An AI strategy written around model features will age quickly. A strategy built around persistent business friction can guide better decisions even as platforms evolve.
Friction is what happens when work waits, gets re-entered, moves without an owner, requires unnecessary approval, or cannot be measured. It is visible in late customer responses, duplicated records, inconsistent reports, and employees inventing workarounds.
Instead of asking every department for an AI wish list, ask them to show you one real transaction. Follow the work from trigger to outcome. Notice where people improvise, correct mistakes, and chase updates. Quantify the time or cost of those moments.
Then ask what type of intervention fits. Clear rules may justify basic automation. Unstructured documents may benefit from AI-assisted extraction. Fragmented customer data may require integration. An unclear responsibility may be solved with a process decision, not software.
Prioritize opportunities with a process owner, dependable data, manageable risk, and a result that can be demonstrated in a focused pilot. That is how an AI strategy becomes an operating plan.
Friction is a starting signal, not the final diagnosis. Understanding the cause is what makes technology useful.
Identify where work slows down, information gets lost, or employees repeat unnecessary tasks.
Examine workflows, responsibilities, and data to determine whether AI, automation, or process redesign is appropriate.
Start with opportunities that have clear ownership, reliable data, manageable risks, and measurable benefits.
Test focused solutions, measure their impact, and expand what delivers sustainable business value.
Next step: Want to identify where this applies in your business?
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