AI skills top global talent shortage list for the first time, ManpowerGroup finds
The News
For the first time, artificial intelligence skills have surpassed all others to become the most difficult for employers to find globally, overtaking traditional engineering and IT capabilities, according to ManpowerGroup's 2026 Talent Shortage Survey. Based on responses from more than 39,000 employers across 41 countries, the survey found that 72% of employers reported hiring difficulty, down modestly from 74% in the prior year.
AI Model and Application Development (20%) and AI Literacy (19%) now lead the global ranking of hard-to-find skills, followed by Engineering (19%), Sales and Marketing (18%), and Manufacturing and Production (17%). Traditional IT and Data skills fell to seventh place at 17%, signalling a rapid realignment of strategic talent investment toward AI-driven capabilities. The Information industry faces the highest shortage at 75%, with Hospitality, Public Sector, and Health and Social Services close behind at 74%.
"The rise of AI skills to the top of the shortage list reflects how quickly the talent landscape is evolving," said Jonas Prising, ManpowerGroup Chair and CEO. "Companies are responding with upskilling and more flexible workforce models, recognising they will need to hire for potential, while building AI literacy across their workforce so people can apply new technology with judgment and confidence." Employers' primary strategies include upskilling and reskilling (27%), offering schedule flexibility (20%), and location flexibility (18%).
Why It Matters
This data has two immediate implications for TA leaders. First, if your organisation is trying to hire for AI-related roles, you are competing in the most talent-constrained market on the planet — and so is everyone else. The traditional sourcing playbook of 'post and pray' will not work for AI skills; you need to think about alternative talent pools, internal upskilling programmes, and geographic expansion into less constrained markets such as China (48% shortage) compared to Germany (83%) or France (74%).
Second, the survey's finding that core human skills — communication, collaboration, teamwork (39%), professionalism and work ethic (36%), adaptability (34%) — remain the most sought-after attributes overall is a reminder that while AI skills are scarce, the foundational interpersonal capabilities that make those skills productive are even more broadly demanded. A TA strategy that fixes solely on technical AI hiring without investing in broader workforce AI literacy and human skills development is only solving half the equation.
Taking Action
All action is situated in your corporate context. These are starting points, not prescriptions — choose what fits.
Connect
Who to talk with in your enterprise
Your head of L&D — Partner on an internal AI literacy programme that upskills existing employees rather than forcing every AI-capability hire to come from the external market. The 27% of employers prioritising upskilling are onto something.
Your sourcing team — Expand your geographic sourcing strategy to include markets with lower talent shortages. The gap between Germany (83%) and China (48%) represents a significant opportunity for remote hiring.
Your CHRO — Discuss whether your organisation's workforce planning model accounts for the shift from traditional IT skills to AI skills. If your talent strategy still treats IT and data as the primary technical skill gap, it is based on last year's data.
Inspect
What to take a closer look at
Audit your current job families and identify which roles would benefit most from AI literacy as a core competency — not just technical AI roles but any role where AI tools are becoming part of daily workflow. Compare this against your current hiring profiles to see where the gap is widest. Specific tool to look at: your workforce planning and skills taxonomy module within your HCM platform (e.g., Workday Skills Cloud, Eightfold Talent Intelligence, or Beamery's skills ontology).
Reflect
What to think about more deeply
The most interesting question isn't whether AI skills are the hardest to find — the data is clear — but whether your organisation is treating AI literacy as a specialist hire or a general workforce capability. If AI is reshaping every role, not just engineering roles, should every job description include some form of AI competency requirement? And if so, how do you hire for a skill that most of your current workforce does not yet have?