Descriptions:
NLW—CEO of AI planning platform Superintelligent and host of the AI Daily Brief podcast—shares the first public analysis of a proprietary study collecting self-reported ROI data from over 1,000 organizations across more than 2,500 AI use cases. The talk, delivered at the AI Engineer conference, combines macro industry data with these ground-level findings to give one of the more data-grounded pictures of where enterprise AI adoption actually stands.
Key third-party figures cited include KPMG’s quarterly pulse survey, which found that full-production agent deployment among companies with over $1 billion in revenue jumped from 11% in Q1 2024 to 42% by Q3—faster movement through the pilot phase than most predicted. McKinsey’s State of AI study is also referenced, showing only 7% of organizations consider themselves fully at scale. On the outlook side, a separate KPMG CEO survey found that expectations of ROI within one to three years surged from 20% to 67% year over year.
The Superintelligent study breaks reported impact into eight categories: time savings, output volume, quality, new capabilities, decision-making improvement, cost reduction, revenue growth, and risk reduction. Early results show 44.3% of respondents reporting modest ROI and 37.6% reporting high ROI. NLW explicitly acknowledges the self-selection bias—respondents are an engaged podcast audience—but argues the data still offers useful directional signal at a moment when traditional ROI measurement frameworks are struggling to keep pace with AI’s actual impact patterns.
📺 Source: AI Engineer · Published December 18, 2025
🏷️ Format: Deep Dive
