Introduction: Software Investment Matters—But the Game Just Changed 

Let’s be clear: software investment in distribution has always been critical. A good warehouse management system (WMS) can transform warehouse efficiency. The right pricing engine can recover margin points you didn’t know you were leaving on the table. Enterprise resource planning (ERP) systems that work create operational leverage that directly impacts your bottom line. 

These investments matter because they compound—better systems create better data, which enables better decisions, which drives better results. Every successful distributor knows this. 

But here’s what’s different about AI: it’s not just another software category you can evaluate and deploy using your existing playbook. 

As we head into the final weeks of 2025 and look toward 2026, the pressure to adopt AI is universal and unrelenting. Manufacturers are demanding it. Customers expect it. Competitors claim they’re doing it. I’ve written extensively about this—articles, LinkedIn posts, blogs—all emphasizing the critical importance of AI adoption for distributors.  

But here’s what I’m seeing across the industry as distributors plan for next year: the typical response is to treat AI like every other technology purchase—add a line item to the 2026 budget, assign it to IT, maybe hire a consultant, and wait for the transformation to happen. 

This is exactly how distributors end up with expensive shelfware and nothing to show for it. 

Sure, AI can technically plug into your existing systems—the APIs work; the integrations are possible, the software will run. Every software company we work with all say the same thing: the software is the easy part. But that’s not where the challenge lies. What needs to change is your fundamental thought process about how your company creates value. Real transformation doesn’t come from adding AI tools to your current processes. It comes from making uncomfortable strategic choices that most distributor leaders would rather avoid. 

As you’re building your strategic plan for 2026, here are four hard truths that separate distributors who genuinely transform from those who just check the “AI strategy” box.

1. AI Funding Comes from Reallocation, Not New Budget Lines 

The instinct is always the same: “Show me the ROI, and I’ll find the money.” But a genuine AI strategy doesn’t start with finding more money—it starts with ruthlessly reallocating what you already spend. Before you can figure out what to cut, though, you need to answer a question most distributors can’t clearly articulate: 

“How does my company actually make money?” 

You can describe what you do—buy from manufacturers, stock inventory, deliver to customers, and provide technical expertise. But can you map the actual value creation mechanics? Where is your leverage? Is it in procurement scale, inventory turns, delivery density, technical problem-solving, vendor consolidation for customers? Which operational signals drive profitable decisions versus which ones are just noise you’ve been tracking for decades? 

Until you model your business this way, you can’t answer the second critical question: “What are we going to stop investing in so we can fund our future?” 

This subtraction mindset applies to far more than budget dollars. It requires conscious reallocation of your most constrained resources: leadership attention, your best people’s time, and organizational focus. If you’re serious about AI becoming core to how you operate, something else must become less of a priority. 

If nothing gets cut, nothing meaningful changes. 

I have a sign on my wall in my office that says, “To do more and be better, it’s going to require a different you.” I believe this is the same for distribution companies. For leaders conditioned to chase growth through addition—more branches, more SKUs, more salespeople—this subtraction principle feels  wrong. But refusing to make these tradeoffs is what will move AI initiatives past pilot projects and PowerPoint decks.

2. You Must Trade This Year’s EBITDA for the Next Decade’s Market Position

Building an AI-capable distribution organization isn’t about buying a few software licenses. It requires fundamentally reskilling your workforce—from counter sales to branch managers to your buying team. To win, you need to free up 20% of your people’s time specifically to learn, experiment, and apply AI to their real daily work. 

This will certainly cause a short-term productivity hit. It requires standing in front of your ownership group or PE sponsors and making a declaration that goes against every instinct in distribution: 

“We’re taking a margin hit this year because we’re investing in becoming AI-native. Expect flat growth while we build capability that will dominate our market for the next decade.” 

I’ve seen this kind of bold workforce investment work firsthand. At Grainger, they had something called “differential investment”—you’d be assigned to work on something completely outside your current role, something strategically important to the business that would stretch your capabilities. You weren’t just learning in a classroom or watching training videos. You were solving real problems that mattered to the company while simultaneously developing skills you’d never have gained in your day job. 

That dual return is exactly what AI transformation requires: people learning by doing actual work that moves the business forward, not theoretical exercises that disappear when they get back to their desk. 

Trying to do this transformation with half-measures is actually more dangerous than doing nothing. You create “confident amateurs”—people who know just enough about AI to automate bad decisions at scale, or who think ChatGPT is a strategy. 

The alternative is full commitment: accept the short-term EBITDA dip for the long-term payoff of a deeply capable, AI-enabled team that can deliver customer value your competitors literally cannot match.

3. Stop “AI-ingUp” Distribution Processes You Should Be Eliminating

The difference between incremental improvements and genuine breakthroughs comes down to one mental shift: separate the goal from the current process. 

Distributors constantly describe their work in terms of how it’s always been done: “We forecast demand by analyzing last year’s sales and adjusting for known project activity.” That’s the process. The actual goal is: “Reliably predict what customers will need, so we stock the right inventory in the right locations.” 

When you abstract to the goal level, everything opens. You can completely rethink what data inputs actually matter (maybe customer payment patterns are more predictive than sales history), how the work gets structured (maybe AI agents monitor real-time market signals instead of monthly spreadsheet reviews), and what humans versus machines should handle. 

It’s the key to unlocking transformative opportunities (workflows you couldn’t run before) instead of settling for incremental ones (making old workflows slightly faster). 

You stop wasting time “AI-ing up” a process you should have killed. 

This forces the uncomfortable question: What would we build if we started this distribution business from scratch today? It prevents you from optimizing obsolete workflows and points you toward genuine operational innovation.

4. Short-Term Thinking in Distribution Is Just Managing Your Decline

In wholesale distribution’s AI era, there are two types of leaders: the “Quarterly Distributor” and the “5-Year Distributor.” 

The Quarterly Distributor waits until an AI strategy is proven, safe, and already adopted by competitors. But by the time an approach is obvious in distribution, you’re already behind. The early movers have already locked in the talent, built the institutional knowledge, and established the customer expectations you’re now scrambling to match. 

Real leadership means investing before there’s certainty and tolerating the short-term discomfort that comes with it. 

Look, I got it. This is a difficult position to take. I understand the quarterly pressures you’re facing—the board meetings, the owner’s expectations, the need to make your numbers. Those pressures are real, and they’re relentless. 

Here’s the fundamental problem: wrapping AI around a flawed process doesn’t fix the process—it just automates the inefficiency at scale. 

 If you need every AI investment to pay back in a quarter, you’re not leading a transformation—you’re managing a decline. 

 Conclusion: What Are You Willing to Give Up? 

Software investment has always mattered in distribution—the right systems create competitive advantage that compounds over time. But AI isn’t just another software purchase you can plug into your existing strategy. It demands a fundamentally different approach. 

A successful AI transformation in wholesale distribution isn’t about the technology. It’s about leadership’s willingness to make difficult strategic choices. It means having the discipline to redesign your companies’ work from the ground up. 

As you plan your distributor’s future for 2026 and beyond, the most important question isn’t what AI tools you’ll add—it’s what you’ll subtract. 

So, ask yourself: What are you willing to give up today to own your market for the next five years?