The Age of Automation: Mind the AI Skills Gap

The Age of Automation: Mind the AI Skills Gap

Back in 2016, I discussed the differences between the roles of a data scientist and data engineer and their equal importance within a big data team. Fast forward to 2017, and the predicted increased demand for big data professionals, data scientists and data engineers has led to a huge AI skills gap that causes a headache for businesses wanting to bring in specialists to take full advantage of AI’s full capabilities.

What is causing the AI skills gap?

The rising tide of AI and automation has led to increased benefits for businesses as a result of being able to upgrade legacy systems and improve data analytics, which in turn leads to results such as improved operational efficiency, reduced costs, and increased business and product opportunities.

These benefits have led to 42% of businesses planning to increase spending on AI over the next five years –with one in five already doing so– and more are bound to follow. Gartner analysis has shown that whilst this might be the intention, enterprises are struggling to implement AI driven data strategies and solutions, and herein lies the problem: there is not enough AI and data talent to meet demand.


So, what needs to be done?

Education is an obvious first place to start when it comes to filling the AI skills gap. Research has found that too few are choosing to learn STEM from an early age and a disappointing number of children and in particular girls, are signing up for computer science courses.

This means the view of the STEM sector needs remodeling to appeal to young people and show them that a career in that industry is inclusive and exciting, and doesn’t just require technical ability but also alternative skills of creativity, problem-solving, teamwork and analytical thinking.

The government is playing a part in offering a long-term solution to filling the AI skills gap and are attempting to get more people interested and invested in AI and machine learning with the introduction of the digital strategy earlier this year, which has promised 4 million free digital skills training opportunities, partnering with businesses to do so.


Nurturing talent

Technology businesses have a lot to offer when it comes to filling the AI skills gap, especially so when they are open-minded to upskilling and training data professionals. This means that as well as education, they can play a part by recruiting from the bottom up and sourcing the data talent that can be taught skills in AI and machine learning.

Hiring managers should be identifying other transferable skills such as creativity, problem solving and ethics. Having an understanding and knowledge of ethics deserves more recognition than it gets when it comes to AI and machine learning for the future; AI technologies face ethical dilemmas every day, from how to exclude racial and gender prejudices from automation, to how self-driving cars decide between the lives of passengers to those of pedestrians.

Many businesses willing to invest in skills and training will be thinking long term, nurturing and training their own and possibly new talent. This will be based on recruiting a very specific set of skills and education rather than experience which can make it difficult for SME’s and start-ups to achieve the goals they need to recruit fast, and so find themselves selling hard, having to compete on salary and benefits whilst struggling to stretch spend on new hires.

When it comes to recruiting AI professionals, the lack of skilled candidates is making candidate attraction and retention pivotal in the recruitment process. Competition for this shallow pool of candidates is fierce and candidates not only have a few opportunities to explore but also the equal amount of offers available to them that also include huge salary offerings. In such a candidate-driven market, it is hard for smaller businesses to compete in attracting AI talent.

I work with the talent and businesses on an in-depth level to really understand what they want and help match the right candidate to business based on what kind of challenge, product, innovation autonomy and opportunity (e.g Equity) that they would receive.

To learn more about candidate attraction we cover it extensively here, or please do get in touch to find out how Eligo can help you with your Data requirement and or recruitment strategy!