New research from IDC projects that over 90% of global enterprises will face critical AI skills shortages by 2026, with sustained gaps threatening $5.5 trillion in losses from delayed products, missed revenue, and impaired competitiveness. Meanwhile, the UK government’s own AI Adoption Research — published in January 2026 — found that just one in six British businesses currently uses AI, with natural language processing and text generation accounting for 85% of existing use cases.
The disconnect between AI spending and AI readiness is becoming impossible for markets to ignore.
Big Tech Is Spending. Workforces Aren’t Ready.
The numbers tell a stark story. Meta Platforms (META), Alphabet (GOOGL), Microsoft (MSFT), and Amazon (AMZN) have collectively committed to more than $300 billion in AI-related capital expenditure for 2025-2026. Nvidia (NVDA) continues to post record quarters on the back of insatiable data centre demand.
But according to Deloitte’s 2026 State of AI in the Enterprise report, only 34% of organisations are using AI to genuinely transform their operations. The remaining two-thirds are either making surface-level changes or simply bolting AI onto existing processes. The biggest barrier cited by leaders surveyed? Insufficient worker skills.
The World Economic Forum estimates that nearly 40% of global jobs are exposed to AI-driven change, yet its January 2026 research found that professionals consistently underestimate the technology’s impact on their own roles. This perception gap delays the upskilling that businesses desperately need.
Small Business Is Falling Further Behind
The skills gap hits hardest below the enterprise level. A YouGov survey of UK SME leaders found that only 31% are currently using AI-powered tools, with nearly seven in ten having no formal plan for adoption. The British Chambers of Commerce reported in September 2025 that while 46% of B2B service firms have adopted AI, just 26% of consumer-facing businesses and manufacturers have done the same.
Future Business Academy, an AI training platform serving small and mid-sized businesses across the UK and Ireland, reports that the primary barriers for its audience remain the same: lack of practical knowledge, uncertainty about where to start, and confusion over which tools actually deliver returns. These aren’t technology problems. They’re training problems.
The IMF’s January 2026 analysis reinforced this pattern globally. Regions with higher demand for AI skills saw employment in AI-vulnerable occupations fall 3.6% over five years compared to areas with lower demand — suggesting that without adequate training infrastructure, AI adoption risks widening economic divides rather than closing them.
Where the Investment Opportunity Sits
The AI training and workforce development market is expanding rapidly as a direct consequence. Several publicly traded companies are positioning themselves to capture this demand.
Coursera (COUR) has seen growing enterprise enrolment in AI and machine learning courses, with business-to-business revenue becoming an increasingly significant share of its top line. Udemy (UDMY), which published research on the AI perception gap alongside the World Economic Forum, continues to build out its enterprise AI training catalogue.
Microsoft (MSFT) is playing both sides — spending aggressively on AI infrastructure while simultaneously monetising workforce readiness through LinkedIn Learning and its Copilot ecosystem. The company’s ability to sell the picks and the shovels and the training manual gives it a unique position in the AI value chain.
Salesforce (CRM) has invested heavily in Trailhead, its free learning platform, while pushing AI agent capabilities through Agentforce. The strategy mirrors a broader trend: major platform providers are recognising that their AI products only generate returns when customers know how to use them.
Beyond individual stocks, the broader ed-tech and professional services sectors stand to benefit from what Pearson’s recent research calls the “learning gap” — the space between what AI tools can do and how well workforces can actually use them. Pearson’s modelling estimates that closing this gap through AI-augmented workforce development could add between $4.8 trillion and $6.6 trillion to the US economy alone by 2034.
The Bottom Line for Investors
AI infrastructure spending will continue to dominate headlines. But the companies and sectors that solve the human side of the equation — training, adoption, and workflow integration — may offer a more durable investment thesis.
The skills shortage is not a temporary growing pain. The IMF describes it as a structural challenge that has persisted for fifty years, with AI simply adding urgency. IDC’s $5.5 trillion figure represents lost economic output, not speculative upside.
For markets, the implication is straightforward: AI’s productivity promise depends entirely on whether workforces can keep pace with the technology. The organisations investing in that readiness — whether they’re Fortune 500 companies building internal academies or specialist training providers serving the mid-market — are addressing the single largest constraint on AI’s return on investment.
The AI trade isn’t just about who builds the models or manufactures the chips. Increasingly, it’s about who closes the skills gap.
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