Relevant research

Ideas that help us see the work differently.

A curated selection of research that challenges familiar assumptions and opens new questions about human contribution, AI and organizational value.

Featured research · Agentic organizations

The Emerging Agentic Enterprise: How Leaders Must Navigate a New Age of AI

Sam Ransbotham, David Kiron, Shervin Khodabandeh, Sesh Iyer and Amartya Das MIT Sloan Management Review and BCG · November 2025

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Why it matters

Agentic AI does more than automate individual tasks. It can coordinate and act across workflows, changing how decisions, accountability and work itself are organized.

Question it opens

What must change around the technology for agents to create value without weakening human judgment or accountability?

Organizational transformation · Peer-reviewed article

Beyond Computation: Information Technology, Organizational Transformation and Business Performance

Erik Brynjolfsson and Lorin M. Hitt Journal of Economic Perspectives · Fall 2000

Why it matters

Technology creates value through complementary changes in processes, structures and ways of working, not through technical capability alone.

Question it opens

What complementary changes in roles, decisions and organizational structures are required for AI investment to create value?

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Human expertise · Working paper

Applying AI to Rebuild Middle Class Jobs

David Autor NBER Working Paper · February 2024

Why it matters

AI could extend the reach and value of human expertise, but only if organizations choose to use it to widen access to consequential work rather than simply remove labour.

Question it opens

Will organizations use AI to extend human expertise and agency, or primarily to remove labour?

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Systems thinking · Open-access scholarly book

Engineering a Safer World: Systems Thinking Applied to Safety

Nancy G. Leveson MIT Press · 2012

Why it matters

Safety is not simply a property of reliable components. It emerges from the controls, feedback, decisions and interactions across the whole system.

Question it opens

What controls and feedback are needed when risk emerges from interactions across the wider organizational system?

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Machine intelligence · Peer-reviewed article

Building Machines That Learn and Think Like People

Brenden M. Lake, Tomer D. Ullman, Joshua B. Tenenbaum and Samuel J. Gershman Behavioral and Brain Sciences · 2017

Why it matters

High performance does not mean that machines learn, reason or understand as people do. That distinction matters when deciding what AI should be trusted to contribute.

Question it opens

Where might fluent performance be mistaken for understanding, judgment or human-like learning?

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