Research & academic work

Knowledge workers now have access to artificial intelligence tools that can draft, summarise, search, analyse and even write code. Whether these tools actually make knowledge work more productive is one of the defining questions of the current decade. This paper reviews the evidence on AI and knowledge worker productivity and argues that the tools are real but the gains are conditional. Randomised experiments and field studies show substantial average productivity gains, from about 14 per cent for customer support agents to roughly 40 per cent time savings on professional writing tasks, yet the same studies reveal striking variation between people, tasks and skill levels. Survey data show that adoption is widespread but that few organisations have captured bottom-line value, and the risks, from hallucination and overtrust to deskilling and weak data foundations, are as documented as the benefits. The paper argues that AI does not replace knowledge management; it depends on it. Lasting productivity gains come when capable tools meet well-managed knowledge, clean data, redesigned workflows and people who are trained, trusted and supported. The paper reviews the modern landscape of AI tools for knowledge work, synthesises the experimental and survey evidence, examines failure modes, and proposes a practical framework for measuring knowledge worker productivity and for introducing AI in ways that produce gains that last.