their revenue engine operates with AI at the center, not adding AI to an existing motion and hoping for better results.

Start with an honest assessment of where you actually are, not where you aspire to be. Most organizations, when they look closely, find they’re at Level 1, with pockets of Level 2 in isolated parts of the business. Knowing that clearly is the prerequisite to knowing what to build next.

From there, the question is where moving up a level would have the most immediate impact on your numbers. Choose the highest-leverage use case, the one that changes the outcome your board is watching most closely.

Then ask whether the AI you’re building on can actually get you there. Getting to better, and eventually everywhere, requires AI that understands your specific business motion deeply. The platform you choose sets the ceiling on what’s possible.

Assess where you are. Architect the vision and path forward. Get the foundation right. The enterprises doing those three things well are the ones that will define what the new standard of best-in-class looks like in the AI era.

See how the Gong Revenue AI OS drives predictable revenue growth.