Harvard Business Review LogoJuly 27, 2026Jorg Greuel/Getty ImagesAI is making data analysis faster and more accessible, but it can also amplify flawed reasoning by producing more answers to the wrong questions. Organizations can avoid that trap by buildingMost companies are building AI analytics as an access problem: How do we let more people ask more questions of more data? But that’s the wrong starting point. The better question is: How do we help people make better decisions with the answers they receive?
Don’t Let AI Make Bad Analytics Worse
AI is making data analysis faster and more accessible, but it can also amplify flawed reasoning by producing more answers to the wrong questions. Organizations can avoid that trap by building “decision discipline”: starting with the decision they need to make, distinguishing between descriptive, predictive, and causal questions, making assumptions explicit, governing metrics consistently, validating high-stakes analyses, and rewarding truth-seeking over confirmation. Companies that use AI to improve the quality of decisions—not just the speed of analysis—will be better positioned to turn abundant data into sound judgment.
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