Most CAIO job descriptions describe a VP of AI with a bigger title. Here is a working template, the six responsibilities, and what to add for South Africa.
TL;DR
Writing a job description for a role your organisation has never had is hard. Nobody inside has done it before, and copying a template risks describing someone else's company.
This guide gives you a working template, explains each section, and lists the mistakes that make the posting attract the wrong candidates.
The CTAIO job description template frames the CAIO as a C-suite executive responsible for an organisation's AI strategy, governance, and cross-functional adoption. The role defines how AI creates business value, makes sure AI systems meet regulatory and ethical standards, and builds AI literacy across the organisation. CTAIO is a hiring resource that also promotes fractional CAIO services, so read its framing with that in mind. The structure is still a useful starting point.
The distinction it draws is worth keeping. A VP of AI typically leads the engineering team and builds AI products. A CAIO decides which products to build, how to govern them, and how to drive adoption across the business.
Role summary. Two or three sentences stating who the role serves and what it is accountable for. For example: "The chief AI officer is accountable for [organisation]'s AI strategy, governance, and adoption, and reports to the [managing director / CEO]."
Reporting line. State who the role reports to and who reports to it. CTAIO's view is that a CAIO who owns enterprise-wide strategy and governance should report to the chief executive, because a CAIO who must set rules that apply to the CTO's teams cannot report to the CTO. If AI is mainly a technology function, reporting to the CTO can work. Pick one and write it down.
Core responsibilities. CTAIO groups these into six domains:
CTAIO notes that most organisations will prioritise three or four of these domains depending on their AI maturity. A mid-sized business with no models in production will care little about model lifecycle management and a great deal about governance and adoption.
Required background. CTAIO describes three common career tracks: machine learning leadership (10 or more years, including leading AI teams), management consulting with an AI transformation specialism (10 or more years), and engineering leadership with significant AI programme ownership (12 or more years). The non-negotiable, in its words, is the ability to operate at C-suite level, including board presentations and cross-functional influence.
Preferred qualifications. An advanced degree in a relevant field, industry experience, and familiarity with regulatory frameworks. Treat these as preferences and not filters. Deep technical expertise alone does not make someone effective in this role.
CTAIO lists five. They hold up well in practice.
CTAIO's template varies the emphasis by organisation type. A startup CAIO focuses on AI product strategy and builds from scratch. A growth-stage CAIO scales a platform and inherits a team. An enterprise or private-equity-backed CAIO focuses on governance and reporting. A regulated-industry CAIO focuses on audit-ready frameworks and satisfying regulators. A mid-sized South African business usually sits between the growth and enterprise profiles in what it needs: governance and adoption first, platform scaling later.
The CTAIO template is written with the US and EU in mind, so adapt the compliance section to your own context.
CTAIO's own advice is that most pre-Series B startups do not need a full-time CAIO, and suggests a fractional one as a way to define the role, set the governance scope, and build structure before hiring. The same logic applies to many mid-sized organisations. If you cannot write the six domains with confidence, or AI decisions are not yet frequent, test the need first. Our guides to a fractional Chief AI Officer and an outsourced Chief AI Officer explain how that works, and our guide to a Chief AI Officer in Cape Town covers the local picture. The AI Readiness Diagnostic is a free way to see where your organisation stands before you scope the role.
A chief AI officer owns an organisation's AI strategy, governance, and adoption. The role decides which AI initiatives to pursue, sets the rules for using AI safely, and drives adoption across business units.
A VP of AI usually leads the AI engineering team and builds products. A chief AI officer has a wider mandate covering strategy, governance, compliance, vendors, and adoption.
CTAIO suggests the CEO if the role owns enterprise-wide strategy and governance, and the CTO if AI is mainly a technology function. Decide before you write the posting.
There is no single path. Common tracks are AI leadership, management consulting with an AI specialism, and engineering leadership with AI programme experience. The essential trait is the ability to lead at executive level.
CTAIO says searches typically run 90 to 120 days, and that the biggest delay is usually agreeing internally on what the role owns.
Ready to move from reading about AI to getting your organisation ready for it? Start with the diagnostic.
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