Firms within the AI industry chain are vying for top talent by offering lucrative salaries, with wealth-generating opportunities now extending beyond founders to encompass researchers and interns alike. There has been a notable surge in both the quantity and remuneration of AI-related roles. Our research, which encompassed 30 listed companies across three key sectors—AI large-scale models and applications, AI chips and semiconductors, and robotics and embodied intelligence—alongside three major internet companies, revealed that even unprofitable startups are willing to make upfront investments to lure talent. In fact, executive salaries at some loss-making enterprises are already on par with those at established industry giants.

Executive compensation varies significantly across sectors. The AI large-scale models and applications sector offers the highest average salaries, while the chips and semiconductors sector leads in terms of median salaries. Conversely, the robotics sector tends to offer relatively lower salaries, reflecting the varying degrees of commercialization within each industry.

High salaries are structured in diverse ways, ranging from cash-heavy packages to equity incentive-dominated plans, as well as balanced approaches that combine both. Companies frequently employ equity incentives as a means to retain talent, with notable disparities in employee stock ownership coverage and ratios across different firms. Some companies offer broad-based stock ownership plans, while others concentrate their equity incentives on key personnel.

A technical background plays a pivotal role in determining talent pricing. Individuals who possess both a deep understanding of technology and the ability to drive its implementation, along with core technical personnel, are often rewarded with high salaries. The substantial investment companies make in talent acquisition represents a strategic investment in their future. However, should these investments fail to yield returns, the talent costs can quickly become a significant financial burden.