NOTE: To use this template, copy the content using the “Copy page” button above, then customise it for your organisation. Updated September 2026.

Chief AI Officer

Location: [Location, hybrid or remote] Reports to: [Chief Executive Officer or Chief Information Officer] Team: [Current team, and the headcount you’re approving] Pay: [Base salary range] plus [bonus, equity, benefits]

The role in brief

We need someone to build and lead the team that puts AI to work across this organisation, and to be accountable to the board for the results.

You’ll build an AI team, set up a network of Claude Champions in every department, get the first agents and workflows into production, and put the governance and training in place that let adoption keep growing. We’ll measure you on how many people use AI every week and on the business results the programme delivers, not on strategy documents.

If you want to talk about AI transformation, this isn’t the role. If you want to build the team and programme that deliver it across [number] employees, read on.

What makes this role different

Not a CIO role

A CIO runs infrastructure, security and enterprise systems. This role doesn’t manage servers or ERP projects; it works with the CIO to put AI to work in the business.

Not a CTO role

A CTO leads product and engineering. This role doesn’t build AI products for customers; it helps internal teams use AI in their work.

Not an AI Operations Lead role

An AI Operations Lead builds and runs the programme day to day. This role owns the programme, the budget and the board relationship, and hires the people who build. See our AI Operations Lead job description if that’s the role you need first.

What this role is

You’ll own the organisation’s AI programme. You’ll map how the business works and where AI fits, prioritise the use cases, build the team that delivers them, set up the governance that lets people experiment safely, and run the change programme that gets AI used.

Core responsibilities

Build the AI team and champions network (35% of your time)

• Hire and lead the AI team, including [AI Operations Leads, builders, a change lead]
• Assign a named AI lead to each major department
• Set up and run a Claude Champions network (5 to 10% of employees)
• Set up office hours, a help channel and support for new users
• Work with Legal, HR and the DPO on policy and risk

Success looks like: The team fully hired and running. [Target]% of employees using AI every week within 12 months. Teams building their own skills, projects and workflows without central help.

Delivery: use cases, agents and workflows (25%)

• Map the organisation’s operating model: its units, the processes each owns, and where AI fits
• Run a prioritised pipeline of use cases, scored on impact, confidence and ease
• Get the first agents and workflows into production, and keep a steady flow after them
• Put a named owner on every agent in production, with its access, instructions and cost visible

Success looks like: A live use case pipeline with owners. Agents and workflows in production in [number] teams within 12 months, each with a measured result.

Tools and platform (15%)

• Select and license the AI platforms, such as [Claude Enterprise, Microsoft Copilot]
• Run a fast approval process for new tools and connectors
• Set role-based access, data controls and connector permissions
• Track usage and cost against the value delivered

Success looks like: An approved tool stack. New tools approved in [number] days. Cost per team visible and justified.

Change enablement (15%)

• Design training by role: foundations, role-specific sessions, hackathons
• Run internal communications and share results
• Recognise the teams and people who deliver results with AI
• Measure adoption by team and act where it stalls

Success looks like: A change programme your team runs without you. Employees teaching each other. Results shared across the organisation.

Governance and board reporting (10%)

• Own the AI policy and the rules for agents, connectors and data
• Run risk assessments, including DPIAs with the DPO where needed
• Report monthly to the executive team and quarterly to the board on adoption and results
• Recommend investment and budget

Success looks like: A policy approved by Legal and the DPO that encourages use. The board sees progress reported like any other programme.

First 90 days deliverables

Month 1: Foundation

• Map the operating model and build the first use case pipeline
• Confirm the tool stack and the AI policy (approved by Legal and the DPO)
• Agree the team structure and start hiring
• Choose the pilot teams and the first use cases
• Present the 12-month plan to the executive team

Month 2: Team and first builds

• Make the first hires
• Recruit and train the first Claude Champions cohort ([number] people)
• Start building the first agents and workflows with the pilot teams
• Launch internal communications, office hours and the help channel

Month 3: First results

• First agents and workflows in production with the pilot teams
• Expand to the next [number] teams
• Set up adoption and results reporting
• Present 90-day results to the board, and the plan for the next quarter

Qualifications

Must have

• Daily, hands-on AI use for at least a year. Can build skills, projects and simple agents, and can coach others to do the same.
• Team building: has hired and led cross-functional teams and created new roles.
• Change leadership: has led a change programme with measured adoption and business results.
• Programme delivery: has taken programmes from plan to production, with a portfolio to show for it.
• Influence: works well with IT, Legal, HR, Finance and business leaders.

Strongly preferred

• Experience in [your industry] and its processes
• Built a centre of excellence or enabling function from scratch
• Background in transformation, organisational development or consulting
• Technical background, able to evaluate AI platforms and agent designs
• Experience in regulated environments
• Budget responsibility for a programme of [size]

Not required

• A PhD in machine learning
• Experience building AI models from scratch (this isn’t a research role)
• A software engineering background
• Previous C-suite experience (strong directors are encouraged to apply)

Success measures

Reviewed monthly

• Weekly active AI users, as a percentage of employees
• Teams with agents or workflows in production
• Hours saved, and the business measures each use case targets
• Use cases moved from pipeline to production

Reviewed quarterly

• Teams building their own skills, projects and workflows
• AI cost against value delivered
• Incidents and how fast they were resolved
• Employee confidence with AI tools

Not measured: strategy decks, roadmap documents, conference talks or articles. They’ll happen; they aren’t how we’ll judge the role.

Pay and benefits

Base salary: [range] Total package: [range, including bonus and equity]

What influences the offer:

• A track record of adoption and business results, not strategy work alone
• Industry experience
• The size and complexity of previous organisations
• References from non-technical colleagues

Benefits: [standard benefits] · [AI tool budget] · [learning budget]

Before you hire: questions to ask yourself

Hire a Chief AI Officer if:

• You have 1,000 or more employees and a committed AI budget
• The programme needs an executive who answers to the board
• You can wait for an executive search
• You want to build permanent internal capability

Consider an alternative first if:

• You need delivery now; recruitment takes months
• You’re not yet sure what the role should deliver
• The CIO or another executive already owns the AI mandate

The alternatives:

• Hire an AI Operations Lead first to build and run the programme; add the executive later. Our AI Operations Lead hiring guide includes a Claude skill that runs the hiring process with you.
• Give an existing executive the mandate with delivery support behind them.
• Bring in an implementation specialist to run the programme while you hire.

Can you define success? If you can’t say what this person will deliver in 90 days, 6 months and 12 months, you’re not ready to hire.

How to apply

[Your application instructions]

In your application, please include:

1. An example of a team you built that changed how an organisation worked
2. How you’d approach our first 90 days
3. A change programme you led, and the adoption and business results it produced
4. How you’d measure this role at 6 and 12 months
5. Something you built with AI in the last month, and why it works

We care more about what you’ve built and led than where you worked or which degrees you hold.

Implementation notes

1. Set the pay range from your executive pay structure and current local market data.
2. Adjust the scope and team to your size; 1,000 employees and 10,000 need different teams.
3. Add industry context throughout.
4. Match the success measures to your business objectives, and agree them before you post.
5. Be honest about your AI maturity, so candidates know whether they’re starting from scratch.
6. Name your tools so candidates know what they’ll work with.
7. Make the reporting line and authority clear, including the budget the role controls.