Certified Chief AI Officer (CCAIO).

LO 1.1Formulate an enterprise AI ambition and multi-year transformation roadmap that sequences initiatives against organizational capability, risk appetite and market conditions. Supports CLO1

Assessment criteria:

• Presents a sequenced roadmap in which each initiative carries an owner, a funding decision point and a measurable value hypothesis.
• States the capability, risk-appetite and market assumptions behind the sequencing and identifies the conditions under which each would no longer hold.

LO 1.2Evaluate competing strategic options for AI investment, including build depth, partner reliance and timing, and justify the recommended course to executive peers. Supports CLO1

Assessment criteria:

• Compares at least two viable strategic options for a given investment decision, with the build depth, partner reliance and timing trade-offs of each made explicit.
• Recommends one course of action and defends it to executive peers using evidence from the scenario rather than preference.

LO 1.3Design revision mechanisms that keep the roadmap current as models, regulation and competitive conditions shift. Supports CLO1

Assessment criteria:

• Specifies named triggers, such as a regulatory change or a shift in model capability, that force a formal roadmap review.
• Defines who reviews the roadmap, on what cycle, and what evidence a revision decision must cite.

LO 2.1Evaluate an enterprise AI portfolio against explicit value criteria and direct funding, scaling and retirement decisions accordingly. Supports CLO2

Assessment criteria:

• Ranks a portfolio of AI initiatives against stated value, feasibility and risk criteria and records a fund, fix or stop decision for each.
• Supports each decision with baseline and benefit evidence rather than sponsor narrative.

LO 2.2Design stage-gated governance that ties continued investment to demonstrated benefit. Supports CLO2

Assessment criteria:

• Designs a stage-gate structure in which each gate names the benefit evidence required before further funding is released.
• Specifies the decision rights at each gate, including who may release funds and who may halt an initiative.

LO 2.3Justify the discontinuation of initiatives that fail their value case, and manage the organizational consequences of stopping them. Supports CLO2

Assessment criteria:

• Presents a discontinuation case that separates the evidence of value failure from the sunk cost already incurred.
• Sets out a wind-down plan covering the people, data assets and vendor commitments of the stopped initiative.

LO 3.1Direct the lifecycle of data assets and models from sourcing and contracting through monitoring, renewal and retirement. Supports CLO3

Assessment criteria:

• Maps the lifecycle stages of a given data asset or model and names the decision owner and review trigger at each stage.
• Specifies monitoring and retirement criteria proportionate to the risk of the asset, including the conditions that force early retirement.

LO 3.2Evaluate build, buy and partner options against enterprise standards for quality, security and exit. Supports CLO3

Assessment criteria:

• Compares build, buy and partner options for a given capability using total cost, security posture and exit terms as explicit criteria.
• Identifies concentration and lock-in risk in the recommended option and states how it will be contained.

LO 3.3Formulate vendor governance that holds suppliers to enterprise standards across the AI supply chain. Supports CLO3

Assessment criteria:

• Drafts vendor governance terms covering performance, transparency and audit rights, with defined escalation steps for non-conformance.
• Defines how supplier claims are verified under enterprise conditions before they are relied on.

LO 4.1Design an AI operating model that places capability, roles and decision rights where the work happens. Supports CLO4

Assessment criteria:

• Selects a centralized, federated or hybrid operating model for a given organization and justifies the choice against its structure and capability.
• Allocates roles and decision rights so that named positions, not committees alone, are accountable for AI decisions where the work happens.

LO 4.2Formulate a workforce transition plan that redesigns roles honestly and sustains trust through change. Supports CLO5

Assessment criteria:

• Produces a transition plan that states role impact honestly and pairs each affected role with a reskilling or redeployment pathway.
• Identifies the trust risks in the transition and the specific commitments made to the people affected.

LO 4.3Lead adoption at scale, converting early wins into durable behavioral change. Supports CLO5

Assessment criteria:

• Defines adoption measures covering usage, proficiency and outcome change, with baselines set before rollout.
• Sets out how early wins are converted into standard practice, including changes to incentives and performance expectations.

LO 5.1Justify AI investment, exposure and trade-offs to boards and investment committees in the language of risk, return and accountability. Supports CLO6

Assessment criteria:

• Presents an investment or exposure case in the language of risk, return and accountability, with confidence claims calibrated to the strength of the evidence.
• Answers skeptical questioning on the case with evidence, and concedes the limits of the data where the evidence is weak.

LO 5.2Design a board reporting regime for AI that presents value and risk without hype and survives scrutiny. Supports CLO6

Assessment criteria:

• Designs a recurring board pack covering portfolio position, value realized, incidents and forward risk, linked to the enterprise risk appetite.
• Excludes vanity metrics and states, for each reported figure, its source and the assumption it depends on.

LO 6.1Formulate responsible AI principles and resource them as an operating capability rather than a policy document. Supports CLO7

Assessment criteria:

• Translates each responsible AI principle into a named control, an accountable owner and a budget line.
• Shows that the resourcing matches the stated principles, and records any principle left unfunded as an accepted risk.

LO 6.2Design escalation and incident response arrangements that make it safe to raise AI concerns. Supports CLO7

Assessment criteria:

• Designs an escalation path through which any member of staff can raise an AI concern outside their own reporting line, with defined response times.
• Sets out an incident response sequence for AI harms covering containment, notification, remedy and post-incident review.

LO 6.3Evaluate the organization's responsible AI posture against regulatory obligations and evidence expectations. Supports CLO7

Assessment criteria:

• Assesses the organization's responsible AI arrangements against the obligations of the governance frameworks that apply to it, and records the gaps found.
• Identifies the evidence the organization could produce today to show it acted deliberately if an AI outcome were challenged.