What is an AI champion?
Workflow, adoption and value
An AI champion is a trusted internal person who helps colleagues use AI in a practical, safe and workflow-relevant way. They are not there to sell tools or replace governance. Their job is to support useful habits, collect examples, spot friction, share working rules and escalate risks when AI use needs review.
Reviewed by Jackie, Head of Learning & Development, Levellers - Last reviewed 8 June 2026
What this means
An AI champion is usually someone inside the organisation who understands both the work and the people doing it. They help translate AI from a general idea into practical use inside day-to-day workflows.
The role can be formal or informal. In a small firm, it might be an operations lead, service manager, HR adviser or analyst who has enough credibility to help colleagues test AI sensibly.
The important point is that an AI champion should support team enablement, not become the only person allowed to understand AI.
Why it matters
AI use often starts unevenly. Some people experiment quickly, some avoid it and some use it in ways the organisation has not approved. A champion can help close that gap by making good use more visible and poor practice easier to spot.
For small and mid-sized organisations, this role can be useful because formal AI teams are rare. A champion can gather practical examples, explain working rules, help colleagues with first attempts and feed real issues back to the person who owns the workflow.
The role is especially useful during AI change management, when teams need steady support rather than a one-off launch message.
How it works
An AI champion usually helps in four ways:
identifying where AI is being used informally and where support is needed
sharing approved examples, prompts and workflow guidance
collecting feedback from users and surfacing blockers
escalating risk, data or quality concerns to the right owner
The role works best when it has boundaries. A champion can advise, demonstrate and support, but they should not approve high-risk use alone or become a substitute for an AI policy.
Examples
In a recruitment firm, an AI champion might help consultants use approved prompts to summarise interview notes, while reminding them that AI should not make selection decisions or introduce unfair criteria.
In a financial advice office, a champion might support advisers with internal knowledge search or meeting preparation, while making clear that advice, suitability and client communications remain subject to human review.
In an operations team, a champion might collect examples where AI helps draft standard operating notes, then work with the workflow owner to decide whether those examples should become shared guidance.
Where reusable examples are needed, the champion may help maintain a prompt library with review dates and usage notes.
Common misunderstandings
One misunderstanding is that an AI champion is a technical expert. Technical understanding helps, but workflow judgement and trust inside the team are often more important.
Another misunderstanding is that a champion should drive adoption at any cost. The better role is to help the team find useful, bounded AI use and stop weak or risky practice from spreading.
A third misunderstanding is that one enthusiastic person can carry the whole programme. Champions need sponsorship, governance, time and a clear route for decisions they cannot own.
Risks and boundaries
The main risk is role confusion. If colleagues treat the champion as the approval route for every AI decision, the organisation can end up with informal governance and unclear accountability.
A champion should not decide data policy, approve regulated use or sign off high-impact decisions alone. For workflows with personal data, employment decisions, client advice or financial commitments, the champion should help users follow the agreed process and escalate issues for human review. This connects directly to human-in-the-loop AI.
What to do next
Nominate one person for one workflow, not for the whole organisation. Give them a short remit: support first use, collect examples, maintain simple guidance and escalate risks. Review the role after 30 days to check whether it is helping the team or creating a bottleneck.
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FAQs
Does every business need an AI champion?
No. Very small teams may only need a clear workflow owner. An AI champion becomes useful when several people are experimenting and the organisation needs shared guidance.
What skills should an AI champion have?
They should understand the workflow, communicate clearly, be trusted by colleagues and know when to escalate. They do not need to be an engineer.
Can an AI champion approve AI tools?
Not on their own. They can help assess practical fit, but procurement, data protection, security and governance decisions need the appropriate accountable owners.
How much time should the role take?
Start small. For a first workflow, the role may only need a regular check-in, a maintained example set and a way to capture user questions.
Sources
CIPD AI in the workplace guidance informed the points on people professionals supporting responsible AI use at work.
CIPD AI skills planning guidance informed the skills and managed adoption framing.
GOV.UK hidden AI risks toolkit informed the behavioural risk and escalation points.
NIST AI Risk Management Framework informed the emphasis on accountable roles, risk management and trustworthy use.
ICO guidance on organisational roles for explaining AI informed the point that responsibilities need to be identified across the decision-making pipeline.