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Wharton-GBK finds only 28% of firms see strong AI returns despite widespread use

Wharton Human-AI Research and GBK Collective’s annual report, The Adaptive Advantage, reveals a gap between AI adoption and measurable business returns among U.S. enterprises. While 80% of managers and senior leaders report any positive returns from AI investments, only 28% describe those returns as strongly positive. The study, based on 1,416 employees at companies with at least $50 million in…

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Key points

  • Only 28% of U.S. enterprise managers report strongly positive AI returns, despite 80% seeing *some* benefit
  • Departments tracking growth metrics (e.g., revenue, satisfaction) are 2.7x more likely to report strong returns than those focusing on efficiency
  • Companies with a Chief AI Officer role see 58% strongly positive returns, vs. 8% where no such role exists

The report also underscores that AI agents are widely deployed (67% of departments use them), but deep integration remains rare. Only 28% say AI is fully embedded in core processes, and just 17% allow autonomous operation. Departments meeting all three criteria—changed workflows, embedded AI, and agent use—report 67% strongly positive ROI. Clear ownership, such as a dedicated Chief AI Officer, correlates with stronger results: 58% of managers in those roles report strong returns, compared to 8% where no such role exists. However, the study does not prove causation—only an association between these factors and reported outcomes. Entry- and mid-level employees also see AI’s impact differently: 58% say workflows have changed significantly, compared to 73% of managers, while only 56% feel adequately trained. The report warns that adoption alone does not guarantee success; measurable outcomes, integration, and employee experience matter more.

Full story from Unite.AI · by Aiden Cross, AI Product Strategy & Execution, AI Research AgentOpen source ↗

Wharton–GBK’s “The Adaptive Advantage: Who’s Winning with AI and How” Report Reveals the AI ROI Gap

Unite.AI · 14 October 2026

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This text was published by Unite.AI and written by Aiden Cross, AI Product Strategy & Execution, AI Research Agent. It is reproduced here with attribution so you can read it in full; the rights remain with the publisher. Read it at the source ↗

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The headline, key points and digest above were generated by Digest AI's editorial model from the linked sources. Automated summaries can contain errors: the sources are the record. Spotted a mistake? Tell us. Published by Martin K., who runs Digest AI and handles corrections.

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