How should AI decision rights be allocated?

By naming the roles separately, the way any decision has always had to be allocated. Who recommends. Who supplies input. Who has to agree. Who decides. Who executes.

AI can now perform parts of several of those. It cannot hold the decide role, because deciding carries answerability, and a system cannot be answerable. So the structure of the exercise is unchanged and the occupants of the boxes have moved.

Separating the work from the right

The confusion this question usually contains is between doing the work of deciding and holding the right to decide. They were always different, and they were easy to conflate while the same person did both.

Gathering the evidence, weighing the options and drafting the recommendation is work. It can be delegated, to a junior, to a supplier, or now to a system. The right to decide is a position in an accountability structure, and delegating the work has never transferred it.

Which makes the AI-specific part narrower than it looks. Most of what these systems do is input and recommendation, and organisations have been allocating those roles to other parties for as long as organisations have existed.

The allocation that goes unmade

The practical failure is not a wrong allocation but an absent one.

For each decision the organisation should be able to state whether the system recommends, decides within stated limits, or executes, and what those limits are. In most deployments none of this is written down. The system produces an output, the output is accepted, and the decide role has been given away by default rather than by choice.

Nobody made that decision, which is the whole problem: an allocation arrived at through drift cannot be reviewed, because there is no record of it having been made.

This estate treats the mapping exercise itself at the delegation boundary map, and the point that the resulting artefact is a record of decisions rather than a policy document applies here too.

What the regulation already allocates

The EU AI Act distinguishes the provider, who develops a system and places it on the market, from the deployer, who uses it under their own authority, and places obligations on both. Graded entry.

That distinction does real work, because it forecloses the most convenient answer. An organisation using a system cannot locate responsibility entirely with whoever built it. Using it under your authority is what makes you a deployer, and deployer obligations attach to that.

Article 14 then says what the person given oversight must be enabled to do, which is a decision-rights allocation written as a design requirement: they must be able to disregard, override or reverse the output, and to stop the system.

Accountability that is real and accountability that is nominal

Accountability can only attach to a person or an organisation, so the question of who is accountable when AI gets something wrong has a short answer. The useful question is whether that accountability is fair, and often it is not.

Assigning responsibility to someone who could not have evaluated the output produces a name to blame rather than a control. It satisfies an audit and changes nothing about the failure rate, because the person named was never in a position to prevent anything.

The test is the one the regulation uses in its single specific provision: competence, training and authority, together. Any one of the three missing and the accountability is nominal. Treated at length at who can override an AI system and who supervises work they cannot do.

What agents change

Chains of agents complicate the tracing rather than the principle. Whoever deployed the chain deployed it.

What genuinely changes is speed. A mistake can propagate through several steps before any human reviews any of them, which means the allocation cannot be made during operation and has to exist beforehand. An agent architecture without a decided allocation is not an ungoverned decision; it is a governance decision made by omission.

Perrow's coupling argument applies directly. Normal Accidents (1984). Tighter coupling gives less warning between a fault and its consequences, and agents acting on each other's outputs is a description of tight coupling.

What this page does not establish

The five-role framing is a widely used organisational-design convention rather than a validated construct, and several proprietary versions of it exist. It is offered because it is clear, not because a study shows it produces better decisions.

The EU AI Act is binding law and not evidence about outcomes, and its oversight provisions do not apply until December 2027 at the earliest. Nothing here shows that organisations allocating rights explicitly perform better than those that do not.

The fairness argument is a normative position rather than a finding. Someone could reasonably hold that accepting accountability for outputs one cannot fully evaluate is simply what senior roles have always involved, and that view is not refuted by anything on this page.

Key sources

• European Union (2024). Regulation (EU) 2024/1689, Article 14: Human Oversight. Graded entry.
• Perrow, C. (1984). Normal Accidents: Living with High-Risk Technologies. Basic Books. In the essential works.
• Weick, K. E. and Sutcliffe, K. M. (2001). Managing the Unexpected. Jossey-Bass. In the essential works.
• National Institute of Standards and Technology (2023). AI Risk Management Framework Playbook, MANAGE 2.4. Graded entry.

Related SuperSkills research

On mapping the boundary, the delegation boundary map. On the authority to act, who can override an AI system. On agents acting independently, AI agents and human judgement and should I let an agent act on my behalf. On verification ownership, who owns verification. On withdrawing a system, deployment is not a ratchet.

About this research

Rahim Hirji is the author of SuperSkills (Kogan Page, 2026), keynote speaker on AI and human capability, and founder of The SuperSkills Intelligence Company. The separation of decision work from decision rights is standard organisational design and is not a SuperSkills coinage.

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