McKinsey: AI innovation constrained by talent shortage

Generative AI has certainly made a “loud entrance” into the world of business over the past six months.

McKinsey’s latest tech trends report predicts that this newest iteration of AI has the potential to transform businesses, particularly around driving economic growth.

The potential economic value from AI tools could be as high as $26 trillion – McKinsey data shows that 25% of companies attribute 5% of their earnings (before tax and interest) to AI.

Unfortunately, a major limiting factor in AI reaching its full business potential is the availability of individuals with the right skills and capabilities to continue innovating AI.

McKinsey report stated that a key uncertainty for the future of AI is the “lack of available resources, such as talent and funding, might affect the pipeline of AI applications, despite technical advances in solutions for industrializing ML and in IT infrastructure”.McKinsey report stated that a key uncertainty for the future of AI is the “lack of available resources, such as talent and funding, might affect the pipeline of AI applications, despite technical advances in solutions for industrializing ML and in IT infrastructure”.

Another potential uncertainty around AI, and its future competitiveness, is the ever-evolving regulatory landscape. The European Union (EU) is on the verge of introducing landmark AI legislation, and the US and the UK are not far behind.

McKinsey shares that organizations need to focus on how to make AI trustworthy and responsible, what checks and balances organizations need to have in place to “guard against AI-related risks associated with data privacy and security, equity, fairness, and compliance”.

The good news is that employers, as well as tech providers, are already highly aware of the need to be responsible for the use of AI within their business.

HR, remember to look beyond AI

While AI is top of mind for businesses at the moment, it is crucial to remember that this demand-supply discrepancy is not just an issue in AI, it is also a wider problem affecting innovation across many areas of tech.

McKinsey shared: “Organizations shouldn’t focus too heavily on the trends that are garnering the most attention. By focusing on only the most hyped trends, they may miss out on the significant value potential of other technologies and hinder the chance for purposeful capability building.”McKinsey shared: “Organizations shouldn’t focus too heavily on the trends that are garnering the most attention. By focusing on only the most hyped trends, they may miss out on the significant value potential of other technologies and hinder the chance for purposeful capability building.”

Other high-value tech like edge, cloud and quantum computing also have huge potential to transform businesses – but these are also the sectors significantly and persistently impacted by skills shortages.

“Our survey of 3.5 million job postings in these tech trends found that many of the skills in greatest demand have less than half as many qualified practitioners per posting as the global average,” noted the report.

For McKinsey, the answer to this skills gap in AI and beyond, is for employers to lean into upskilling.

Rather than relying onto the external pipeline, businesses need to focus on their existing employees and how they can learn, reskill and develop to fill the existing demand.