Recent research suggests that AI has created the world’s largest and fastest-developing financial services technology skills shortage in over 15 years. Dalvinder Kular, assistant editor at FStech, explores the current talent challenges firms are facing and how they can begin to plug the gap.

Artificial Intelligence (AI) is transforming the global economy, reshaping industries, and redefining the future of work. This is particularly evident in financial services, where AI is driving advances in everything from fraud detection and algorithmic trading to customer service automation and compliance.

However, while the technology advances, a critical shortage of skilled workers is emerging that could disrupt the rapid progress that has been made so far.

According to a recent report, AI has created the world’s largest and fastest-developing financial services tech skills shortage in more than 15 years.

The 2025 annual study by recruitment giant Harvey Nash and digital consultancy Nash Squared, which surveyed over 2,000 technology leaders across 62 countries, found that AI has jumped from the sixth most scarce tech skill in financial services to number one in just 18 months. This represents the steepest and largest jump in any technology skills shortage recorded in the sector since the year 2000.

The research also revealed that just over half of technology leaders said they are suffering a skills shortage compared to 28 per cent last year.

The companies behind the research said that the ongoing skills shortage is linked to “significant growth” in AI investment, with around 90 per cent of global technology leaders now reporting they are either piloting AI or investing in AI developments, up from 59 per cent in 2024.

Upskilling towards success

To meet the demand for AI talent, companies are embracing a blend of internal upskilling, external recruitment, and partnerships with training providers.

Anna Brailsford MBE, chief executive of Code First Girls, thinks that upskilling has emerged as the most viable solution in the short-term.

Code First Girls, which provides technology, coding and AI skills in the UK, has trained over 200,000 women and non-binary individuals in coding and digital skills. Its Code First Teams programme equips existing employees, from both technical and non-technical backgrounds, with critical skills in AI, cyber and data.

“The most successful upskilling programmes are built around tailored learning pathways based on role, career stage, and business priority,” says Brailsford. “Upskilling must be accessible and inclusive, especially for underrepresented groups.”

NatWest, Barclays and Goldman Sachs, have all partnered with Code First Girls for AI training. These have delivered promising results, with NatWest reporting a 95 per cent employee retention rate among participants.

Gareth Randell, who has 20 years of experience at firms RBS, NatWest, and UBS, says that upskilling internal teams in financial services vital “but not a silver bullet.”

“You can’t just send someone on an afternoon course and expect them to be an AI expert,” says Randell, who is currently programme delivery director at Google transformation partner Qodea. “It takes time and knowledge to develop these skills.

“If you do have people internally with the skills to train your team, it’s likely they will be in high demand elsewhere.”

Rethinking the hiring process

Along with upskilling their employees, firms are getting more creative with their hiring processes.

Peter Weston, associate director - financial services at Harvey Nash says that as AI is not a separate discipline, there are not hordes of AI experts out there. He thinks it is a skillset that needs to be integrated into every role.

“Technical and data aptitude is becoming fundamental to any hire, even roles you would not immediately think of as having a requirement” he says. “The reality is that AI now spans all business units – legal, marketing finance, sales and operations – which in my view, means that the time has come when AI capability or at least aptitude and willingness to learn should be factored into hiring decisions.

“You possibly wouldn’t hire someone who said they couldn’t or won’t use Microsoft Office, the same may be true now if a candidate has no interest whatsoever in AI.”

Weston highlights that in the firm’s recent report, two thirds of tech leaders said they would hire someone with genAI skills and two years’ experience over someone with five years’ experience but no genAI skills.

“HR has a leading role to play here in ensuring that hiring managers are factoring AI into their assessment processes and talent decisions,” he adds. “For most roles, AI aptitude should be seen as a significant contributing assessment factor, and for some roles, it may already be a deal-breaker.”

Randell points out that within financial services there is more demand for human skills, such as relationship management and empathy, than there is for technical skills.

“We are still in an era where AI is very much a support to human endeavour, as such the creative and problem-solving skills of people is growing in value,” he said.
Additionally, there are transferable skills that some people may already have and can build on.

“While the impression is that AI is a complete bolt out the blue, in reality, similar jobs have been around for many years,” Randell adds. “For example, on the technical side, machine learning engineers build products using models in production and AI agents and AI applications are effectively models in production – the main difference is the nature of the model.”

Shrinking the talent pool

Many firms are starting to use AI in the initial stages of the hiring processes to filter out candidates who may not have the right qualifications or experience. But Brailsford warns that AI may be perpetuating the skills crisis by creating issues through discriminatory algorithms.

AI systems trained on historical data can exacerbate existing inequalities. In hiring, this means algorithms may favour candidates who mirror previous hires that are often male, white, and from elite institutions.

If unchecked, these biased systems can embed discriminatory practices into the hiring process itself, creating a self-fulfilling cycle of underrepresentation and ultimately a further narrowing of the talent pool.

“Financial services firms are increasingly deploying AI and digital tools for core roles associated with men,” Brailsford points out. “However, with the lack of workforce training to effectively understand and use these tools, a gap is forming, and this is having an impact on efficiency and competitiveness.”

She adds that diversity remains a serious issue in the tech sector, with women representing just 22 per cent of IT professionals.

“By 2026, there may be only one woman for every 115 tech roles, further narrowing the potential talent pool,” Brailsford adds. “This is a critical challenge with AI, where gender stereotypes and equalities present in data sets and algorithms can perpetuate existing societal biases.”
Scaling back

While some firms scramble to find AI specialists, others are using the emerging technology to save money and scale back their current workforce. High profile tech giants including Intel and Microsoft have announced job cuts while executives from Amazon and BT have made hints that AI could replace part of the workforce.

In the financial services sector, the impact is more nuanced. While automation is replacing certain tasks, such as those in administration, AI is also creating new opportunities.
Weston points out that insurance companies are using AI in underwriting and pricing quests while banks are using AI models within trading, reducing the amount of traders in a number of locations.

“Specific to the investment management sector, we have seen the use of AI for performance and client reporting and automating very manual tasks across the industry,” he adds. “This will be commonplace for the industry very soon – leaving those behind who have not adapted.

“That said, there is still understandable push back and caution in the industry to realising some of the potential gains to be had from AI. Concerns around data integrity and also the models AI are based on, if incorrect could have serious financial consequences for the business and the industry.”

The report from Nash Squared and Harvey Nash report found that organisations furthest along in their AI implementation journeys are 38 per cent more likely to increase their tech headcount than their peers.

“AI is changing the kind of people leaders want to hire, all roles now have an AI or data element,” Weston said. “The biggest risk is not that AI takes jobs, but that people fail to adapt to AI being part of their role.”

Talent pipeline

Rohan Malhotra, associate head of careers services at ESCP Business School, warns of a sharp decline in graduate and early career recruitment. According to him, KPMG’s graduate recruitment has dropped by one third in the past year, while Deloitte has cut 18 per cent of early careers roles. EY and PwC have also reduced these opportunities by 11 and six per cent respectively.

He said these reductions are largely attributed to AI tools now handling the admin-heavy tasks traditionally assigned to junior employees.

“This trend is already reshaping access into the professional workforce and traditional early roles are disappearing, meaning fewer hands-on training opportunities for young people,” he adds. “If this continues unchecked, we risk creating a world where there are senior experts and AI systems, but fewer early-career professionals learning how to become future leaders.”
However, Malhotra also points out that this shift could lead to companies “reimagining” the early careers experiences.

“Companies can create more meaningful, AI-integrated training pathways where new talent learns to work alongside AI from day one,” he says. “The challenge is making sure these experiences exist and are accessible to all."

A long-term solution to filling the AI skills gap is to ensure that people have the skills they need before entering the workforce.

“To build a sustainable pipeline of tech and AI talent, we need to start much earlier in the education system,” Brailsford says. “Encouraging students and young people to pursue careers in AI begins with early exposure, from primary through to secondary education.
“In addition, schools lack clear tech career advice, tech pathways, and clear messaging that AI roles are both inclusive and growing in demand.”

For example, the British government has started to recognise the need for AI skills in the workplace with the rollout of training schemes, while multinational companies like Amazon are implementing courses for their employees.

“These programmes help demystify the technology, offer hands-on experience, and show practical routes into employment,” explains Malhotra. “To further encourage young people it’s vital that schools, universities, and employers highlight these pathways early.

“This can be by showcasing success stories, integrating AI literacy into the curriculum, and offering internships or mentorships tied to AI-driven roles."

Brailsford thinks that programmes like those run by Amazon and Google are a good start, but they must do more to prioritise non-traditional learners such as those from underrepresented backgrounds and career switchers.

Randell says that many young people are being encouraged to train in AI, but there is still a gap between education and the skills employers actually need. Ultimately, the sector moves at such a pace that learning on the job is essential.

“With much of AI’s rapid evolution happening behind closed doors in the private sector, it’s nearly impossible for educators to keep up,” Randell adds. “Initiatives like Experience AI and the AI Campus in London are promising, but stronger public-private collaboration is essential to truly bridge the gap.

“By co-designing curricula, expanding access beyond tech hubs, and focusing on practical, career-ready training, the next generation can be given a real-shot at getting to grips with AI.”

The future outlook

As AI continues to reshape industries at speed, companies need to hire and train professionals who can develop, manage, and apply these innovative technologies.

But across many industries, including financial services, AI adoption is often accelerating at a pace that existing talent pools are unable to keep up with.

Firms are taking a number of steps to address this, from upskilling current employees to seeking out those with a varied skilled set. However, these efforts must be inclusive and forward-looking, ensuring that women, underrepresented groups, and non-traditional learners are not left behind.

If AI becomes a tool only wielded by a narrow demographic, the industry risks reinforcing systemic inequities and further shrinking the available talent pool.

Firms must realise that plugging the AI skills gap isn’t just a technical or hiring issue, it is a structural one which requires a long-term investment in education, curriculum reform, and public-private collaboration that begins well before individuals enter the workforce.

At the same time, financial services providers must remain agile and human-led, recognising that while AI is revolutionising the industry, human creativity, empathy, and problem-solving skills cannot be replaced by technology.

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