Workers with AI skills are getting these pay cash premiums – Computerworld
As companies are scramble to get ahead in the artificial intelligence (AI) arms race, one problem the face is finding and retaining AI talent.
For example, Meta has been extending job offers to candidates with AI experience without even interviewing them, and CEO Mark Zuckerberg went so far as to email researchers at Google’s DeepMind unit to recruit talent.
Foote Partners, a recruitment, consulting and research firm, recently published its latest IT skills and pay index, which found, not surprisingly, that companies are paying premiums for workers with AI-related abilities.
Foote Partners recognizes 47 “critical A.I. skills,” and on average, employees who obtain those skills get a pay premium of 7% to 21%. Those premiums can come in different forms, including bonuses and cash compensation.
“This is cash paid out, not as a salary increase but in addition to salary,” said David Foote, chief analyst at Foote Partners. “In fact, 28 of these core AI skills can add between 15% and 21% in pay, well above the 9.6% average premium across all 632 non-certified skills we report. They are very hot right now.”
Cash premiums for skills such as AI chatbot app developer and large language model (LLM) tuning are paid out separately from salaries so that as needs are met and the value of those talents declines, the payouts can be reduced or eliminated.
“Perhaps the main difference with skills pay is, unlike a bonus, skills pay premiums are typically paid out at every pay period — same as salary — instead of a lump sum at the end of year, which is more common with bonuses,” Foote said.
In addition, more than a dozen AI-related certifications “are showing real market value strength,” he said. Those skills include prompt engineering, neural networks, AI engineer, AI scientist, and AI model optimization.
According to Foote, a Certified Artificial Intelligence Scientist earns the highest pay premium, ranging 8% to 12%, with the average being 10% of base salary equivalent,. The next highest cash pay premium in this cluster is for a Microsoft Certified: Azure AI Engineer Associate, who can earn 9% of base equivalent in skills premium pay.
Averaging 8% of base salary equivalent in skills pay premium are: SAS Certified Professional: AI and Machine Learning; IBM Certified Specialist — AI Enterprise Workflow V1; Artificial Intelligence Engineer (AIE – all tracks); and Google Professional Machine Learning Engineer certifications.
“We’ve been tracking some of these AI-related skills for many years, updating every 90 days,” Foote said. “Others have been recently added. So, given all the volatility in the marketplace for skills cash pay premiums, there have been remarkable changes over time ,including most recently.”
Foote Partner’s findings are echoed elsewhere. Freelance work platform Upwork, which recently published its 2024 list of most in-demand skills, found that the rise of AI — especially generative AI in the last couple of years — has changed the top skills businesses seek from independent professionals. In particular, generative AI modeling, machine learning and data analytics are the top three fastest-growing data science and analytics skills, as well as among the most in-demand skills.
“In particular, skills in key programming languages commonly used in the development of AI — Python, Java, and SQL — rank among the top five most sought-after skills on the technical side in the US,” Ya Xu, head of data and AI at LinkedIn, said in a blog post.
Machine learning skills can command at least a 10% premium compared to the average tech worker, according to a survey conducted at the end of 2023 by tech staffing firm Dice. “But this is a fast-moving market where the demand is growing rapidly,” said Art Zeile, CEO of Dice. “I predict that this premium will only continue to grow as the gap between supply and demand for AI talent grows, and offering benefits such as continuous professional development and training will be key to retaining this top talent.”
A key differentiator in the job interview process now involves how a tech professional has upskilled themselves in the face of the growing demand for AI, Zeile noted.
“Now is the time to ensure that their skill sets encompass [LLM] theory and programming architecture, areas that may have been overlooked or haven’t been delved into fully,” he said. “Recruiters are looking for tech professionals who are quick on their feet and able to adapt to changes with agility and curiosity.”
In January 2023, AI or machine learning-related skill sets were referenced on 9% of tech job postings. Just over a year later, in February 2024, that figure had climbed to nearly 14% of all tech job postings, according to Zeile.
“As AI continues to evolve, its impact on organizations will be most prominent in key departments such as research and development, data analytics, and operations,” Zeile said.
To secure top AI talent in these areas, Zeile advised that companies:
- Invest in comprehensive recruiting strategies that show a full understanding of what a particular AI role actually requires — whether it’s machine learning, Python, or data science skills for tech jobs, or other content-centric skills such as copy writing and graphic design.
- Establish competitive salaries and provide opportunities for professional growth and development.
- Offer flexibility in the form of hybrid/remote work environments. Dice’s 2023 Tech Sentiment Report noted that remote work remains very important to tech professionals: 73% of those surveyed said it is “extremely” or “very” important to have the opportunity to work remotely at least three days a week.
While Amazon, Google, Meta and Microsoft are among the top 15 companies hiring for AI talent right now, according to Dice, there are a variety of factors tech pros must consider determining if Big Tech is right for them.
“While these Big Tech companies offer many opportunities for individuals with AI skills, candidates should also consider startups and other industries that align with their career goals and work/life balance preferences that would also still give them the ability to learn and flex their AI muscles,” Zeile said. “Ultimately, it is up to tech professionals to decide what companies most align with their values and what kind of industries they want to work in.”
Startups, Zeille said, often provide more room for innovation and growth, but may have less rigorous AI programs in place. At the same time, compensation at Big Tech companies might be higher, but work/life balance lower. Once a candidate has decided what is important to prioritize in their future role, they can job search accordingly.