Everywhere you turn right now, someone is talking about Artificial Intelligence. For business leaders, that can create an odd kind of pressure: the feeling that if you are not already “doing AI,” you are somehow behind.

For distributors, the best approach to alleviate that pressure is to start somewhere much simpler.

What business problem are you trying to solve?

That question matters because AI is not a strategy, it is a tool. A very powerful tool in the right situation, but still a tool. And like any technology, its value depends on whether it is being applied to something that actually matters to the business.

Consider where friction exists today. Maybe Customer Service spends too much time searching for information. Perhaps Purchasing is reviewing large amounts of data manually. Maybe Sales is repeating tasks that add little value, or leadership is waiting too long for information needed to make a decision.

Those are business problems. They are also much better starting points than, “Where can we put AI?”.

This is especially important because the market is moving quickly. Recent McKinsey research shows that AI use is becoming widespread, but far fewer companies have successfully scaled it across the business.[1][2] In other words, there is still a very big difference between experimenting with AI and actually creating value from it.

The encouraging part is that you do not have to boil the ocean.

Start with one meaningful problem. Put a value around it. What would improve if the problem went away? Would customer response be faster? Could employees spend more time on higher-value work? Would decisions improve? Could margin, accuracy or cash flow benefit?

Once the outcome is clear, then look at the foundation underneath it. Is the data reliable? Is the process itself sound? Are there security or privacy concerns? Who needs to review the output? These questions are not barriers to AI; they are what allow it to be used responsibly and successfully. NIST’s Generative AI guidance similarly emphasizes governance, measurement and human accountability as part of responsible adoption.[3]

There are amazing AI opportunities for distributors today. There are also situations where a process improvement, integration, better reporting or simple automation is the better answer.

The goal is not to use AI everywhere. The goal is to use the right solution in the right place to create a better business outcome.

The strategy is still profitable growth. AI is simply one more way to help get there.

Additional Resource

For a deeper practical discussion, watch TUG Connects 365 – Acumen Group Presents: Make AI Work For Your Business. It is a useful session for teams thinking about how to move from general AI interest to responsible business use.

Sources

[1] McKinsey & Company, “Where value is won and lost in distribution,” June 9, 2026. Source link

[2] McKinsey & Company, “AI at work but not at scale,” December 10, 2025. Source link

[3] National Institute of Standards and Technology, “Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile,” updated April 8, 2026. Source link