ISO 42001 Annex A.3.2: Allocate AI Roles Across the Lifecycle

What control A.3.2 requires in practice

Control A.3.2 asks the organisation to define roles and responsibilities for AI and to allocate them in line with its own needs. The wording is deliberately open: it does not name a role such as a chief AI officer, and it does not prescribe a committee. What it expects is that the work AI creates has owners, and that the owners know what they are answerable for. Three outputs matter in practice. First, a defined set of responsibilities that covers the activities the organisation actually performs with AI. Second, an allocation of those responsibilities to identifiable people or functions. Third, a level of detail sufficient for those people to do their duties. Annex B, which is guidance, lists areas that may need an owner, among them risk, impact assessment, security, privacy, human oversight, supplier relationships and data quality. The organisation decides which areas apply and how to prioritise them, using its policy, objectives and identified risks.

Allocate the work across the lifecycle

Annex B.3.2 connects role allocation with policy, objectives and identified risks. It highlights coverage across activities such as assessment, resources, oversight, development and data quality. Organisations must consider the guidance under clause 6.1.3(e), but its example roles do not mandate an identical department structure.

As an original method, follow a system from proposal through use and eventual transfer or retirement. Identify which responsibility changes hands and what information the next person receives. Ownership gaps often appear at these transitions rather than within a specialist team's normal work.

Why AI role allocation matters to the business

Most AI failures that reach customers involve a task that several teams assumed someone else held. A model is updated, a supplier changes terms, an output is relied on in a new way, and each team sees only its own piece. Allocated roles turn those moments into decisions with a name attached. The commercial benefit is practical: fewer delays while people work out who may approve a change, faster response when something goes wrong, and a credible reply when a client or regulator asks who is accountable. It also protects people. Staff who know the limits of their authority are more likely to escalate in good time. For organisations that both build and operate AI, clear roles also prevent a developer's assumptions from silently becoming an operator's problem.

How to implement control A.3.2

One workable approach is to start from decisions rather than job titles, then check the result against the areas Annex B suggests.

1. List the AI activities your organisation actually performs, such as building, configuring, buying, operating or retiring a system.
2. Under each activity, note the decisions that carry consequences, for example accepting a use case, approving release or responding to an adverse effect.
3. Compare that list with your AI policy, objectives and risk findings to see whether any area has no owner.
4. Assign each responsibility to a named role, and say what that role can approve, who it must consult and who carries out the outcome.
5. Describe responsibilities at the level the post-holder needs, avoiding long job descriptions nobody reads.
6. Trace one system from proposal to retirement and check what passes between owners at each hand-over.
7. Revisit allocations when systems, suppliers or the organisation's role in AI change, and keep the reasons for the current allocation.

Illustrative manufacturing example: data quality has no continuing owner

Illustrative software example: oversight is split between teams

A software provider sells an AI recommendation feature. Product design specifies a human review concept, customer support explains the feature and the customer controls who reviews outputs. No internal role checks whether the supplied information makes that review feasible.

The provider assigns responsibility for the information it supplies and for understanding the boundary between its role and the customer's. It does not claim to control every customer decision. Instead, the allocation makes its own duties and the interface explicit, including how concerns return from users.

Describe duties at a usable level

A role description should enable the person to perform the duty. “Responsible for ethical AI” is too broad to tell someone which evidence to obtain or which decision to escalate. Explain the relevant activity, expected output, authority and interfaces in a proportionate way.

One person can hold several roles where suitable. Different stages may require different expertise, including technical, domain and affected-party understanding. Avoid assigning a specialist task solely because someone is available or has the most senior title.

Connect accountability with practical capability

Responsibilities need resources, competence and access to information. An oversight role without time to review, or an assessor unable to obtain supplier evidence, may be unable to fulfil the intended purpose. Connect allocation with human resources and clause 7.2 competence.

Decide how roles remain covered during absence or staff change. A handover should preserve the relevant conditions and unresolved issues, not just account access. In global teams, consider where local knowledge is essential and which decisions need central authority.

Evidence and common mistakes