UK businesses are experiencing real challenges when it comes to finding the right talent, with a recent survey finding that it faces one of the largest regional skills gaps compared to most other European countries. This growing gap could slow down innovation and make existing inequalities even worse.
While there’s often talk about AI taking over jobs, the real potential lies in people and AI working side by side, combining their strengths to improve decision-making, support people to learn new skills, and reveal diversity and inclusion gaps in business processes. Ensuring the mechanism for recruiting talent into a business is free of bias is just one example of how it can be used to close these critical skills gaps.
Despite the majority of companies (78%) reporting that they use AI in at least one business function, half of businesses view AI as solely a productivity tool, rather than a strategic enabler.
In my conversations with HR leaders and people managers in global companies, however, AI is increasingly becoming a tool to spot bias, personalise development, and make evidence-based decisions that strengthen both equity and performance.
To truly harness the transformative power of AI, it is imperative that businesses shift their perspective and embrace its potential as a catalyst for strategic growth and inclusive innovation.
What are the key challenges facing businesses?
Businesses across the UK are facing persistent shortages in areas such as digital, leadership, and STEM fields.
According to a report by Edge, many UK firms report a lack of adaptive and digitally fluent leadership capable of managing transformation and remote teams effectively. It is an issue which is arising frequently in my conversations with leaders and is backed up by a report from World Economic Forum which found that skill gaps are categorically considered the biggest barrier to business transformation, with 63% of employers identifying them as a major barrier over the 2025- 2030 period.
As the CEO of a business dedicated to diversity, equity, and inclusion, I recognise that too many organisations have traditionally recruited from a narrow pool, often favouring candidates from higher socio-economic backgrounds.
This approach overlooks the wealth of untapped talent residing in regions and communities where mobility and opportunity have historically been limited. By making a conscious effort to recruit and nurture diverse talent, we not only unlock critical skills that are scarce in the broader market but also address the urgent need for greater representation in rapidly developing technology sectors.
Women and minorities for example, who frequently hold qualifications equal to or exceeding those of their peers, must be given equitable opportunities to contribute and thrive within organisations.
Using AI to uncover what humans miss
AI can be used to analyse hiring data in companies to surface subtle patterns of exclusion, including language in job descriptions and historical promotion trends. By flagging where bias appears, this empowers HR teams to intervene early and create more equitable talent pipelines.
Unilever for example, mitigated bias during its talent recruitment by stopping visits to the campus for young talent recruitment, where recruiters could have been influenced by affinity bias, and instead relied on AI algorithms to scout for early career individuals. It also used social media to advertise the roles, and screened videos using AI to assess softer skills. As a result, 450+ hires were made globally, with a high percentage of gender diversity.
However, it’s vital that the data AI learns from does not carry bias. For example, AI trained on data on past hires can then lead to screening favouring individuals with similar profiles.
Responsibility therefore lies with the people who design and oversee these systems, including developers, vendors and HR leaders. It’s vital that the data used is not flawed through ensuring data is audited, and models are continually retrained to prevent outdated bias.
It’s crucial that AI is seen as a partner, not a substitute for human judgement.
Empowering underrepresented employees
AI is also increasingly being used to uncover the hidden patterns in workforce data that reveal where skills gaps exist, and which employees have leadership potential that currently isn’t being harnessed. By analysing performance metrics and learning behaviours, AI can generate actionable insights that inform the design of training.
It can also support managers to provide more targeted insights-based training that is specific and relevant to an individual. For example, if a mid-level woman in a technology firm has demonstrated strong technical performance, but is underrepresented across leadership, AI can analyse historical data, participation in training, mentorship opportunities, to ascertain which pathways successful employees historically take in the business, and the gaps in support for an individual.
Transparency is key
If businesses are to tackle the ongoing skills crisis, it’s vital that human oversight is maintained to ensure biases do not exist in the models. Development and HR teams must therefore receive training on DE&I principles including bias reviews, continual learning and updates. Diverse AI development teams also ensure AI systems are designed with multiple perspectives.
With the UK Employment Rights Bill proposing establishing dedicated regulatory bodies and frameworks to oversee AI use and compliance, the businesses that get ahead now will not only ensure they comply but ensure they remain competitive to future and existing staff, ensuring they can continue to innovate with the right talent.
