UK tech industry: Invest in AI and upskill the workforce for long-term success

By investing in AI and upskill, the UK will be able to develop a more agile workforce.

This is a contributed article by Daniel Kroening, Co-founder and Chief Scientist at Diffblue

Artificial intelligence (AI) is becoming an increasingly important contributor to the UK technology industry and the economy. In fact, a recent report from PwC found that the UK's GDP will be up to 10.3% higher in 2030 as a result of artificial intelligence (AI) - the equivalent of an additional £232bn. This means that investment in AI is one of the biggest commercial opportunities for the country, and many of its organisations.

However, research from Deloitte has recently revealed that while the vast majority (82%) of large businesses in the UK are investing in AI initiatives in some way, only 15% can be considered ‘seasoned' AI adopters. From a global standpoint, this puts the UK behind other regions such as the US (24%), Germany (22%), Canada (19%), Australia (17%) and France (16%) when it comes to AI maturity.

Investment in AI talent must be spread across the country

In this competitive international market, creating a favourable business environment for AI and investing in training is key for ensuring the long-term success of the UK's national AI strategy. While parts of the UK already have a thriving AI scene, it's important to ensure this continues to grow and that investment in AI is proportionally distributed across the country, both to make the most of existing AI talent and encourage new talent development.

For example, although 80% of the UK's top 50 AI start-ups are based in London, there are notable AI success stories from outside of the capital. Oxford, Cambridge, Bristol and Edinburgh have all produced prosperous businesses powered by AI and data analytics. Take, for example, DeepMind, which came out of Oxford in 2010, was acquired by Google, and is now a leading AI company.

Develop your own AI experts from in-house talent

As a spinout of the University of Oxford, Diffblue is another example of an AI start-up with roots outside of London. We are very fortunate to have a pool of talent from varied backgrounds and experiences, but even in Oxford, there isn't an abundance of readily available AI experts.

Many businesses in the UK are facing a similar challenge when it comes to recruiting employees with AI skills. Universities cannot yet produce enough AI developers and software engineers to meet the growing demand for AI talent, with AI-specifc degrees in very low supply. Demand is only going to increase in the years to come.

Encouraging growth of the AI industry

For the UK to be a global hub for AI, we need to address this challenge. The government and the private sector can encourage the growth of the AI industry in the UK by investing in two key areas:

  1. AI and automation tools to make effective use of human talent. In addition to a shortage of AI skills, the UK is short of software engineers in general. Using AI to help automate some of the steps in the software development process can be an effective way for businesses to make better use of existing talent, bring products to market quickly, and drive technological innovation (AI and otherwise). While many tools that assist with software development are still very new, some of the UK's existing AI technology could be more widely adopted by companies with software development initiatives. At Diffblue, we are currently working with developers to automate the writing of unit tests, and we are also exploring other areas in the software development life cycle where AI can be used to speed up and improve elements of human coding.
  2. Upskilling and reskilling teams and employees with a non-tech background. There aren't enough university places in AI programmes to provide the training the UK needs, so companies need to tackle this challenge themselves. At Diffblue, we started investing early in hiring talented computer scientists and developers who may not have ever worked in AI before, and training them to work with our AI engine. We expect that new team members will spend three to four months learning the inner workings of our technology before they can actively contribute to new development, but the investment has been worthwhile. We encourage other businesses to follow suit and build effective training programmes to re-skill their teams.

By investing in these areas, the UK will be able to develop a more agile workforce with the skills required to effectively use AI, while also maximising current resources. As a result, the country should be able to reach its potential as a hub AI expertise and advancement, and be a serious competitor on a global scale.

Daniel Kroening is Chief Scientist and co-founder of Diffblue. He has 15 years' experience building software verification tools and is the primary author of the CBMC verification framework. Kroening is also a Professor of Computer Science at University of Oxford.