Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of Artificial Intelligence on Knowledge Worker Productivity and Quality
Fabrizio Dell’Acqua, Edward McFowland, Ethan Mollick, Hila Lifshitz‐Assaf, Katherine C. Kellogg, Saran Rajendran, Lisa Krayer, François Candelon, Karim R. Lakhani · Organization Science · 1 Mar 2026
Where this sits in the debate
- Will AI actually boost productivity and growth? · its finding: it depends (why studies differ)
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Abstract
We introduce and study the concept of a “jagged technology frontier” to describe the uneven impact of artificial intelligence (AI) capabilities, where AI assistance improves performance for some tasks but worsens it for others, even within the same knowledge workflow and with a seemingly similar level of difficulty. In collaboration with the global management consulting firm Boston Consulting Group, we have developed realistic management consulting tasks and examined the human performance implications of using AI to perform complex and knowledge-intensive work. The preregistered experiment involved 758 knowledge workers. After establishing a performance baseline on similar tasks, subjects were randomly assigned to one of three conditions: no AI access, GPT-4 AI access, or GPT-4 AI access with a prompt engineering overview. For each one of a set of 18 realistic knowledge tasks within the frontier of AI capabilities ranging from creative to analytical tasks, subjects using AI outperformed those not using AI, completing 12.2% more tasks and completing them 25.1% more quickly on average while also delivering solutions of significantly improved quality. However, for a complex managerial task selected to be outside the frontier, subjects using AI were 19% less likely to produce correct solutions compared with those without AI, pointing to potential limitations of AI supporting knowledge workers. We discuss the positive and negative implications of AI-aided human performance in knowledge-intensive tasks. Funding: Financial support of the Harvard Business School Digital Data Design Institute and Division of Research and Faculty Development is acknowledged. Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2025.21838 .
About this publication
Leading field journal. A leading journal in economics or a neighbouring field (on the Tinbergen Institute’s A list or near the top of the RePEc ranking), or a top-rated computer-science venue.
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- Published
- 2026 (8 months ago)
- Citations
- 221 (OpenAlex)
Citations in context
221 citations — 100th percentile among the 188 indexed papers from 2026 in this collection. Citation counts favor older papers; this compares only same-year papers here, not the whole literature.
Edward McFowland, Ethan Mollick, Karim Lakhani, Katherine Kellogg signed the wemustactnow.ai letter · author affiliation matches seed institutions harvard university, massachusetts institute of technology, university of pennsylvania, university of warwick — part of why this paper is in the collection.
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