Agentic Readiness Audit
This case study hangs on one question: which tasks sit inside the capability frontier? That is exactly what the audit answers – prioritised and decidable.
To the auditManagement consulting · 758 consultants · field experiment with a control group
Do employees who use AI deliver better results?
A consulting firm had to decide whether to put AI in the hands of all its people. That it feels faster was clear early on. Whether better work comes out of it, nobody could say. So it was not debated but measured.
GPT-4 from OpenAI for everyone
Employees were given GPT-4 from OpenAI. With it they could gather ideas, write drafts, rephrase, summarise, structure, look for counterarguments and critique texts. Human graders read the results without knowing who had worked with AI and who had not.
Rated over 30% higher, finished over 25% faster.
The gap did not come from the AI doing the work, but from it being in the room from the first minute. The comparison ran against the control group in the same firm, not against an industry average.
The study also shows where the AI's capability frontier sits: on one task deliberately placed beyond it, the answers were less often correct – and more convincingly phrased than the control group's. The error came well packaged. Which is why the audit settles first which tasks belong inside.
This case study hangs on one question: which tasks sit inside the capability frontier? That is exactly what the audit answers – prioritised and decidable.
To the auditCo-creation is a way of working, not an installation. In the training your team learns to work with AI from the blank page on instead of correcting at the end.
To the trainingPeer-reviewed, with a control group. Three people graded the results independently, without knowing who had worked with AI.
Source: Dell’Acqua et al., Harvard Business School / BCG, Organization Science 37(2), 2026, pp. 403–423 (first as HBS Working Paper 24-013, 2023).