5 ways you can plug the widening AI skills gap at your business

Half of global technology leaders believe their organization has an AI skills shortage, and the capability gap has almost doubled in a year.

The newly released Nash Squared/Harvey Nash Digital Leadership Report found that almost twice as many technology leaders (51%), compared with last year (28%), said their business has an AI skills shortage — an 82% jump.

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The report by the recruitment specialist, the largest and longest-running survey of IT leadership in the world, found AI has jumped from the sixth-most-scarce technology skill to number one in just 18 months, the steepest and largest jump in any IT skills shortage recorded by the survey in more than 15 years of research.

To put that level of growth in perspective, the report found that the increase in demand for cyber capability, another sought-after skill, has risen far more gradually — from 16% in 2009 to 33% this year.

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So, why is the demand for AI rising so quickly? Nash Squared CIO Ankur Anand told ZDNET that the steep rise is linked to the speed of innovation.

“There’s an unprecedented pace of development in generative AI and the supporting large language models,” he said.

“If you look at OpenAI or Google, they come out with more advanced models every few months. Professionals must learn new skills quickly, and traditional learning methods can’t keep pace.”

In short, business leaders need a new approach to filling the AI skills gap. Here are five areas to prioritize.

1. Train existing staff

The research shows technology leaders and their companies have been slow to respond to the AI skills crisis, as more than half of companies (52%) are not upskilling in generative AI.

Anand said successful organizations have a business strategy that states what AI means to the enterprise and how talented professionals will address those concerns.

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In addition to tapping into expert resources, like academics at colleges who are aware of the talent and the skills coming through, smart business leaders focus on continuous learning and development for their professionals.

“That’s easier said than done, given the pace at which AI is progressing, but it’s important to foster a growth mindset within the organization,” said Anand.

“The best companies develop a career growth plan, with role-based certifications, whether for technology or softer skills. This clear career path becomes part of a continuous learning plan.”

2. Source AI-skilled experts

The research suggests almost two-thirds (65%) of tech leaders would choose an AI-enabled software developer with just two years of experience over one with a five-year career but without AI skills. So, what do the best AI specialists look like?

Anand said the priority is sourcing people with analytical and problem-solving abilities: “AI challenges are complex, so businesses need that strong mindset.”

Great professionals ally technical capabilities with business domain expertise, so they know how to use AI to help the organization achieve its desired objectives: “That combination is crucial.”

The best AI specialists also understand ethics: “If people deploy AI without the guardrails, they will not be able to develop solutions responsibly.”

Also: Why neglecting AI ethics is such risky business – and how to do AI right

Finally, Anand said great AI professionals share knowledge with others. “One of the things I’ve seen in my team is the importance of mentorship,” he said.

“The most talented people coach staff in the team and the rest of the business. This is a strong skill that business leaders need to focus on in the search for AI talent.”

3. Change your recruitment model

Tech leaders expect AI to fill one in five technology jobs in the next five years, but the report suggests AI is also changing operating models.

Anand said the first thing to recognize is that AI is changing traditional recruitment models.

“There are platforms that can screen resumes and assess skills,” he said. “AI is helping the industry move away from experience-based to skills-based assessment. Data-modelling techniques can also help companies predict the characteristics of a successful candidate for a role.”

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Second, those candidates are unlikely to focus solely on technological expertise.

The right talent will help companies augment human expertise with data-enabled capabilities, especially as the use of agentic AI increases during the next few years: “Soft skills, combined with a few hard technical skills, will be the perfect fit,” he said.

Finally, business leaders who look for this blended talent will cast their recruitment nets far and wide, covering diverse geographies, backgrounds, and capabilities.

“This means no one will be saying, ‘This job can only be filled by someone with five years’ experience,'” he said.

4. Engage with next-generation capability

Compared to the global average, organizations that attract, retain, and incorporate Gen Z viewpoints are twice as likely to be prepared for AI demands and one-fifth more likely to report a measurable ROI from AI.

Anand said successful business leaders understand the values of younger professionals and their desire for purpose in work, particularly around social responsibility.

“They look for organizations that align with these values,” he said. “You need to give them challenging opportunities so they feel like they’re part of a continuous learning process.”

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Access to those opportunities is crucial because the days of someone looking to work for one company for decades are gone.

“The younger generations gain knowledge quickly and get bored doing the same thing — they want to move on,” he said. “Organizations must understand the values of these generations and build career plans that suit them.”

Those plans should include flexibility across working locations and hours: “A good work–life balance is the number one factor for choosing an employer.”

5. Keep exploring new AI opportunities

The organizations most ahead with large-scale implementations of AI are 24% more likely to increase their tech headcount than their peers, mostly in areas of AI and data.

Anand said pioneering tech leaders stay one step ahead by not being scared of emerging technologies.

“There are still large enterprises that are keeping away from Gen AI because of fears about security,” he said.

“But if you don’t engage with these technologies, your people won’t stay. The best professionals need a challenging job. They recognize that AI could make mundane roles redundant in the future.”

Anand said smart business leaders foster a culture of experimentation to keep staff interested and excited.

“They reward the risk–taking because even the failures drive new learnings, and these lessons will deliver success in the future,” he said.

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