AI isn’t taking your job; the big threat is a growing skills gap

Despite sizeable tech layoffs over the past two years, a tech talent gap persists — especially for those trained on implementing and using generative artificial intelligence (genAI) tools. Consultancy McKinsey & Co. now projects that demand for AI-skilled workers will outpace supply by two-to-four times, a skills gap likely to continue at least until 2027.

That echoes what consultancy Deloitte wrote in a recent report. It found that corporate leaders continue to rate critical talent shortages as one of their greatest fears, even as job-seekers report despair about their hiring prospects. “And yet neither side seems prepared to address it,” Deloitte said in its report.

A ManpowerGroup survey of 40,413 employers in 42 countries found that 74% of employers still struggle to find skilled talent, with only 16% of execs confident in their tech teams and 60% citing the skill gaps as a key barrier to digital strategies. Along the same lines, Bain & Co. found that 44% of corporate leaders say limited in-house expertise has slowed AI adoption, with demand for AI skills rising 21% annually since 2019 and a shortage of talent lasting another two years.

The good news? Pay for AI skills continues to increase, growing 11% a year since 2019, according to Bain & Co. Workers with AI skills such as prompt engineering command a 56% wage premium (up from 25% last year), suggesting the value they bring, according to PricewaterhouseCoopers (PwC).

PwC said its data “does not show job or wage destruction from AI,” it shows growth across AI-exposed roles — even highly automatable ones. AI is boosting expertise, allowing workers to take on higher-level tasks. according to Joe Atkinson, PwC’s Global chief AI officer.

PricewaterhouseCoopers

“AI is at the forefront of corporate transformation, but without the right talent, businesses will struggle to move from ambition to implementation,” Sarah Elk, head of AI research for Bain & Co.’s Americas group, said in a statement. “Executives see the growing AI talent gap as a major roadblock to innovation, limiting businesses’ ability to scale and compete in an AI-driven world.”

While the gap has always been a challenge, gaining experience is harder than ever with AI taking over various work tasks, remote work weakening apprenticeships, and rising job complexity that require broader skills, Deloitte said.

The AI skills gap is driven by the rapid growth of AI technologies and the increasing demand for adoption across industries, according to Kelly Stratman, Ernst & Young’s global ecosystem relationships enablement leader. “Currently, 50% of enterprises with more than 5,000 employees have adopted AI solutions, and even more are considering doing so. At the same time, job postings requesting AI skills increased by 2000% in 2024 alone.”

By 2030, companies are expected to spend $42 billion a year on genAI projects such as chatbots, agents, research, writing, and summarization tools.

Key AI skills in short supply include prompt engineering, programming, and bias handling. Just as vital are soft skills such as adaptability, critical thinking, and emotional intelligence to ensure responsible, ethical AI use, according to Stratman.

PwC’s new AI Jobs Barometer shows demand for AI skills growing, even as the US job market slows. In response, PwC recently launched two AI tools that offer career development through tailored training and an AI coach that adapts to each employee’s goals and projects.

Bain & Co. projects AI job demand could reach up to more than 1.3 million in the US over the next two years, while the number of skilled workers available is on track to hit less than 645,000 — implying the need to reskill up to 700,000 US workers. “Companies navigating this increasingly competitive hiring landscape need to take action now, upskilling existing teams, expanding hiring strategies, and rethinking ways to attract and retain AI talent,” Bain’s Elk wrote.

The first response to the skills gap is to take an honest assessment of your organization and align AI projects with core business goals, “because really, this isn’t just a question of AI readiness, it’s about digital, data and AI readiness,” tech consultancy Thoughtworks wrote in a new report.

The key takeaways from Thoughtworks’ report:

Strategic alignment matters: 61% of leaders have a mature tech strategy compared to 19% of late adopters, showing its impact on digital and AI success.

Continuous improvement is essential: 93% see room for tech ecosystem improvement; 77% of leaders seek major changes.

Tech leadership boosts ROI: 53% of leaders report positive ROI, outpacing all other groups.

Justin Vianello, CEO of US technology talent training firm SkillStorm, said a shortage of qualified talent — especially in cloud, cybersecurity, and AI — is a bigger barrier to hiring than AI automation replacing jobs. Organizations struggle to find candidates with the right skills, certifications, and clearances, Vianello said, referring to shortages for government agencies.

While AI can boost productivity by handling routine tasks, it can’t replace the strategic roles filled by skilled professionals, Vianello said. To avoid those kinds of issues, agencies — just like companies — need to invest in adaptable, mission-ready teams with continuously updated skills in cloud, cyber, and AI.

The technology, he said, should augment – not replace — human teams, automating repetitive tasks while enhancing strategic work.

Success in high-demand tech careers starts with in-demand certifications, real-world experience, and soft skills. Ultimately, high-performing teams are built through agile, continuous training that evolves with the tech, Vianello said.

“We train teams to use AI platforms like Copilot, Claude and ChatGPT to accelerate productivity,” Vianello said. “But we don’t stop at tools; we build ‘human-in-the-loop’ systems where AI augments decision-making and humans maintain oversight. That’s how you scale trust, performance, and ethics in parallel.”

High-performing teams aren’t born with AI expertise; they’re built through continuous, role-specific, forward-looking education, he said, adding that preparing a workforce for AI is not about “chasing” the next hottest skill. “It’s about building a training engine that adapts as fast as technology evolves,” he said.