In 1975, the first digital camera was invented at Kodak. By 1996, Kodak commanded a $28 billion market cap with 140,000 employees. By 2012, they were bankrupt. The story isn’t about technology — it’s about seeing the future clearly and acting decisively.

Today, wholesale distribution stands at a similar inflection point. However, unlike Kodak, this isn’t about a single technology disrupting one product line. This is about artificial intelligence (AI) fundamentally transforming your cost structure. The winners will operate at 40% lower commercial process costs while delivering materially higher service levels. The losers will find themselves in a cost structure trap from which there is no escape.

This isn’t speculation about some distant future. Morgan Stanley recently estimated that generative AI alone will drive $4.1 trillion in annual labor cost savings by 2027 (https://mgstn.ly/40QdofO). Private equity firms are already building AI-native distribution platforms designed to operate firms at significantly lower cost basis. While many distributors are still debating whether to invest in basic automation, the technology to transform commercial processes has already arrived.

Consider a typical sales support function today. Your team manually researches customer histories, prepares quotes, checks inventory availability and validates pricing — spending hours on tasks that AI can complete in seconds. This isn’t only inefficient; it’s strategically dangerous. Every hour your team spends on these tasks is an hour they’re not spending on actual selling. More importantly, it’s creating a cost structure that will soon be uncompetitive.

The hidden tax: Your commercial processes are bleeding value

The true cost of your commercial processes isn’t visible on your P&L. It’s hidden in what technologists call “accidental middleware” — humans acting as the connective tissue between systems, manually transferring and translating information that should flow automatically.

Look at your product managers spending days maintaining cross-references between supplier catalogs. Watch your customer service team toggle between screens, transcribing information from one system to another. Observe your sales reps manually researching customer histories before each call. This isn’t value creation — it’s systemic inefficiency masquerading as necessary work.

The cost is staggering. A typical mid-sized distributor has 30% to 40% of its commercial workforce acting as human middleware. At an average fully-loaded cost of $75,000 per employee, a distributor with $500 million in revenue is likely spending $4 million to $5 million annually on what are essentially human data transfer mechanisms. This doesn’t include the opportunity cost of what these employees could be doing instead, or the error rates inherent in manual processes.

However, here’s what should keep you up at night: This cost structure is about to become optional. AI agents can now handle these data translation and transfer tasks at scale, with higher accuracy and at a fraction of the cost. Early adopters are already deploying these systems, creating an expanding cost advantage that will become increasingly difficult to overcome.

Consider the implications. If your competitor reduces its commercial process costs by 25% while simultaneously improving accuracy and speed, how long can you remain competitive? How will you justify a cost structure propped up by human middleware when AI agents can handle the same tasks for pennies on the dollar?

Intelligence at scale: The economics of AI-enabled commerce

What’s coming isn’t automation — it’s intelligence at scale. AI agents aren’t software tools; they’re digital employees working 24/7, don’t make mistakes and cost a fraction of their human counterparts. More importantly, they’re about to reshape the fundamental economics of distribution.

Consider what happens when a quote request (RFQ) arrives at a typical distributor today. A sales rep reviews it, checks multiple supplier catalogs, validates pricing, confirms availability, formats the response and follows up with the customer. Best case: hours of work. Typical case: days of delay. This process, multiplied across thousands of interactions, creates your current cost structure.

Now imagine this: An AI agent receives the RFQ, instantly matches requirements across your entire supplier network, validates pricing and availability in real-time, generates an optimized quote and responds to the customer — all in seconds. The sales rep? He’s notified only if his judgment is actually needed, perhaps on complex customizations or strategic pricing decisions. This isn’t science fiction — it’s happening now in forward-thinking distributors.

Here’s the crucial insight: These agents aren’t only faster; they’re transformative. They don’t reduce costs; they create capabilities that are impossible with human-centric processes. An AI agent can simultaneously:

 Monitor every customer’s buying patterns for opportunities;

Track competitor pricing across thousands of SKUs;

Optimize inventory levels across your network;

Generate personalized promotions for each customer;

Predict and prevent customer churn.

This creates what technologists call an “intelligence gap” — a fundamental competitive advantage that can’t be overcome through incremental improvement. When your competitor can process thousands of customer interactions simultaneously while your team is manually handling them one at a time, no amount of human effort can close that gap.

The economics are brutally straightforward. Early pilots we’ve observed show:

85% reduction in quote processing time;

15% increase in quote conversion rates;

200-300 basis point margin improvement through dynamic pricing;

60% reduction in average customer service response times;

90% decrease in data entry and validation costs.This isn’t about replacing humans; it’s about liberating them. When AI agents handle the mechanical aspects of commercial processes, your team can focus on what humans do best: building relationships, solving complex problems and creating strategic value. The result is an organization operating at a fundamentally lower cost basis while delivering materially higher service levels.

Seizing the advantage: Your 24-month window for action

The window for gaining competitive advantage through AI is closing rapidly. By 2027, Morgan Stanley estimates AI will drive $4.1 trillion in annual labor cost savings. However, that number masks a crucial truth: The benefits won’t be distributed evenly. Early adopters will capture disproportionate value, while laggards will face an increasingly impossible game of catch-up.

The path forward isn’t mysterious, but it demands urgency and precision. Here’s your execution framework:

1. Map your attack surface 

Don’t start with AI, start with inefficiency. Examine commercial processes where humans are:

Transferring data between systems;

Making repetitive decisions;

Monitoring routine activities;

Responding to standard queries.

This isn’t a casual exercise. A rigorous process mapping will reveal that 30% to 40% of your commercial workforce is engaged in activities that AI can handle more effectively. That’s not only a cost reduction opportunity — it’s also a strategic vulnerability.

2. Reconstruct your commercial architecture 

Your current processes were designed around human limitations: the speed at which people can process information, the number of options they can evaluate and the volume of data they can analyze. AI removes these constraints. This means you’re not only automating existing processes; you’re reimagining them entirely.

Start with high-impact, low-complexity processes where success is easily measured:

RFQ response automation;

Customer service inquiry handling;

Product data management;

Pricing optimization.

However, move quickly. We’re seeing early adopters achieve full deployment in these areas within six to nine months, creating immediate cost advantages.

3. Build your intelligence infrastructure 

This transformation requires new capabilities. You need:

Teams that understand how to deploy and manage AI systems;

Processes designed for human-AI collaboration;

Data infrastructure that can support AI operations;

Metrics that capture the full value of intelligent automation.

Don’t build this alone. The market is already rich with vendors and advisors who have solved these problems. Use them. The goal isn’t to become an AI company; it’s to use AI to become a more effective distributor.

4. Create your timing advantage 

The economics of AI adoption follow a simple rule: The earlier you start, the greater your advantage. This isn’t only about cost reduction — it’s about data accumulation, learning effects and organizational capability building. Every month of delay is a month your competitors are potentially building their lead.

The competitive imperative

The distribution industry is entering a period of fundamental restructuring. The winners will be those who move decisively to transform their commercial processes through AI. The cost advantages they create — 25% lower operating costs, materially higher service levels, faster market response — will become increasingly difficult to overcome.

This isn’t another technology initiative. It’s a fundamental reimagining of how distribution businesses operate. The question isn’t whether to make this transition — it’s whether you’ll be leading it or following.

Your competitors are already moving. Private equity firms are building AI-native distribution platforms. Tech-forward distributors are deploying AI agents across their commercial processes. The time for careful observation is over. The time for decisive action is now.  

A veteran in the tech industry working with wholesale distributors across multiple verticals, Brooks Hamilton held pivotal roles in professional services and product management at Zilliant, including vice president of the professional services team. His tenure was marked by ground-breaking work in AI-driven price optimization and sales effectiveness in B2B companies. Passionate about the transformative impact of AI, he is a sought-after speaker and thought leader on adopting AI and pricing best practices. You can reach him at brooks.hamilton@strategyadvisors.ai.