Capability ยท AI leadership

The Chief AI Officer agenda, run like a CIO runs IT.

A Chief AI Officer is accountable for where AI creates value, how it is governed and secured, and whether people actually use it. I approach that agenda as a former Group CIO: a portfolio of use cases with owners and numbers, controls written before the build, evaluation before release, and adoption measured after go-live.

I do this work as AI & Automation Lead at Dexterous Group in Melbourne. This page shows the capability; it is not an offer of personal services.

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How I approach it

The method, step by step.

  1. A portfolio, not pilots

    Every AI use case gets an owner, a volume, a time per task and a measure of success before anything is built. Pilots without a business owner are where most AI spend disappears.

  2. Controls before code

    Data classification, an AI risk register, access rules and human sign-off points are written first, so the build inherits them instead of having them bolted on.

  3. Evaluation as the release gate

    Nothing is shipped because it demoed well. A fixed set of real cases, an accuracy bar and a reviewer acceptance bar decide whether it goes live.

  4. Adoption is the result

    Training, change management and a named owner per process. An AI system nobody uses is a cost, not a capability.

Work

Where I have done it.

Anonymised: no client, employer product or confidential detail.

Problem
A finance team wanted AI help with quarterly compliance work without risking a wrong lodgement.
What I did
Ran process discovery with 18 staff, built a roster of AI agents with a written graduation bar and a rule that nothing lodges with a regulator automatically.
Result
The flagship agent reached version 0.7.0 with 71 evaluation tests before wider use.
Stack
Python, Claude, Xero API and MCP, n8n
Problem
A diversified group needed one view of operations across many companies.
What I did
As Group Head of IT, designed and ran a custom ERP for 13 years, from data model to releases and training.
Result
72 tables, 416 releases, and the reporting moved off spreadsheets.
Stack
C#, .NET, SQL Server, Power BI
Tools and standards

What I work with.

  • AI strategy and portfolio
  • AI risk register
  • ISO 42001 and Australia's AI6 practices
  • Evaluation frameworks
  • Change management
  • COBIT 5, ITIL, PMP
Questions

Frequently asked.

What does a Chief AI Officer do?

A Chief AI Officer decides where AI should and should not be used, owns the governance and security of AI systems, and is accountable for adoption and measurable results. In practice it combines strategy, risk, engineering oversight and change management for AI across the organisation.

How is a CAIO different from a CIO?

A CIO is accountable for technology services and infrastructure. A CAIO is accountable for AI outcomes: which processes AI changes, how decisions made by AI are controlled, and whether the organisation gets value from it. Many organisations start with the CIO carrying both.

Does an Australian business need a Chief AI Officer?

Not always as a separate role. It needs someone accountable for AI value and risk. Smaller organisations usually give that to an existing executive with clear authority; larger and regulated ones increasingly create the role.

Is Amjid Ali a Chief AI Officer?

No. Amjid is AI & Automation Lead at Dexterous Group in Melbourne and a former Group CIO. He writes and speaks about the CAIO agenda and does this work inside his role; he does not run a personal consultancy.

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Also on this site.

For project work, contact Dexterous Group. For speaking, media or a peer conversation, email mail@amjid.au or message me on LinkedIn.