Over the last six months, we've started hearing a consistent refrain from independent operators: I'm not waiting anymore.

The gap between what's technologically possible and what legacy software vendors actually ship has gotten too wide, and distributors are noticing. At Premier ProduceOne, SVP Marc Pavlofsky is applying a pragmatic and operator-first lens to AI, one that looks less like hype and more like a roadmap for how independent distributors will actually adopt this technology over the next few years.

His approach illustrates a distinct point of view: AI not as a product category to buy, but as a force multiplier that lets operators finally stop waiting on legacy software to catch up.

The Vibe Shift In Independent Distribution

For too long, the question has been: "What tools does the market have available?"

The question is flipping to: "What tools do we need to build to win?"

That's the shift Marc is feeling, and more distributors are starting to see themselves as builders and not just buyers. Waiting for a software company to build what they need has become too expensive.

"If I say I want it and there are tools that can build it for me, I will get it," Marc said. "I'm not putting up with it. I'm just not accepting [software delays] as an answer anymore," Marc said of legacy provider delays.

"There's a part that I think may scare a lot of software providers, but it has me very excited as an operator," Marc said.

The fear Marc is alluding to can be real for everyone as operators are losing patience with the traditional model with years of waiting, roadmap discussions, feature debates. But the excitement is real too: For the first time, small teams can move as fast as big ones.

A PDF Ingest Tool, Built on a Whim

Marc's first hands-on AI project was small but telling.

One of his technology vendors consistently bills Premier ProduceOne in PDFs and regularly runs over budget. Rather than keep fighting invoice line items manually, Marc vibe-coded a PDF-to-CSV ingest tool himself that now flags overbilled tickets automatically.

As he put it: "I'm sure if I got a hold of one of your coders, they would be pulling their hair out saying  'It's OCR, it's so simple.' But I couldn't, and I didn't need to, because I was never going to set aside the time to do that. What I built works, and that’s all that matters to me"

That’s what the future of buyer/vendor relationships looks like - if there is a problem, distributors are not going to be waiting on their vendors to “fix”, they’re going to fix it themselves. For Marc, that changes everything. He's no longer stuck choosing between paying attention to invoice audits or running his business, he gets both.

Three Workflows That Are Obvious Next Candidates

Marc pointed to a handful of specific workflows he sees as near-term AI opportunities inside produce distribution:

• Voice-native CRM for DSRs. Reps dial a number on the drive home and talk through their day. The agent turns loose conversation into structured pipeline entries like close probability, stage, total opportunity, even auto-populated customer addresses. No more evening data entry.
• Competitive price ingestion. Pull in competitor price lists in whatever format they arrive: PDFs, scraped pages, screenshots, etc. Let AI interpret the SKUs, map them to the internal catalog, and surface pricing gaps. Data that was too stubborn to get into the organization is suddenly accessible.
• Vendor invoice audits. The problem Marc already solved for himself, now repeatable. Every distributor has vendors who overbill. Few have the time to check line by line.

Each has the same shape: a specific, painful workflow nobody was going to hand-build software for, now buildable by the person who feels the pain.

The Internal Software Thesis

The bigger idea Marc is sitting with is where the next layer of value will get created, and it's not from buying more software.

"We are going to get to a place where I will be able to have a small, sophisticated jack-of-all-trades team that understands the commercial logic, and then get a ton of direct code support from the AI."

In his view, distributors won't become software companies. But they will build internal tools the way they build internal spreadsheets today. A single solutions engineer, one person who understands the business and coordinates with AI to do most of the actual coding, can ship custom tools to the people inside the org who need them.

"I need an app on my phone that does this" stops being a three-quarter vendor request. It becomes a two-week internal project. And while he’s not staffing it quite this year - it is in next year’s budget.

Adoption Is an Environment, Not a Mandate

One of the sharpest points from the conversation was how Marc thinks about getting AI into the hands of his team. He doesn't frame it as "how do we get people to use AI?" He frames it as: how do we get people into an environment where AI is already doing work for them?

The distinction matters because mandating AI usage is an input, but designing workflows so people experience the outcomes of AI (a CRM that fills itself in, an invoice auditor that catches overcharges) is what drives adoption.

"It's not my job to make them use AI. It's my job to make sure they're in an environment where they get the outcomes from it."

Productivity Unlock, Not Headcount Cut

Marc was emphatic on one point: AI isn't an excuse to shrink the sales team.

A DSR who carries 80 accounts today, with AI handling the admin and prep work, can carry 120 or 150 tomorrow. That rep's commission goes up. Revenue per rep goes up. Hiring gets easier to justify, not harder.

The people will be more valuable, especially in my world, where it's all downstream of [these productivity enhancements] . . .  I do think that my sales rep who used to carry 80 accounts may carry 120 or 150 — and oh, by the way, he just raised his commission.

That's the shape of the unlock in distribution. The human doesn't go away. The friction around the human does.

The Next Skill: Knowing Where to Point It

What stands out most in Marc's thinking isn't any single tool or workflow. It's the lens.

Most of the AI conversation in food distribution right now is about capability, with people asking “what can these models do?” The more useful question, the one Marc is asking, is about fit: where are the specific workflows inside my business where permanent cost comes out and permanent value goes in?

That's the real skill now. Not using (or even building) with AI, but knowing where to point it. As Marc put it: "I have to spec out creative, targeted use cases for AI."

The distributors who treat AI adoption as a strategic exercise rather than a rollout program are going to compound a lot of advantage over the next few years.

Premier ProduceOne is early in that journey. But the thinking is sharp, and the direction is set.

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