From Doers to Orchestrators: A VC's Vision for the Revenue Team of the Future

Ben Fletcher has spent the last decade at Accel, one of Silicon Valley's leading venture firms, making bets on enterprise software, AI, and infrastructure. He's led investments in some of the most notable companies in the current AI wave — Lovable, Synthesia, Legora, n8n — and before that, spent years at Google leading M&A. His vantage point is unusual: he sees hundreds of companies at once, across industries and stages, which means the patterns he notices tend to be real. We sat down with him at Captivate '26 in Austin to talk about what separates the companies winning right now from the ones falling behind, and what he thinks the revenue org looks like on the other side of this shift.

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There's a word Ben Fletcher keeps coming back to when he talks about the future of revenue teams. Not "efficient." Not "automated." Not even "AI-powered," the phrase so ubiquitous it’s begun to lose meaning. 

The word he prefers is “orchestrator.”

"I see the revenue orgs really shifting to orchestrators," he said during his fireside chat at Captivate '26. "Not going away, but being the ones that help you insert AI at the right times."

It's a small word doing a lot of work. And understanding what he means by it requires starting with the companies that are already there.

The Real Separator

When Ben looks across his portfolio — and across the broader market — the reason that some companies are growing while others are stalling has become more and more clear. It's not product category, market size, or founding team pedigree.

It's shipping speed.

"The one common theme I see is the rate of innovation and how quickly those teams are now shipping on the engineering front," he says. "Those cycle times have been reduced so drastically. And now you're seeing it flow through on the revenue side."

This might sound like engineering shop talk, but it's not. What Ben is describing is a compounding advantage. The companies that have fully internalized AI as a production tool, not an experiment, are able to figure out what customers want and get it in front of them faster than competitors can respond. By the time anyone else catches up, the gap has already widened.

Fewer than 10% of enterprises have scaled AI agents to deliver tangible value, despite nearly two-thirds having experimented with them. What Ben watches for are the rare companies on the right side of that gap: the ones where AI is native to the way work gets done, not bolted on top of it.

"Those are the companies that are AI native," he says. "The ones that have really adopted the AI stack. And they're able to bring those efficiencies into every function."

How to Spot the Snake Oil

Ben is direct about the flip side of that observation. The same wave that's lifting the best companies is also carrying a lot of noise — tools built not to solve real problems, but to ride the moment.

He's watched a specific pattern play out. An AI product goes viral, then quickly rises from zero to $100M in revenue almost overnight. "But if the product has no defensibility, no use case,” he warns, “it will come back down.”

His criteria for durability are blunt: Is this genuinely speeding up a process that matters? Is it solving real complexity, or just eliminating a friction point nobody was paying for before? "If you can trace it back to the complexity it's solving and the ROI," he says, "then it looks like a full-on workflow that's been automated to exactly what I need. Versus: what's going to get me rich quick?"

For revenue and comp leaders evaluating their own AI stack, the question isn't whether a tool is impressive in a demo. It's whether the value is ongoing — and whether it shows up in your numbers.

The Reality of AI Fatigue 

There's a tension at the center of the AI moment that Ben names directly, and it's one that most vendor conversations carefully avoid.

"We've moved into an era of dichotomies," he says. "This is the most exciting time I've ever had in the industry, but it’s also the most exciting, and the most exhausting. And I feel for everyone in this room, because it's the same thing. It's a constant balance of making sure you're building and at the forefront, but not burning out because there's just so much going on."

He's describing something that data is beginning to confirm. A January 2025 survey found that 74% of the C-suite reported feeling excited about AI, while 68% of individual contributors reported feeling anxious or overwhelmed. Executives and frontline teams are living in different realities, and that gap creates its own kind of organizational risk.

For revenue ops and comp leaders, the implication is pointed. The answer to AI fatigue isn't less AI. It's better AI — fewer tools, more integration, clearer ROI. The teams that get this right aren't the ones throwing the most agents at their salespeople. They're the ones who've thought carefully about which agents actually matter, and built the workflows to deploy them with precision.

The Software Factory

To understand where revenue teams are heading, Ben reaches for an analogy from engineering — the sector where this transformation has already played out a step ahead of everyone else.

"With software development, you now have what's called software factories," he says. "Throughout the day, you have engineers that are planning the agentic work. They're looking at it before they sign off. They're never actually closing their laptops because there are always agents working in the background, and the engineers are orchestrating what's going on, checking, planning how they work together."

This is not hypothetical. Stripe is already merging over a thousand machine-written pull requests a week — not by eliminating engineers, but by transforming what engineers do. The humans set the direction. The agents execute. Review, judgment, and orchestration stay human. Repetitive generation doesn't.

Ben sees the revenue org moving through exactly the same transition. "You now have agents that can go out and do the prospecting for you. The BDR function — doing the outbound, cultivating, warming leads — we used to have recipes in the software tools to make sure we were there at the right buying time. That's just getting easier with agents."

56% of sales professionals now use AI daily, and those daily users are twice as likely to exceed their sales targets compared to non-users. That gap will only widen. By the end of 2026, 75% of B2B sales organizations are projected to incorporate some form of AI-driven sales development, up from about 28% at the end of 2024. 

The question isn't whether this is coming. It's whether your team is building for it now.

What Orchestration Means in Practice

Ben’s orchestrator framing is sharp, because it reframes the anxiety around AI and headcount into something more useful: a job description for what great revenue leadership looks like going forward.

"I see it on the research side, bringing data to the forefront, doing the outbound, helping through the process, automating RFPs," he says. "Revenue orgs are really shifting to orchestrators. To do that, you need folks with the right experience and the right tools to orchestrate and deliver at the right time."

In this model, the orchestrator doesn't disappear into the machine. They decide when the machine runs, what it does, and when a human hand is the right one for the job. That requires judgment that no agent has yet — market knowledge, relationship intelligence, the read on when a deal needs a person on the phone instead of an automated sequence.

What it doesn't require is spending 72% of your time on non-selling work. Sales teams using automation report saving roughly 18 to 22 hours per week per rep by eliminating repetitive outreach and administrative tasks. That's nearly an extra month of selling time per year, per person, available to be redirected toward the work that actually moves revenue.

"What was my process today?" Ben asks, summing up the question every revenue leader should be starting with. "And now, with AI — how can I automate it? How can I streamline it? And what is it going to look like in the future?"

The best revenue teams aren't waiting to find out.

Watch Ben’s full Captivate ‘26 session on-demand. 

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Ben Fletcher is a partner at Accel, where he leads enterprise software and AI investments. He is based in London and has been involved in the funding and growth of companies including Lovable, Synthesia, Lagora, and NAN.