Why AI Hiring Is So Difficult

Many businesses seeking to hire AI professionals are likely to face extensive AI hiring challenges, due to them competing with multinational technology companies and venture-capital-backed startups for a limited pool of highly skilled technical talent.

The AI talent shortage is likely to widen over the next few years, unless urgent action is taken to increase the supply of AI professionals. For organisations aiming to leverage AI, the focus should not only be on attracting AI talent, but also on improving compensation and recruitment strategies to secure and retain it. Additionally, businesses should consider interim approaches such as engaging contractors or upskilling existing employees while building longer-term capability.

The main challenges facing AI recruitment

According to the latest UK Government AI talent market data, 35% of businesses are struggling to fill AI roles. In the Government’s Department for Science, Innovation and Technology (DSIT) research, they found that 60% of organisations reported the most common factor that prevented AI adoption was a lack of AI skills and expertise within organisations. As a result, some businesses may be less agile and competitive on the market, as they delay, scale back, or abandon plans to use AI to improve operational efficiency and drive innovation.

Misalignment between the supply and demand of niche and senior leadership AI talent is threatening AI adoption

One of the reasons AI hiring is so challenging currently is the complete misalignment between supply and demand in the sector. There are far more organisations seeking AI talent than there are qualified professionals available. With more than 80% of executives planning to increase AI investment over the next few years, as reported by IT Desk UK, this issue will likely continue to worsen.

The challenge becomes even greater when organisations are recruiting for specialist positions or niche skill sets. Beyond technical expertise, employers are increasingly seeking professionals who can combine AI knowledge with strong business and leadership capabilities. Many businesses are finding it particularly hard to secure niche or senior and leadership-level AI talent. As reported by People Management, in 2025, certain skills were particularly difficult to secure within AI recruitment, such as critical thinking (35% of businesses agreed), cross-functional leadership (24%), and leadership and initiative (23%).

As a result, organisations face intense competition for a limited pool of candidates who possess both the technical expertise and broader business skills needed to lead and deliver successful AI projects.

The AI talent shortage is causing significant salary inflation

The scarcity of experienced AI professionals has contributed to significant salary inflation across the market, which has had a knock-on effect on businesses’ ability to hire AI professionals. The sky-high AI salaries offered by Big Tech companies, as reported by The Times, with compensation packages of up to £630,000 per annum in London, have played a role in raising compensation benchmarks in the market.

For example, the base salary of a software engineer in London averages at at £66k, according to Indeed, whilst an AI/ML engineer in London earns £20k more at £86k, as seen on Indeed.

As a result, even well-funded scale-ups and established organisations often struggle to compete on total compensation packages, when considering salaries, benefits, equity, and bonuses. This can have a knock-on effect on the success of AI initiatives, as businesses may be forced to hire smaller, more generalist teams in order to facilitate relevant skills within budget. In some cases, companies may divert a significant proportion of AI investment funding away from research, development, and implementation activities towards recruitment and employment costs.

Traditional recruitment processes are ineffective when hiring AI talent

Many organisations struggle to hire AI professionals because their recruitment processes have not evolved in line with the changing nature of AI talent. Traditional recruitment practices often favour candidates with conventional computer science degrees; however, the rapid development of AI means that formal qualifications do not always reflect the most current skills and knowledge. Therefore, some of the strongest candidates may come from non-traditional or linear backgrounds.

Several companies are now providing apprenticeships, which allow professionals to develop their AI skills while on the job, ensuring businesses keep up with industry demand. In fact, the UK Government have reported that AI apprenticeships have risen from 3% of all AI hires in 2020 to 19% in 2025, mirroring this need.

Additionally, partnering with an AI recruitment agency can help organisations tailor their hiring processes to the AI industry and attract more candidates.

Many hiring managers have difficulty assessing AI skills

Businesses may also face difficulties accurately assessing AI engineers and other skilled professionals during the recruitment process. Given the pace at which AI technologies, tools, and frameworks evolve, hiring teams may lack the specialised expertise needed to effectively evaluate candidates’ technical capabilities. This can lead to inconsistent hiring decisions, overlooked talent, and widening AI skills gaps. Consequently, businesses may struggle to build AI teams effectively, potentially exacerbating existing skills shortages and slowing the successful delivery of AI initiatives.

Global competition and access to talent are reducing local talent pools further

AI recruitment challenges are being exacerbated by growing global competition for skilled workers. An international shortage of AI talent means demand is high across organisations of all sizes, from multinational corporations to venture-backed startups and small businesses.

Organisations are no longer competing only with local competition, but with firms across the world. According to Deel, among the workforces of the top 100 US startups, the UK was the largest source of international tech talent, with UK-based employees making up 12.2% of their combined workforces. This reflects a broader trend in which US firms increasingly view English-speaking countries such as the UK, Canada, and Australia as key talent pools.

Remote and hybrid working models have further intensified this pressure by making it easier for overseas employers to hire UK-based talent. As a result, UK businesses face increasing pressure to offer more competitive salaries and overall compensation packages to attract and retain skilled workers.

Why AI hiring challenges continue to worsen

Rapid tech evolution

The pace of change and innovation within AI has accelerated significantly, in alignment with new technologies and skills evolving rapidly. Some of the latest emerging AI skills include:

• Deploying agentic AI systems
• Building custom Retrieval-Augmented Generation (RAG) pipelines
• Evaluating and testing AI systems
• Developing multimodal AI applications
• Prompt and context engineering

The constant churn of new technology and methods exacerbates skills shortages. It can also make organisations struggle to define exactly what skills they need, leading to unrealistic job specifications and ineffective recruitment processes, which cost businesses more money.

GenAI hiring explosion

The widespread adoption of generative AI (GenAI) has significantly accelerated demand for AI professionals. Since the emergence of large language models (LLMs), organisations across sectors rushed to build internal capabilities and launch AI-driven products and services.

This sudden increase in demand created a hiring surge that has been difficult for organisations to keep up with. Therefore, businesses are now competing for the same small group of specialists with experience in generative AI, natural language processing, prompt engineering and AI product development. Consequently, hiring timelines have increased, and salary expectations have risen further.

Lack of established talent pipelines

AI hiring problems are exacerbated further by the underdeveloped AI talent pipeline. The current academic channels cannot keep up with demand in the AI talent market.

Although universities, training providers, and government initiatives are expanding AI-focused programmes, it takes years to develop the technical expertise and commercial experience that employers require. Then, due to the consistent evolution of AI technologies, the skills professionals learn in the first year of their course, for example, may become significantly less relevant by the time they graduate. This is why it is so challenging to develop useful formal education courses for AI.

However, one thing is clear: until the supply of skilled professionals increases significantly, organisations are likely to continue facing challenges recruiting AI talent.

Poor AI readiness is making AI hiring more challenging

Another consideration is whether companies are actually ready for AI. Successful AI operations need an established and well-maintained data infrastructure, which provides a solid foundation for all AI initiatives. This is often referred to as ‘AI readiness’.

Some companies may decide to move ahead and engage AI engineers and architects straight away, but without a robust data infrastructure, an effective governance framework, and clear business objectives, even the most talented AI professionals will struggle to deliver meaningful outcomes.

Before investing heavily in AI recruitment, organisations should assess whether they have:

• A reliable and accessible data infrastructure
• Strong data governance and security policies
• Clear business problems or objectives that AI can solve
• Executive sponsorship and organisational buy-in
• Processes for measuring AI performance and ROI

Without these foundations, businesses risk hiring expensive AI talent before they are in a position to fully utilise their expertise. In many cases, organisations may benefit from first strengthening their data capabilities and internal AI strategy before scaling their AI hiring efforts.

AI talent shortages are increasing project failure risks

Organisations that experience AI recruitment difficulties are more likely to see their projects fail. Without the right professionals in place, companies will experience delays and vital deadlines being missed. Additionally, if businesses cannot hire deployment-focused or commercially-minded specialists, they may struggle to move AI projects beyond proof-of-concept stages to generate measurable business value.

Talent shortages can place excessive pressure on existing teams, increasing the likelihood of burnout, knowledge gaps, and implementation errors, which may lead to much worse outcomes if ineffective AI initiatives are deployed to users.

However, businesses also need to focus on ensuring that they have a strong internal AI strategy that has buy-in from executive leadership through to operational teams. A weak strategy, unclear objectives, or misalignment on priorities can also contribute heavily to failed AI projects.

How contractors can address AI recruitment difficulties

As a consequence of intense AI talent shortages, many organisations are turning to AI contractors and temporary staff to fill vital gaps in AI projects.

This approach allows businesses to access highly targeted expertise, such as model developers, data engineers, prompt engineers, or AI governance experts, on a short-term basis to cover essential AI skills gaps. This can be useful for organisations that are looking to get a project over the line or as a way of accessing certain skills until they are able to hire a permanent team member or upskill a current employee.

Key takeaways…

As demand for AI workers increases, many businesses are experiencing barriers to adopting and scaling AI systems within their operations. From persistent talent shortages to rapid technological evolution, several factors are creating an increasingly difficult AI recruitment landscape.

Without action to strengthen talent pipelines and develop a greater supply of skilled professionals, particularly as demand continues to accelerate across industries, the UK’s AI recruitment challenges will likely deepen.

Experiencing AI hiring challenges?

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