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How AI Helps the Best and Hurts the Rest

Nicholas Otis et al.

MIT Sloan Management Review2026https://doi.org/10.63383/uflh4491article
FT50AJG 3ABDC A
Weight
0.50

What the paper says

Can generative AI serve as an on-demand business adviser? A field experiment with hundreds of small business owners in Kenya found that AI access boosted revenues and profits by 15% for high performers — but caused a nearly 10% decline for those who had already been struggling. The culprit: Weaker performers followed generic or misleading AI advice because they lacked the judgment to filter it out. Leaders deploying AI at scale must design their rollouts carefully to avoid widening performance gaps.

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https://doi.org/https://doi.org/10.63383/uflh4491

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@article{nicholas2026,
  title        = {{How AI Helps the Best and Hurts the Rest}},
  author       = {Nicholas Otis et al.},
  journal      = {MIT Sloan Management Review},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.63383/uflh4491},
}

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How AI Helps the Best and Hurts the Rest

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.