· 5 min · Angad Bank

AI Strategy: Why Most Companies Start at the Wrong End

The most common mistakes in AI adoption — and how behavioral science makes the difference.

AI Strategy AIStrategyBehavioral Science

The Problem Isn’t the Technology

When companies talk about AI strategy, they almost always start with the technology. Which tool? Which model? Which vendor?

That’s the wrong starting point.

The real question is: What decisions do people in your organization make poorly today — and how can AI help?

Behavioral Science Is the Key

From my work with founders and innovation teams, I see the same pattern over and over: The technology works, but adoption fails. Why? Because no one considered the human side.

  • Decision fatigue causes teams to ignore AI tools after the initial rollout
  • Confirmation bias leads executives to only accept AI outputs that confirm their existing views
  • Status quo bias prevents established processes from being questioned

A Better Approach

  1. Understand the behavior first — Before implementing an AI solution, map the decision-making processes
  2. Prototype rapidly — Test with real users, not presentations
  3. Measure adoption, not features — The best algorithm is useless if nobody uses it

This article is part of my series on evidence-based AI strategy. Contact me for a free introductory call.