Chief Data Officer vs Chief AI Officer: Which to Hire First?

As organisations accelerate AI adoption, many leadership teams are asking the same question: should they appoint a Chief Data Officer (CDO) or a Chief AI Officer (CAIO) first?

While the two roles are closely connected, they solve very different business challenges. A Chief Data Officer creates the trusted, governed data that organisations depend on, while a Chief AI Officer transforms that data into commercial outcomes through artificial intelligence. One role builds the foundations, the other unlocks the value.

The right appointment depends on factors such as your organisation's digital maturity, existing data capabilities and long-term AI ambitions. As investment in AI continues to grow, understanding where each executive fits within the leadership team has become increasingly important, with demand for both chief data officer jobs and chief AI officer jobs continuing to rise across the technology sector.

In this guide, we'll explore the key differences between the two roles, when organisations should hire each one, how they work together, salary considerations and what businesses should consider when recruiting senior AI and data leaders.

Why Organisations Are Separating Data and AI Leadership

Not long ago, responsibility for AI often sat alongside existing executive positions such as the Chief Data Officer (CDO), Chief Technology Officer (CTO) or Chief Information Officer (CIO). AI was viewed as another technology initiative rather than a business capability, making it a natural extension of an existing leadership role.

That approach is becoming far less common.

As organisations move from experimenting with AI to embedding it across products, operations and customer experiences, they're recognising that governing enterprise data and leading AI transformation require different expertise. Data quality, governance and compliance remain fundamental, but organisations also need leaders who can identify commercial AI opportunities, oversee implementation and drive organisation-wide adoption.

This shift is changing the way businesses approach leadership hiring. Rather than expecting one executive to own every aspect of data and AI, organisations are increasingly building complementary leadership teams with clearly defined responsibilities.

This reflects what we're seeing across the European technology market. Demand for dedicated AI leadership has accelerated significantly over the past year as organisations move beyond experimentation and begin looking at how AI can be embedded across the business. Rather than asking whether they should invest in AI, executive teams are increasingly asking how they should structure leadership to support it.

Chief Data Officer vs Chief AI Officer: What's the Difference?

Although the Chief Data Officer and Chief AI Officer work towards the same strategic objective, their day-to-day responsibilities are fundamentally different. One focuses on ensuring data is trusted, secure and accessible, while the other focuses on using that data to create measurable business outcomes through AI.

Chief Data Officer (CDO)

A Chief Data Officer is responsible for creating the data foundations that support every part of the organisation. Their role is to ensure enterprise data is accurate, secure, accessible and compliant, giving leadership teams confidence that they can make informed decisions based on trusted information.

While responsibilities vary between organisations, Chief Data Officers are typically responsible for:

• Developing the enterprise data strategy
• Establishing data governance frameworks
• Improving data quality and integrity
• Overseeing master data management
• Ensuring regulatory compliance
• Supporting enterprise data architecture
• Embedding a data-driven culture across the business

As organisations continue to invest in digital transformation, demand for chief data officer recruitment and chief data officer jobs has grown steadily. Businesses increasingly recognise that without strong governance and reliable data, it becomes significantly harder to scale AI initiatives successfully or generate meaningful business insight.

Chief AI Officer (CAIO)

Where the Chief Data Officer builds the foundation, the Chief AI Officer is responsible for turning that foundation into measurable business value. Their focus is on identifying where artificial intelligence can improve productivity, enhance customer experiences, automate processes and create new commercial opportunities.

Chief AI Officers are commonly responsible for:

• Developing the enterprise AI strategy
• Leading generative AI initiatives
• Driving machine learning adoption
• Establishing AI governance frameworks
• Identifying automation opportunities
• Supporting AI-enabled product development
• Prioritising AI investment across the organisation

The rapid growth in chief AI officer jobs reflects a significant shift in how organisations view artificial intelligence. Rather than treating AI as a standalone technology project, businesses are increasingly appointing dedicated executives who can align AI investment with wider commercial strategy and long-term business objectives.

Why AI Leaders Need Strong Data Foundations

It's easy to think of the Chief Data Officer and Chief AI Officer as competing roles, but in practice they're highly dependent on one another. The effectiveness of any AI strategy is determined by the quality of the data that underpins it, making collaboration between the two executives essential.

As Elliott Delente, Director of Permanent Recruitment at Montreal Associates, explains:

"AI is only as effective as the data it's built on. If the underlying data isn't right, AI simply won't deliver at scale."

A useful way to think about the relationship is to imagine a Formula One team.

The Chief Data Officer is responsible for producing high-performance fuel. Their focus is on ensuring enterprise data is clean, governed, secure and reliable. The Chief AI Officer designs and drives the engine, using that data to build intelligent systems that improve decision-making, automate processes and create competitive advantage.

Even the most advanced AI models cannot compensate for poor-quality data. Equally, organisations with well-governed data will struggle to realise its full value if they lack the leadership needed to develop and scale AI initiatives. The strongest organisations understand that data and AI leadership are complementary capabilities rather than competing priorities.

Should You Hire a Chief Data Officer or Chief AI Officer First?

One of the biggest misconceptions is that organisations need to choose between a Chief Data Officer and a Chief AI Officer. In reality, the right appointment depends on where your organisation is in its transformation journey, the maturity of its data estate and the outcomes it's hoping to achieve over the next three to five years.

While every organisation's priorities are different, the framework below provides a useful starting point when assessing which leadership capability is likely to deliver the greatest value.

When to hire a Chief Data Officer

If your organisation is still addressing inconsistent reporting, fragmented systems or regulatory challenges, strengthening data leadership should usually be the priority. Investing in chief data officer jobs at this stage creates the governance, quality and trust needed for future AI initiatives to succeed.

When to hire a Chief AI Officer

Businesses with mature data capabilities are often ready to focus on accelerating AI adoption. Hiring a Chief AI Officer enables organisations to move beyond experimentation, develop a clear AI roadmap and ensure investment delivers measurable business outcomes rather than isolated proof-of-concepts.

When organisations need both

For larger organisations, the question is rarely whether to appoint a Chief Data Officer or a Chief AI Officer. Instead, it's about recognising when each role becomes necessary.

As AI becomes embedded across multiple business functions, separating responsibility for enterprise data and AI strategy allows both executives to focus on their areas of expertise while working together to support wider transformation goals. This collaborative approach is becoming increasingly common across organisations investing heavily in AI, cloud and digital innovation.

Are Organisations Hiring Chief AI & Data Officers Instead?

Alongside dedicated Chief Data Officer and Chief AI Officer roles, we're also seeing the emergence of hybrid positions such as the Chief AI & Data Officer (CAIDO). 

These roles combine responsibility for enterprise data and AI strategy under a single executive and are most common in organisations at an earlier stage of AI maturity or within fast-growing scale-ups.

As AI programmes become more sophisticated, however, many organisations find the remit becomes too broad for one leader. We're increasingly seeing businesses separate data and AI leadership, recognising that each discipline requires dedicated expertise to support long-term transformation. While hybrid roles continue to have their place, the continued growth in chief ai officer jobs suggests many organisations still see value in dedicated AI leadership.

Salary Expectations for Chief Data Officers and Chief AI Officers

Executive salaries vary significantly depending on location, organisation size, sector and the scope of transformation programmes. Rather than comparing base salaries alone, organisations should consider the broader value these executives are expected to deliver.

While salary benchmarking is important, it shouldn't be the only factor influencing an executive appointment. The strongest candidates are often evaluating organisations based on the scale of transformation, board-level commitment to AI, investment in technology and the opportunity to shape long-term strategy.

We're also seeing greater flexibility in how organisations approach these appointments. Some businesses begin with interim or contract executives to define an AI roadmap before moving to a permanent appointment, while others recruit permanent leaders from the outset to embed AI capability across the organisation.

As demand for chief AI officer jobs, chief data officer jobs and wider AI leadership continues to increase, organisations should expect competition for experienced candidates, particularly those with proven experience delivering enterprise transformation.

Executive Search Is Becoming a Competitive Advantage

Hiring senior AI leaders has become increasingly challenging. The strongest candidates are rarely applying for advertised vacancies and are often already leading transformation programmes, advising executive teams or building AI capability within global organisations.

This is particularly true when recruiting for emerging positions such as Chief AI Officer, where organisations are looking for more than technical expertise. Successful candidates combine commercial awareness, leadership capability and the ability to influence change across the business.

As a result, organisations are increasingly moving away from traditional recruitment methods and partnering with specialist executive search firms that understand both the technology landscape and the leadership qualities required to deliver successful transformation.

At Montreal Associates, we support organisations across Europe with chief data officer recruitment, leadership hiring and specialist executive staffing solutions across AI, cloud, data and digital transformation. Whether you're recruiting for cdo jobs, caio jobs or building an entirely new AI leadership function, our consultants combine deep market knowledge with extensive executive networks to identify leaders capable of delivering lasting impact.

Contact our team today or start your job search.

FAQs About CDO jobs and CAIO jobs

What is the difference between a Chief Data Officer and a Chief AI Officer?

A Chief Data Officer is responsible for enterprise data strategy, governance and compliance, ensuring data is accurate, secure and accessible. A Chief AI Officer uses that trusted data to develop AI strategies, implement machine learning initiatives and create measurable business value.

Should I hire a Chief Data Officer before a Chief AI Officer?

It depends on the maturity of the organisation. Businesses with fragmented data or limited governance often benefit from appointing a Chief Data Officer first, while organisations with mature data foundations may be ready to accelerate AI adoption through a Chief AI Officer.

Do I need both a Chief Data Officer and a Chief AI Officer?

Not always. The right leadership structure depends on your organisation's AI maturity, existing data capabilities and long-term objectives. Some businesses benefit from appointing a single executive in the early stages of AI adoption, while others require dedicated data and AI leadership from the outset. As AI initiatives become more sophisticated, we're increasingly seeing organisations separate the roles to give both data governance and AI strategy the focus they require.

What do CDO jobs typically involve?

A Chief Data Officer develops enterprise data strategy, improves data quality, oversees governance, ensures regulatory compliance and creates the trusted data foundation needed to support business decision-making and digital transformation.

What do CAIO jobs typically involve?

A Chief AI Officer develops an organisation's AI strategy, oversees AI implementation, identifies automation opportunities, establishes AI governance and ensures AI investments deliver measurable commercial outcomes.

Why are Chief AI Officer jobs growing so quickly?

As organisations move beyond AI experimentation and begin embedding AI across products, operations and customer experiences, demand has grown for executives who can lead enterprise-wide AI transformation and align technology investment with business strategy.

How can MA support AI executive hiring?

Montreal Associates specialises in executive technology recruitment across AI, data, cloud and digital transformation. Our specialist consultants support organisations with chief data officer recruitment, leadership hiring and executive staffing solutions, helping businesses secure experienced leaders in an increasingly competitive market.