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United Kingdom
The US continues to dominate pay for artificial intelligence talent, extending its lead over other major economies as employers reshape reward strategies to compete for scarce skills.
Median total compensation for mid-level machine learning roles now exceeds $170,000 in the US, according to WTW’s latest Artificial Intelligence and Digital Talent Salary Survey Report. It compares with around $122,000 in Germany and just under $100,000 in the UK, highlighting a significant pay gap between the US and European markets.
Canada has slipped behind the UK into fourth place, reflecting pressure in some mature markets. Across all countries studied, median salaries for machine learning roles rose by an average of 2%, while total compensation increased by 6%.
Elsewhere, Mexico recorded a 19% rise in salaries and a 29% jump in total compensation, while Brazil also posted double-digit increases. Canada, by contrast, saw declines in median pay for these roles.
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“AI pay is no longer just about where salaries are highest, but where momentum is building fastest and how employers are aligning pay and incentives to keep pace,” said Ruchi Arora, Europe Leader for Work, Rewards, and Career consulting, WTW. “Employers that rely on last year’s assumptions risk falling behind, particularly as short and long-term incentives play a bigger role in fast-growing markets.”
Incentives reshape AI talent strategy
AI roles continue to command higher pay than other digital disciplines, including cyber security and cloud engineering, reflecting the scarcity of advanced skills such as algorithm design, neural networks and data modelling.
Cloud computing salaries are also rising quickly, with median salaries for cloud engineering increasing by 9% on average across ten countries, while total compensation is up 12%. China and India recorded particularly strong growth, driven by investment in cloud infrastructure.
“Organisations are increasingly using short and long-term incentives to compete for scarce skills,” Arora said. “In AI roles especially, stronger growth in total pay rather than base salary alone suggests that long-term incentives are becoming a more important retention lever. For example, we’re seeing some employers using Restricted Stock Units with regular vesting periods in order to make pay packages more attractive and ‘sticky’ in terms of retaining talent for longer.”
Demand for digital roles is being led by software engineers, followed by application developers and data scientists, while AI engineers rank lower in current demand despite their growing strategic importance.
The US, India and Germany lead global demand for AI and machine learning engineers, with supply strongest in India and the US.
“These patterns underline why a single global pay strategy rarely works,” Arora said. “What is considered a hot role – and how organisations need to reward and develop those roles, depends heavily on local supply, maturity of adoption, and the mix of incentives on offer.”
Employers are also broadening reward strategies beyond base pay. Nearly half now offer differentiated programs for digital talent, combining higher salaries with flexible working, learning and development, retention bonuses and long-term incentives.
As AI roles continue to evolve, companies are reassessing job design and career paths alongside pay, reflecting the shifting demands of the digital workforce.
