What does a Chief AI Officer do?

A Chief AI Officer owns the AI portfolio, the path from pilot to production, governance and model risk, and workforce capability. The role is accountable for business outcomes from AI, not for building models.

Who does a Chief AI Officer report to?

In enterprise the seat usually reports to the CEO or COO and presents to the board on a set cadence. In the mid-market it reports to the CEO or managing director and sits on the existing leadership team rather than heading a new function.

What are the core responsibilities of a Chief AI Officer?

Setting and sequencing the AI portfolio, moving initiatives into supported production, owning data and model governance, building internal capability, and reporting measurable P&L or risk outcomes.

Should a mid-market business hire a full-time Chief AI Officer?

Usually not at first. A business between A$20M and A$200M in revenue typically needs one to three days a week of senior AI ownership, which is why the mid-market version of this job description is realistically a fractional description.

Chief AI Officer job description: enterprise vs mid-market

The same title means two very different jobs depending on the size of the business. Here are both descriptions, written to be copied and adapted — plus the honest note about which one an Australian mid-market business is actually hiring for.

3 August 2026 · 12 min read

Why one job description does not work

Most Chief AI Officer job descriptions in circulation were written for organisations with a funded AI function, a model risk committee and a research agenda. Paste that into a A$60M business and you will attract candidates expecting a team, a budget and a multi-year mandate, then lose them in month four when they discover the job is actually to get three initiatives into production with borrowed people.

The enterprise version and the mid-market version share a purpose — someone is finally accountable for AI producing a result — but they differ on nearly everything else: reporting line, headcount, scope of governance, time horizon, and what good looks like in the first ninety days.

Write the one that matches your business. Both drafts below are structured the same way so you can lift either wholesale.

Version one: enterprise (A$500M+ revenue)

Job description · Enterprise

Purpose of the role

The Chief AI Officer is accountable for the safe, governed and commercially productive application of artificial intelligence across the organisation. The role sets the enterprise AI strategy, owns the funded portfolio of AI initiatives, and is answerable to the executive and the board for the outcomes that portfolio delivers.

Reporting line and structure

Reports to the Chief Executive Officer or Chief Operating Officer.
Member of the executive leadership team.
Leads a funded AI function with direct reports across delivery, data science, and AI governance or risk.
Presents to the board or a board risk and technology committee on a set cadence.

Key accountabilities

Own a multi-year enterprise AI strategy and the funded roadmap that delivers it.
Chair the investment process that funds, sequences and terminates AI initiatives.
Own model risk: inventory, validation, monitoring, drift, and documented controls.
Own regulatory and privacy obligations relating to AI, in partnership with legal, risk and the CISO.
Establish the enterprise AI platform, patterns and vendor architecture with the CTO.
Build and lead the internal AI capability, including hiring, structure and uplift for the wider workforce.
Report measurable value — cost, revenue, risk reduction — to the executive and board.

Outcomes in the first 90 days

A complete inventory of AI activity already running in the business, including shadow use.
A prioritised portfolio with funding recommendations and explicit stop decisions.
An approved AI governance framework and acceptable-use policy in force.
An agreed measurement standard so every initiative reports value the same way.

Evidence to require from candidates

AI systems they took into production at enterprise scale, and who operates them today.
Regulated-environment experience: model risk, audit, privacy, or APRA/ASIC exposure where relevant.
A portfolio they cut, and the reasoning they gave the executive.
Board-level communication: how they explained AI risk to non-technical directors.

What to leave out

Do not list model building, prompt engineering or tool selection as accountabilities. At this level they belong to the team, and putting them in the description filters for the wrong candidate.

Version two: mid-market (A$20M–A$200M revenue)

Job description · Mid-market

Purpose of the role

The Chief AI Officer is accountable for turning AI activity into a small number of measurable business results. The role owns the sequence — what gets tried, what gets stopped, and what makes it into supported production — and does so without a dedicated team, by working through the functions that already exist.

Reporting line and structure

Reports to the Chief Executive Officer or Managing Director.
Sits on the existing leadership team; no new function is created.
No direct reports. Capability is borrowed from operations, finance, technology and marketing.
Realistically a one to three day per week seat, not a full-time executive package.

Key accountabilities

Decide which AI initiatives are funded, in what order, and which are stopped.
Move initiatives from working demo to supported production: owner, monitoring, rollback, retired process.
Set a proportionate AI policy — data handling, approved tools, what staff may and may not do.
Lift practical capability in the existing team so the business is not dependent on one person.
Report against one or two P&L outcomes agreed with the CEO before work starts.
Advise on build, buy and partner decisions without becoming the vendor manager.

Outcomes in the first 90 days

A short, honest list of what is already running and what it has actually produced.
One initiative live in production with a named internal owner.
A written AI policy staff can follow without asking permission for every task.
An agreed measure, baselined, so the second ninety days can be judged.

Evidence to require from candidates

A system running in production today at a business of comparable size, and who runs it now.
What they killed, and why they killed it.
How they delivered without a team, and which internal people they worked through.
How they would break down your brief — a real operator decomposes the problem rather than pitching a solution.

What to leave out

Do not ask for a research agenda, a published body of work, or enterprise model-risk governance. Do not ask for a team leader. Asking for the enterprise profile at mid-market rates is the single most common reason these searches fail.

Side by side

The same title, two different jobs. This is the fastest way to check which one you are actually writing.

Dimension	Enterprise	Mid-market
Reports to	CEO or COO, plus board committee	CEO or Managing Director
Team	Funded function with direct reports	None; borrows existing capability
Primary focus	Strategy, risk and portfolio at scale	Getting a few things into production
Governance scope	Model risk, audit, regulatory obligations	Proportionate policy and data handling
Horizon	Multi-year roadmap	Two to four quarters
Measured on	Portfolio value and risk posture	One or two P&L outcomes
Commitment	Full-time executive	One to three days per week

The honest note about the mid-market version

Read the mid-market description again and the shape of it is obvious: no team, a two-to-four quarter horizon, one to three days a week, and a mandate that ends when the work is banked. That is not a full-time executive job. It is a fractional description wearing a permanent title.

Businesses that write it as a full-time role usually end up in one of two places. They fail to fill it, because the candidates who can do the work are priced at A$250,000 to A$450,000 and the budget is not there. Or they fill it with someone junior to the brief, and eighteen months later the pilots are still pilots.

Writing it as a fractional engagement from the start solves both. The cost is proportionate to the work, the start is measured in weeks, and the exit is clean when the business is ready for a permanent hire.

The remaining risk is quality, and it is a real one. “AI expert” is a self-appointed title, so the description alone will not protect you — the evidence sections above are the part that does. Ask for the production system. Ask who runs it now.

Common questions

What does a Chief AI Officer do?: A Chief AI Officer owns the AI portfolio, the path from pilot to production, governance and model risk, and workforce capability. The role is accountable for business outcomes from AI, not for building models.
Who does a Chief AI Officer report to?: In enterprise the seat usually reports to the CEO or COO and presents to the board on a set cadence. In the mid-market it reports to the CEO or managing director and sits on the existing leadership team rather than heading a new function.
What are the core responsibilities of a Chief AI Officer?: Setting and sequencing the AI portfolio, moving initiatives into supported production, owning data and model governance, building internal capability, and reporting measurable P&L or risk outcomes.
Should a mid-market business hire a full-time Chief AI Officer?: Usually not at first. A business between A$20M and A$200M in revenue typically needs one to three days a week of senior AI ownership, which is why the mid-market version of this job description is realistically a fractional description.

Chief Orchestration Officer is building Australia’s vetted bench of fractional AI leaders for businesses between A$20M and A$200M in revenue. Vetting happens before anything is listed, and it is independent of payment.

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