Welcome to our annual Data, Analytics, and Artificial Intelligence Officers Compensation Survey. This report explores compensation for executive roles related to artificial intelligence and/or data analytics. For this report, Heidrick & Struggles compiled data from a survey conducted in summer 2025, featuring responses from 318 executives.

As always, we welcome your feedback and encourage you to contact us or your Heidrick & Struggles representative with any questions or comments.

Market context

Across industries, organizations are racing to integrate artificial intelligence into their operations—but few would describe themselves as experts. Nearly every company is experimenting, often through multiple pilot programs or proofs of concept, yet most still consider themselves in early implementation phases. The prevailing sentiment is one of collective learning: progress is real, but maturity remains elusive. In some cases, the drive to move quickly has already led to setbacks, including litigation and compliance risks that have made many leaders more cautious about scaling AI too aggressively.

Data quality, security, and compliance continue to be the most consistent barriers to scale, underscoring that even as AI reshapes business priorities, few organizations have yet figured out how to operationalize it sustainably.

Leadership structures—and by extension, compensation patterns—are evolving unevenly. AI initiatives typically begin under technology executives such as the CTO, but many companies are now carving out distinct AI leadership roles. However, nearly half of the AI leaders surveyed report that their organization has simply reclassified existing positions to include AI responsibilities. This approach has created confusion about what constitutes true AI leadership and has inflated compensation expectations across the board, because these roles have a remit wider than AI alone. As companies benchmark against these redefined roles, salary bands are rising even when the scope of responsibility or the technical expertise required may not justify it. The result is a market where compensation is outpacing clarity. Organizations want AI leaders but are still figuring out what those leaders should do—and not do.

At the workforce level, companies recognize the need for widespread upskilling. Change management and cloud engineering skills are in especially high demand as organizations navigate how to integrate AI systems responsibly and at scale. Meanwhile, some skills once viewed as critical, such as prompt engineering, have already seen declining demand as AI tools improve their own capabilities. The net effect is a fluid, fast-moving skills market that parallels the higher-level lack of clarity about AI leadership and compensation. Nonetheless, the fact that companies are finding it easier to find people with strategically relevant skills even as the technology continues to evolve quickly suggests that companies are moving toward successfully embedding AI into the ways of working.

For full compensation data, download the report.

About the author

Ryan Bulkoski (rbulkoski@heidrick.com) is the global head of the Artificial Intelligence, Data & Analytics Practice; he is based in the San Francisco office.