If the first two parts of The Accountability Gap exposed the problem and questioned where decisions should sit, the next challenge is execution: how do firms govern AI without slowing compliance to a crawl?
Most responses have been predictable — more controls, more oversight, more sign-offs. But added governance does not always mean better control. In many cases, it slows decisions, obscures ownership, and creates friction without reducing risk.
Firms are now caught between two pressures: prove control to regulators, and operate at machine speed. This is where the accountability gap becomes operational. The question is no longer whether AI can be governed — but whether it can be governed without breaking the system around it.
In the first part of The Accountability Gap, we looked into the accountability problem and why it hasn’t been solved. In part two, we then discussed with key thought leaders what decisions machines are able to make. In this third part we ask a key question – how can we govern AI without it slowing it down? Read the full article.
