Peltarion, leading AI innovator and creator of an operational deep learning platform, today announced the findings of a survey of AI decision-makers examining what they see as the impact of the skills shortage, and suggestions on how to overcome it. The research, ‘AI Decision-Makers Report: The human factor behind deep learning’, presents the findings of a survey of 350 IT leaders in the UK and Nordics with direct responsibility for shepherding AI at companies with more than 1,000 employees.
The report finds that many AI decision-makers are concerned about the business impact of the deep learning skills shortage. 84% of respondents said their company leaders worry about the business risks of not investing in deep learning, with 83% saying that a lack of deep learning skills is already impacting their ability to compete in the market. These companies are exclusively focusing on recruiting data scientists (71% of AI decision-makers are actively recruiting to plug the deep learning skills gap), and this is already impacting their ability to progress with AI projects:
- Almost half (49%) say the skills shortage is causing delays to projects
- 44% believe the need for specialist skills is a major barrier to further investment in deep learning
- However, almost half (45%) say they are struggling to hire because they don’t have a mature AI program already 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. In fact, the current approach, which relies on hiring a centralized team of data scientists to work on deep learning projects, is never going to work. Unlike big data and analytics AI usually relies heavily on specific business domain expertise, something that is very hard to transfer to an isolated data science team. We see this problem over and over again in enterprises - leading to AI projects that make no business sense, are not completed and create stress for data science teams.” explains Luka Crnkovic-Friis, Co-Founder and CEO at Peltarion. “Fortunately, with the right tools and a bit of training, it is possible to empower engineers and other domain experts to build AI systems themselves. The other good news is that for AI, unlike analytics, you don’t need to centralise your data, but can solve the problem locally which again reduces the need for advanced data engineering and science skills.”
Less than half (48%) of respondents said they currently employ data scientists who can create deep learning models, compared to 94% that have data scientists who can create other machine learning models. This shortage is having a direct impact on teams: 93% of AI decision-makers say their data scientists are over-worked to some extent because they believe there is no one else who can share the workload. However, with the right tools, others can make a serious impact on AI projects.
“Organisations need to move projects forward by bringing on existing domain experts and investing in tools that will help them input into AI projects. This will reduce the strain on data scientists and lower deep learning’s barrier to entry,” concludes Crnkovic-Friis. “We need to make deep learning more affordable and accessible to all by reducing its complexity. By operationalising deep learning to make it more scalable and understandable, organisations can put themselves on the fast track and use deep learning to optimise processes, create new products and add direct value to the business.”
About the research
The survey was conducted by independent research consultancy Coleman Parkes, through phone interviews and online surveys. It included 350 CIOs and senior IT decision makers from across the UK, Iceland, Sweden, Norway, Denmark, and Finland, at organisations with over 1,000 employees. All respondents have direct responsibility for AI and deep learning and have a team that includes experts in AI and deep learning reporting directly to them.
Peltarion is a leading AI innovator with offices in Stockholm and London. The first platform “Synapse” was released in 2004, and since then, Peltarion has helped companies and organisations like NASA, Tesla, Dell and Harvard to benefit from AI. The vision for Peltarion is to make AI accessible and affordable to more people and create a platform where people can work with AI without needing the skills of a data scientist, is a step towards this vision. Among the Peltarion customers, you will find doctors fighting cancer, carmakers optimising battery power, curators identifying moods in music, farmers keeping their crops secure. And the opportunities to do more expand every day. peltarion.com