What ASX leaders are learning about building AI leadership capability

For many organisations, the conversation about artificial intelligence has changed. Twelve months ago, the focus was often on experimentation. Today, leaders are increasingly focused on execution. Questions about governance, capability, investment and risk are now being discussed at board and executive levels. As a result, many organisations are asking a new question: 

Who should lead AI?

Over the past year, Davidson Executive & Talent has supported multiple ASX-listed organisations seeking insight into the global market for senior AI leadership talent. Across those engagements, a consistent theme emerged. 

Finding AI leaders is rarely the hardest part. 



Defining what success looks like is.

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Why AI leadership has become a strategic decision

Many organisations are still determining where AI capability should sit within the business.  Should accountability sit with technology? 

Data? 

Digital? 

Product? 

Operations? 

The answer often depends on the organisation's maturity, strategy and existing leadership structure.  What is becoming increasingly clear, however, is that AI leadership is no longer simply a technical appointment.

The strongest AI leaders operate across technology, commercial strategy, governance, risk and organisational change. They are expected to help organisations navigate complex decisions about customer outcomes, operational efficiency, responsible AI practices and long-term capability development. 

That makes AI leadership as much a business challenge as a technology one. 

The AI leadership roles emerging globally 

One of the most common questions we hear from clients is: "What are other organisations calling this role?"  The answer varies considerably. 

Across Australia, Asia, Europe, the United Kingdom and North America, organisations are adopting a range of leadership structures, including: 

• Chief AI Officer 
• Chief Data and AI Officer 
• Chief Data Officer 
• Head of AI 
• VP Machine Learning Engineering 
• AI Platform Leader 

While titles differ, the underlying responsibilities are often surprisingly similar. 

Across markets, AI leaders are increasingly responsible for: 

• AI strategy and execution 
• Data governance 
• Responsible AI and risk management 
• Product development and commercialisation 
• Platform enablement 
• Organisational capability uplift 

The title may change.  The leadership challenge often does not. 

What attracts senior AI leaders

Remuneration remains important. But it is rarely the deciding factor.  Across global markets, senior AI leaders consistently place value on: 

• Meaningful business impact: many candidates want to solve significant problems rather than lead isolated technical initiatives. 
• Organisational commitment: Candidates often look for evidence that AI has executive sponsorship and long-term investment. 
• Scale and complexity: The opportunity to influence enterprise-wide outcomes remains a strong motivator. 
• Leadership alignment: Senior AI leaders want confidence that executive teams understand both the opportunities and constraints associated with AI adoption. 
• Capability runway: Many candidates assess whether they will be building something sustainable or simply responding to short-term pressure. 

What organisations are getting wrong 

One of the more common challenges we observe is treating AI leadership as a recruitment exercise. 

In reality, it is usually an organisational design question. 

Before engaging the market, leaders often need clarity on: 

• accountability 
• reporting lines 
• decision-making authority 
• governance expectations 
• measures of success 

Without that clarity, even highly capable candidates can struggle to succeed. 

The strongest appointments typically occur when organisations first define how AI capability should contribute to business outcomes and then identify leaders who can deliver that vision. 

Looking ahead

The market for AI leadership will continue to evolve. 

New titles will emerge. 

Responsibilities will shift. 

Organisational structures will mature. 

What is unlikely to change is the importance of leadership capability. 

The organisations making the greatest progress are not necessarily those investing the most in AI. 

They are often the organisations making deliberate decisions about leadership, governance and capability before technology becomes the limiting factor. 

As AI moves from experimentation to execution, leadership decisions are becoming some of the most important technology decisions organisations make.