When I was at Grainger, we had something called differential investment. The idea was straightforward. Certain projects mattered enough that they didn’t get handed to whoever had spare capacity. They got a leader pulled from the business, someone who understood how the company made money, put in charge of making the project deliver. Not a technologist. Not a project manager running a checklist. A business leader who owned the outcome.
I keep thinking about that model as I watch distributors approach AI. Because most of them are doing the opposite.
What Sysco Actually Did
Sysco put its AI strategy under formal board oversight this month. The board renamed its Technology Committee the Artificial Intelligence Transformation and Technology Committee, and it now meets monthly with management to oversee adoption. The company tied that governance to a $100 million cost-savings program in its fiscal 2027 outlook, driven by AI-based process improvements and automation.
The reaction I expect from a lot of small and mid-size distributors: that’s Sysco. $84 billion in sales, 333 distribution centers, 75,000 employees. Of course they can stand up a board committee. We can barely get our team to agree on which chatbot to use.
I understand the instinct. I’ve run operations where every initiative fought for the same three people’s time. The instinct is still wrong, and it’s the kind of wrong that costs you two years you won’t get back.
The lesson from Sysco isn’t the dollar figure. It’s the decision to treat AI as an operating strategy with an owner and a cadence, instead of a pile of disconnected projects nobody is accountable for. That decision has nothing to do with your revenue. A $60 million distributor can make it on a Tuesday. Most won’t because they’re waiting for permission, they think only scale provides.
Where Most Distributors Get Stuck
When they finally decide to put someone in charge of AI, they hand it to IT. It feels natural. AI is technology, IT owns technology, done.
That’s backwards.
I’ve spent the last two and a half years working to understand how AI can impact distribution, and I’ve looked at all of it through the lens of someone who spent years in the trenches. Here’s what that time convinced me of. The people who understand the business are the ones who must guide the strategy. The IT people are the ones who help execute it. Get that order wrong and the whole effort tilts toward what’s technically interesting instead of what moves the operation.
I love IT. The good ones are remarkable at making systems talk to each other and keeping the whole operation running. That’s exactly the problem. They’re busy keeping the business operational. AI adoption is not a systems integration job first. It’s a set of decisions about how work gets done at the field level, where customer interactions happen. Which processes change. What you stop doing. Where the savings land.
The tools themselves are amazing. That’s not in question. But a tool without context fails to hit the objective. Your IT leader can tell you whether an AI tool connects to your ERP. Your IT leader cannot tell you whether rewriting your quote-to-order flow is worth the disruption to your counter team, because that call requires knowing what happens when a customer calls in a rush order and the rep must make a judgment. That’s business knowledge. It lives in the people who’ve worked the field, not the server room.
What Two and a Half Years Taught Me
When I started digging into AI for distribution, I assumed the hard part would be the technology. It isn’t. The technology works. The hard part is knowing where to point it, and that judgment doesn’t come from a demo.
Watch what happens when a distributor buys a capable AI tool and hands the rollout to someone without operational depth. The tool gets configured to do what the vendor’s example showed, not what the business needs. It answers questions nobody was asking. It automates a step that wasn’t the bottleneck. Six months later the honest verdict is that it technically works and nobody uses it.
Now watch the same tool in the hands of someone who’s run a branch. They know the rush order is where margin leaks. They know the counter rep’s judgment call is the moment that keeps or loses the account. They point the tool at that moment, shape it around how the work really flows, and the thing starts paying for itself. Same software. Completely different result. The difference is entirely the context of the person guiding it.
That’s the pattern I’ve seen again these two and a half years. The tool is rarely the variable that decides success. The person deciding how it fits the business is.
Why the Grainger Model Matters More Now
This is where the Grainger differential investment model matters more than ever. Put an upcoming leader from the business on AI. Someone who understands how the company operates, who’s watched customer interactions go right and wrong, who can look at a tool and see where it fits in the actual flow of the work. That person guides the strategy. IT helps them execute it. Run it in that order and you’ll succeed where a technology-led project stalls, because the context the tool can’t supply on its own is sitting in the driver’s seat.
There’s a moment from Grainger that makes this concrete. When the company wanted to understand how our sister operation Acklands-Grainger ran itself as a business, we didn’t send executives to study it from thirty thousand feet. We didn’t send IT. We assigned a group of people who understood how the operations worked and how sales happened. That’s what made the difference. They could see the real mechanics, not the org chart version, because they’d lived the same work themselves.
That’s the same call you’re making with AI. The person who understands the operation sees where a tool fits and where it breaks. Send the wrong person to figure it out and you get a report that reads well and changes nothing.
Sysco understood this. They didn’t route AI to the CIO and walk away. They put it in front of directors and tied it to operating targets. They made it a business job with business accountability.
The Objections I Hear, and What I Tell People
Two pushbacks come up every time I make this argument. Both deserve a straight answer.
The first comes from IT leaders, and some of it is fair. Plenty of IT leaders are business-fluent. They’ve sat with sales, they understand the customer, they’d run this well. If that describes your IT leader, then you already have the person. My point isn’t that the title says IT. It’s that the person needs deep business context, wherever they sit on the org chart. What you can’t do is default the job to IT because AI has the word technology attached to it. Default assignment is the failure. Deliberate assignment to the right person is the win.
The second comes from smaller distributors. You may not have a spare general manager to reassign. I get it. You’re running lean and everyone already carries a full load. But this isn’t a full-time job at your size. It’s one person, a few hours a week, and a standing monthly meeting with you. If you can’t free up that much for the single technology shift most likely to reshape your cost structure this decade, that’s worth sitting with. The distributors who find the hours now are the ones who won’t be scrambling to catch up in two years.
What the Owner Actually Does
Naming an owner isn’t the finish line. It’s the start. Here’s what the role looks like in practice, so this doesn’t become another title with no teeth.
In the first 90 days, the owner does three things. They map where AI could move a number in your business, not where it looks impressive, but where it touches revenue, cost, or a customer experience that’s costing you. They run one or two focused pilots against those spots, small enough to move fast, real enough to matter. And they set up how you’ll know it worked, in dollars or hours or retained accounts, before the pilot starts, not after.
From there, the monthly meeting carries the weight. Every month the owner reports three things to you: what changed, what it saved or earned, and what’s next. If a pilot isn’t working, it gets killed or fixed, not quietly carried. If one is working, it gets resources to scale. IT sits in that conversation as the execution partner, building the integrations and keeping it stable, working against a direction the business has already set.
That’s the whole structure. An owner with business context, a concise list of high-value targets, honest measurement, and a monthly meeting where decisions get made. It isn’t complicated. It’s just disciplined, and discipline is the part most distributors skip.
What Changes Monday Morning
Here’s what I’d tell any distributor who isn’t Sysco. Name one person from the business who owns AI. Not a committee. Not IT by default. A general manager, an operations VP, a rising leader who understands your customers and carries a number. Give them a standing monthly meeting with you where they report what changed, what it saved, and what’s next. Let IT execute against that direction. That’s the whole governance structure. It costs you nothing but the discipline to hold the meeting.
The distributors who install that ownership now will spend the next two years compounding real operational gains. The ones who park AI in the IT backlog will spend those same two years running disconnected experiments that never add up to anything.
Sysco showed you the play. The barrier to running it isn’t your size. It’s whether you’re willing to name an owner from the business and hold the meeting.
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