Bridging the AI skills gap

By Tracy Stanton, SVP Client Services, EMEA at Magnit.

  • 1 month ago Posted in

Organisations are now looking to the future, not just in terms of technology, but in the type of talent they are searching for. In the UK in particular, a surge in AI technology adoption has increased demand for professionals proficient in AI and machine learning. This follows on from the Government’s initiative to position the UK as a global leader in AI. It’s abundantly clear by now that AI is not just a momentary trend. The question now moves away from ‘should we be adopting AI?’ to ‘how can we ‘maximise the technology’s impact?’. The answer lies in finding the right talent.  


With AI skills in high demand and short supply, tech leaders must adopt innovative strategies to equip their workforces for evolving roles and meet the growing need for AI expertise. 

Skills-based hiring  


As AI skills are a relatively new area of expertise, companies may find themselves struggling to find talent through traditional avenues. Usual qualifications such as degrees, or extensive experience in the AI world, are much less common on CVs which causes problems for hiring teams trying to fill their organisations with the right talent. 

This means that teams have to shift their approach, focusing much more on skills that might not necessary be AI in definition, but are still instrumental in its development and deployment - such as machine learning, data analytics and Python.  It is crucial for organisations not only to identify workers with transferable technical knowledge but also those who possess soft skills such as critical thinking, communication, and adaptability.



External hiring is only part of the puzzle. Central to any effort to fully leverage AI is for companies to look inwards at their existing talent pool and develop a comprehensive upskilling effort in order to bridge skills gaps. However, it is imperative that these upskilling efforts align with a coherent AI strategy. Teams must evaluate what they are looking to achieve with their AI implementation to ensure that everything is geared towards that. If not, as AI technology is advancing so quickly, it could lead to a scattered approach that focuses on the wrong tools or skills at the time that can quickly become obsolete. 

Once a strategy is in place, teams must foster a culture of learning. This may involve partnering with an AI vendor or an academic institution who will be able to provide crucial expertise and insight into those skills that are needed and how best to train them. With this expertise on board, organisations can develop personalised learning paths for those who have the skills and desire to take an AI roles. Teams must ensure that these learning paths are engaging and utilise the full suite of educational platforms that now exist within the corporate world such as e-learning, or virtual on-the-go learning tools. 

Contingent workers


Clearly, acquiring and holding on to the right talent is an essential component of any strategy, however these efforts can often take time to fully implement. This becomes an issue as the rate of change in the AI space right now means any time that is lost currently, may have a compounding effect in the future. So what can businesses do to try and bridge skills gaps that exist at the moment, whilst they formulate their plans for the future? A great solution is to leverage contingent workers. These are workers that are brought in on an ad hoc or project basis for a very specific purpose. They often come with high proficiency in certain areas, and can provide crucial expertise and flexibility in a time of need for businesses. 

For example, an AI expert or a highly proficient technical expert could be brought in to propel AI implementation forward. The AI expert would assess current capabilities and suggest suitable technology, as well as how to implement it. Alternatively, a technical expert could be brought in to build a specific tool or platform to propel AI implementation forward. An enormous benefit of this approach lies in its flexibility. Once the task is fulfilled, the contract can end, allowing teams to move on. Additionally, if the demand for AI-related skills continues and the talent is a good fit, there is the possibility of converting the contractor to a full-time employee, providing an easy way to fill that skills gap permanently. This ability to solve an acute problem without a longer-term financial commitment can be a make-or-break factor for companies looking to keep pace with their competition. 

AI will reshape the future of work. As such, businesses must now be prioritising developing robust strategies to harness its potential effectively. Those firms that take a two-pronged approach – attracting top AI talent while simultaneously nurturing and upskilling their existing workforce – put themselves in the best position to succeed. 

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