Research & practice
Human–AI Work
What becomes valuable when intelligent systems can participate in planning, analysis, production and execution?
Adaptive expertise
As AI absorbs more routine cognitive production, job readiness becomes less about reproducing standard procedures and more about framing unfamiliar problems, evaluating evidence, handling exceptions and adapting knowledge to changing contexts.
From tools to work systems
The unit of analysis should not be the model alone. Performance emerges from the whole human–AI work system: task allocation, interfaces, incentives, escalation paths, accountability, skills and organisational routines.
AI adoption vs AI advantage
Access to similar models is increasingly commoditised. Sustainable advantage therefore shifts toward complementary organisational capabilities: work redesign, domain expertise, data and process quality, managerial judgement and the ability to integrate human and machine strengths.
Current questions
- Which human capabilities become more valuable as agentic AI becomes more autonomous?
- How should roles be redesigned around exception handling, judgement and accountability?
- When does AI augment cognition, and when does it erode capability through over-reliance?
- How should organisations evaluate AI systems when performance is jointly produced by humans and machines?