The lack of deep learning skills is hampering the performance of British businesses, according to new research from operational AI firm Peltarion.
Its survey of firms across the UK and Nordic regions found 83 percent of AI decision-makers believe the deep learning skills shortage is affecting their business’s ability to compete in the market. Almost half (49 percent) said the shortage is delaying projects, while 44 percent see the shortage as posing a major barrier to further investment in deep learning.
The talent shortage is a cause for serious concern among businesses, who see deep learning (a sub-field of artificial intelligence) as an avenue to optimising processes and creating more intelligent data-driven products.
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Recruitment
As it stands, 71 percent of businesses are actively recruiting in an effort to remedy the skills gap. This could either indicate businesses are adopting a more proactive approach to the issue, or that the dearth of talent is prolonging the recruitment process.
The problem is further aggravated by the ‘chicken and egg’ dynamics at play. Almost half (45 percent) said they are struggling to hire because they don’t already have a mature AI program in place.
“This report shows that companies can’t afford to wait for data science talent to come to them to progress their AI projects,” explained Luka Crnkovic-Friis, Co-Founder and CEO at Peltarion. “The current approach, which relies on hiring an isolated team of data scientists to work on deep learning projects, is delaying projects and putting strain on the talent companies do have.”
Crnkovic-Friss believes the solution can be found right under the noses of AI decision-makers, in the form of talent already at hand. By providing existing teams with the tools they need to capitalise on deep learning opportunities, he hopes to allow other members of the workforce to contribute to AI projects.
“This will reduce the strain on data scientists and lower deep learning’s barrier to entry. We need to make deep learning more affordable and accessible to all by reducing its complexity,” he noted.
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