Four ways AI can be used to tackle the skills gap

What’s the relationship between AI and the skills gap? Cyril le Mat has a few ideas. 

While the skills gap has been an ongoing agenda point for many years now, the events of 2020 and the coronavirus pandemic have further intensified the challenge and companies are urgently seeking solutions to address the problem.

A recent study from Cornerstone found that whilst employers are increasingly prioritising skills development of their employees, there remains a confidence gap between employers and their people when it comes to skills.

90% of leaders feel confident in their ability to develop skills but only 60% of employees feel confident in their organisation’s ability to develop their skills for the future. With 2021 bringing further uncertainty, now is the time for companies to think outside the box and turn to smarter solutions.

The power of AI

AI has become a crucial tool across the business world, from helping to develop products to providing new insights into marketing efforts, but AI’s potential in HR to assist skills development remains elusive.

whilst learning programmes are indeed in place in organisations, the question is whether these are the right learning programmes for employees?

According to Deloitte, AI is mainly used in organisations to improve consistency and quality, with only 16% of organisations using AI to improve insights of workers. To truly address the skills gap, HR must understand how to squeeze out all the potential AI has to offer. So, what are the ways that AI can help skills development?

Identifying the right learning opportunities

Learning is integral to narrowing the skills gap yet lack of training is often cited as one of the main reasons for employees leaving their organisation. But whilst learning programmes are indeed in place in organisations, the question is whether these are the right learning programmes for employees?

Each employee has different learning requirements, career paths and goals, some of which are unknown to the employees themselves. Gathering and processing data on employee profiles and current learning programmes, AI can then analyse the value these programmes have for each employee.

Organisations can consequently provide competency-based recommendations and personalise learning opportunities to each individual and their goals. 

Internal mobility 

External recruitment is often seen as a one-way ticket out of the skills gap but whilst hiring new recruits can provide a fresh set of perspectives and skills, existing employees can also possess and provide the same required abilities if the opportunity is presented to them.


AI can be used to gain insights into the current skill sets of your employees and where these skills might be useful in other areas of the business – providing new internal recruitment opportunities. Categorising employees’ competencies and having the data in one place also allows HR to better understand and make quicker decisions about which roles require internal or external recruitment.

Predicting future talent requirements 

One of the primary features of AI is its ability to make predictions. For HR, this can be utilised both for employees and their future learning opportunities and for the business and its future talent requirements. To do this, companies must have interpretable career and employee data to be able to formulate models and make meaningful predictions.

For example, if an employee has previous experience in data analytics but is currently in a sales role, could they be a good match for a job in marketing and are they likely to succeed in a career switch? Is there a possibility that they could leave the company?

These are all questions that AI can provide a perspective on. It’s important to note, though, that externally inputted bias is taken into account when assessing employee data and AI products and algorithms must be routinely evaluated to alleviate any potential bias against race, gender, age etc.

Having predictions at hand means that companies can be one step ahead and make crucial decisions to prepare for the future.

Data-driven decisions for the wider business

AI solutions are cross-functional, and the interpretations they provide can also be used to gain understanding and drive outcomes across a wide variety of flexible and changing situations. Whilst utilising AI in HR primarily impacts employees and their learning requirements, the findings and patterns generated by algorithms can also help make decisions for the wider business.

For example, if HR were to use AI to uncover real-time market trends around key skills, this knowledge can then be used to make wider decisions on how to improve departments within the business. For instance, if there are positive trajectories in skills that your organisation currently doesn’t account for, is there a way they can be used?

Unlocking unknown skills in the market could be the key innovator to improve a whole department or business unit.

There’s no doubt that AI will continue to dominate the business world in the next year and beyond and it has great potential to become more than just a streamlining tool, especially in HR. Having a greater understanding of AI and the benefits it brings to people and their organisations will allow HR professionals to see the overall value of the technology.

It should also be said that even though AI brings an element of automation to the role of HR and L&D, it will never erase the human element of human resources. Ultimately, whilst AI can uncover trends and predictions it is up to humans to decide on how those findings can then be applied to the organisation.

By embracing the power of AI, HR can truly make a difference to the workplace and future-proof their organisation. 


About the author

Cyril Le Mat is director of data science at Cornerstone OnDemand



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