AI Simulation

Data is the part of AI that refuses to be motivational. A company can buy a larger model, rent more GPUs, and hire a cheerful consultant to say “agentic workflow” three times in a meeting. What it cannot easily buy is the exact operational data its AI needs: rare failures, unsafe edge cases, clean labels, sensitive medical records, multi-agent traffic chaos, robotic mistakes that do not injure anyone, and enough variation to make a deployed system less embarrassingly brittle. ...

A negotiation bot walks into a pricing dispute. That is not the start of a joke. It is the start of a procurement problem, a marketplace design problem, a customer-service escalation problem, and, sooner than executives would like to admit, a governance problem. Once AI systems begin making choices on behalf of organisations, their behaviour in social settings matters. Not just whether they answer correctly. Not just whether they sound polite. Whether they cooperate, defect, compromise, optimise, over-trust, or quietly behave like a very caffeinated economist. ...