The next phase of enterprise AI is a structure, not a model.
In The AI assembly line, McKinsey argues that the next phase of enterprise AI is not a better model but the structure that puts models to work: “an agentic orchestration layer where data, models, and agents interact seamlessly.” The layer, in their framing, is the conveyor belt — it moves the flow of tasks, decisions, and data through the organization so that intelligence becomes throughput instead of a demo. McKinsey & Company, The AI assembly line: Strategic imperatives for CEOs (May 2026)
The thesis is right, and it is now the consensus a CEO or CIO will carry into the room. The harder question is the one the article raises but does not answer for any specific industry: what does that layer have to be before a regulated business can actually run on it?
Efficiency is not enough to put a carrier into production.
A life or health carrier cannot deploy an orchestration layer on efficiency alone. A regulator can ask, three years later, to reconstruct exactly why a decision was made — against the rules, forms, and model versions that were live that day. A Chief Risk Officer will not sign off on a system without a single control that halts every agent at once. A Chief Underwriting Officer needs humans in the loop on specific decisions, and only those. And the data the models read is PHI and PII that, in many cases, is not allowed to leave the carrier’s boundary at all.
None of that is exotic. It is the baseline for insurance, healthcare, and banking. But it is exactly the part a generic orchestration layer treats as someone else’s problem. The conveyor belt is assumed; the governance around it is left as an exercise for the buyer. McKinsey even names the data constraint directly — anonymizing data before it reaches the model is on their list of enterprise requirements. For a carrier, that is not a tuning option. It is a condition of deployment.
Regisseur is the orchestration layer with the governance compiled in.
Regisseur is the agentic orchestration layer built for that reality. The same conveyor belt — process, tools, agents, and integrations as configurable primitives — with the governance compiled in rather than bolted on: an append-only audit trail that replays any decision against the rules that were live, autonomy ceilings an agent cannot exceed, explicit human review gates, and a workspace-wide emergency brake. It runs on-prem or air-gapped, against the carrier’s own model keys, with PHI masked before it ever reaches a model.
This is the hybrid McKinsey describes as the goal: “This hybrid model ensures efficiency while preserving accountability and trust.” McKinsey, “The AI assembly line” (May 2026) The difference is that, for a regulated carrier, accountability and trust are not the trade you make against efficiency — they are the reason the layer is allowed to exist at all.
And because the carrier owns the configuration and runs it in their own boundary, the orchestration layer is an asset they hold, not a feature they rent.