GoKawiilEntrepreneur Op-Ed: AI Fails at Companies Because Decision-Making Isn't Fixed First
A contributor argues that enterprise AI pilots often succeed technically but fail to change business outcomes because they operate alongside existing workflows rather than inside them. The piece traces this to fragmented, inconsistent decision-making processes across teams, which limits how much impact any AI system can have once deployed.
GoKawiil's interpretation of the reporting above, not reported fact.
Many companies measure AI success by model accuracy rather than whether it actually reshapes how choices get made, leading to stalled ROI despite heavy investment. The argument suggests that organizational structure and decision ownership, not algorithm quality, are the real bottleneck to AI adoption at scale.
- AI pilots often work in isolation but fail to alter real business decisions.
- Fragmented, inconsistent decision-making across teams undermines AI's potential impact.
- Embedding AI directly into workflows, not as a side analytics layer, is key to scaling it.
Competing in the Age of AI" by Marco Iansiti and Karim Lakhani — This Harvard Business Review Press book tackles exactly the gap the article describes: AI that stalls because operating models and decision workflows never changed. It's a practical read for leaders trying to move AI from side experiments into the core of how the business actually runs.
See Competing in the Age of AI" by Marco Iansiti and Karim Lakhani on Amazon → Affiliate link — we may earn a commission on purchases, at no extra cost to you. Product picked by AI based on this article; it is not a tested recommendation.Source: entrepreneur.com — Bidhan Baruah, 2026-08-28
Published there as: “You Didn’t ‘Fail at AI’ — You Never Fixed the Way You Make Decisions”
Read the original report → The summary and analysis above are GoKawiil's own, written from reporting by the source above. Facts and quotes belong to the original publisher.