Artificial intelligence may be scaling across the enterprise—but the talent required to make it work is not.
New data from ManpowerGroup’s 2026 Talent Shortage Survey signals a decisive shift in the global labor market: for the first time, AI model and application development (20%) and AI literacy (19%) rank as the hardest-to-fill capabilities worldwide. Engineering roles, long the gold standard of scarcity, have been pushed aside. Traditional IT and data skills now sit in seventh place.
The headline number is equally stark: 72% of employers report they still cannot find the skilled talent they need.
If the early AI era was defined by experimentation and proof-of-concept pilots, 2026 is shaping up to be defined by workforce constraints.
From Innovation Gap to Talent Gap
For years, the tech sector’s primary concern was access to cutting-edge tools, infrastructure, and compute power. Today, access to AI platforms is widespread. Open models, enterprise copilots, and automation frameworks are proliferating.
The bottleneck has shifted.
Organizations can license AI capabilities. They cannot license institutional AI fluency.
AI model development topping the shortage list suggests enterprises are moving beyond surface-level adoption. They want proprietary models, domain-specific applications, and deeper integration into core business systems. That requires specialized talent—machine learning engineers, prompt engineers, data scientists—who are in finite supply.
More telling is AI literacy ranking close behind.
This isn’t just about elite developers. Employers now need managers, HR leaders, operations teams, and frontline staff who understand how AI systems function, where they create risk, and how to apply them responsibly. Broad-based AI fluency is becoming as fundamental as digital literacy was a decade ago.
A Persistent 72% Problem
The overall shortage rate—72%—confirms the challenge is not easing. It’s evolving.
Previous surveys highlighted shortages in engineering, skilled trades, and traditional IT roles. Those gaps remain, but the epicenter has shifted toward hybrid capabilities: technical depth combined with business application.
In short, the market isn’t short on degrees. It’s short on adaptable, AI-enabled talent.
That reality will take center stage at Mobile World Congress 2026 (MWC) in Barcelona, where more than 109,000 professionals and representatives from 95% of the world’s leading IT and telecom companies are expected to gather March 2–5.
While vendors will showcase next-gen devices, AI-powered networks, and automation breakthroughs, executives across the C-suite are wrestling with a more fundamental question: Who will run all this?
The Human Edge at MWC 2026
ManpowerGroup and its tech talent brand Experis plan to spotlight these findings throughout the conference, emphasizing what they describe as the “human edge” in the AI era.
Mara Stefan, VP of Global Insights at ManpowerGroup, argues that competitive advantage no longer hinges solely on model sophistication. The differentiator is workforce capability and clarity around future skills.
That framing reflects a growing consensus across HR and technology leadership: AI transformation is a workforce transformation.
Upskilling as the Primary Defense
One insight stands out from the survey: upskilling and reskilling existing employees is now the number one employer response to structural talent scarcity.
That shift has significant implications for HR tech and workforce strategy.
External hiring alone cannot close the AI skills gap. The supply of experienced AI developers and strategists simply isn’t large enough. Instead, companies are building “hybrid superteams”—blending human expertise with AI tools and investing heavily in rapid relearning cycles.
At MWC’s Talent Arena, Experis will host sessions focused on hyperautomation and agentic AI applications in talent acquisition and workforce transformation. The emphasis is practical: how automation can help address the very shortages it exacerbates.
Hyperautomation—combining AI, robotic process automation (RPA), and analytics—promises to reduce manual workloads. But it also demands new skills to design, oversee, and optimize those systems.
It’s a paradox defining this era: AI can alleviate talent shortages, but only if organizations have enough AI talent to deploy it correctly.
Four Forces Shaping the Future of Work
During a main-stage session at MWC, Stefan will present insights from The Human Edge: Global Future of Work Trends report, outlining 16 trends across four macro forces:
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Hybrid Superteams
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Rapid Relearning
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Changing Norms
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The Succession Crisis
Together, these forces describe a labor market in flux.
Hybrid superteams suggest humans and AI will operate in tandem rather than in opposition. Rapid relearning reflects compressed skill half-lives—what’s cutting-edge today may be obsolete in 18 months. Changing norms point to evolving expectations around flexibility, purpose, and digital fluency. The succession crisis underscores demographic shifts as experienced leaders retire without clear pipelines of AI-ready replacements.
Each trend intersects with the same underlying challenge: skills alignment at scale.
The Competitive Stakes
For CTOs, the AI talent shortage affects deployment timelines and innovation velocity. For CHROs, it reshapes workforce planning and learning strategy. For CEOs, it directly influences revenue growth and market position.
Companies that solve the AI talent equation gain compounding advantages. They innovate faster, automate smarter, and adapt more quickly to regulatory and competitive shifts.
Those that don’t risk falling into a familiar trap: owning powerful technology that never fully translates into performance.
Live recordings of ManpowerGroup’s Work Intelligence Lab podcast at MWC—featuring leaders from IBM, EY, and other global players—will likely reinforce the same message: the AI race is no longer just about models or infrastructure.
It’s about people.
And right now, the data suggests there aren’t enough of them.
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