In a tough economy, is a revenue AI operating system the competitive advantage GTM needs?

We’re operating in an unforgiving economic climate. Growth is harder to find, margins are tighter, and there’s little appetite to increase budgets or headcount to keep pace. Most of us are facing the same challenge: how can we keep growing when the usual levers — more reps, more spend — are off the table?

The answer lies in productivity per rep. Not in doing more activities, but in helping every seller generate more revenue while holding costs flat. In this market, productivity is the new growth.

Thankfully, this is where a revenue AI operating system can become a true differentiator. Not as a set of shortcuts or automations around the edges, but as a robust system that can scale the instincts and abilities of our best reps across the whole team. Done right, revenue AI can expand deal capacity, accelerate productivity, and lift win rates — the trinity of GTM leverage in tight conditions.

We’ve reached the point where incremental time-savers aren’t enough. A real differentiator will be how fast AI can turn our data into better actions — surfacing our “next best moves” in ways we’ve never seen before.

I’ll admit I’ve been cautious about AI’s promises. It’s easy to get swept up in the hype, and getting a few minutes back here or automating a few workflows there isn’t nearly enough in a harsh economy.

But since the pressure to grow continues, I’m encouraged by how revenue AI is evolving — away from a set of “AI features,” into a more connected operating system that links insights to actions and outcomes. That shift has the potential to make the next two years truly transformative for seller productivity.

When I think about where it can have the biggest impact — particularly as new AI agents start showing up for reps and leaders alike — three opportunities stand out.

Reps lose hours each week pulling together background on an account — scanning websites, digging through LinkedIn, mapping org charts, reading news, piecing together initiatives. AI can compress that five-hour research cycle into five minutes, synthesizing dozens of data points across sources and surfacing what really matters: who’s driving change, where the budget sits, and which priorities are already in motion.

That’s not just efficiency; it’s more capacity. With richer context delivered where they already work, reps can engage more accounts and walk into conversations at a higher, more strategic level. It’s how we create more at-bats without more headcount.

Too many deals stall because we miss subtle but critical signals. A competitor undercutting on price, a champion losing influence, or a new executive shifting priorities. AI can unearth those signals across conversations and CRM activity, flagging risks before we see them.

The upside isn’t only saving at-risk deals; it’s also focusing on the ones most likely to close or expand. By combining real-time deal health with account potential, AI helps GTM teams protect what’s vulnerable and double down on what matters most. In a market where time is the most finite resource, having that focus directly lifts pipeline quality and win rates.

This is where I see the biggest upside. Systems that nudge reps to “send another email” or “log an activity” don’t move revenue. Today’s revenue AI can lighten the load by drafting outreach and automating follow-ups. But a true revenue AI OS goes further, guiding reps with insight-driven next best actions.

Imagine it telling us:

“Engage this executive sponsor, they’re emerging as the decision maker.”

“Loop in a technical stakeholder, that’s where the deal is slowing down.”

That’s the leap from automation to augmentation. It gives every rep the same judgment that a top-performing seller or frontline manager would bring to a deal. When next best actions are grounded in signals, the quality of every interaction rises. That’s how doubling revenue per rep moves from aspiration to achievable.

We’re operating in an economy where spending more isn’t an option. The GTM teams that win will be the ones turning AI insights into action faster than anyone else. The real advantage isn’t in cutting costs, it’s in expanding deal capacity, lifting productivity, and closing more business with the same team.

As a member of Gong’s Customer Advisory Board, I see these challenges and opportunities play out across leading organizations. We’re all facing the same macro reality: rising targets, intensifying pressure, and flat budgets. Productivity per rep remains one lever we can still pull, and revenue AI gives us the chance to pull it harder.

I don’t believe every claim being made about AI. But I do believe the next 12–24 months will be decisive. This is when we’ll see whether AI becomes just another feature in our tech stacks, or the engine that truly drives revenue performance.

The difference will come down to how quickly teams turn data into decisions and insights into action. In this market, that capacity is the new competitive advantage — the one that keeps teams in the game when it matters most.