Is the UK about to miss out on a £190 billion tech market?
In this guest article, Stuart Davie, VP of Data Science at Peak, explores why the UK might be missing out on capitalising on a billion-dollar tech market, falling behind the likes of US and India.
We are in the grips of the fourth industrial revolution – the Intelligence Era – which will be characterised by advances in artificial intelligence (AI) and machine learning (ML). AI and ML will change the way the world works. Most business leaders understand this, with 71% of UK decision makers stating that AI will play a major or moderate role in their business achieving its objectives in the next five years.
And in the next three years, the digital sector could add as much as £190bn in value to the UK economy, thanks to a growing tech ecosystem accelerated by rapid digital transformation during the pandemic. But do we have the skill sets in the workforce to realise this growth?
The need for data scientists is relatively obvious. These roles are crucial to developing practical and innovative AI-driven solutions that tackle business challenges. The main reason why demand for data scientists in the UK has increased 231% over the last five years – businesses understand the potential they offer. Yet, at a national level we are in very real danger of missing out on the growth potential of AI and the digital sector. Yes, a lack of data scientists is a problem, but so is a lack of data proficiency in the wider workforce.
Research by Peak shows the adoption of AI in medium to large businesses across the UK, US and India. The findings suggest that the UK is falling behind India and the US when it comes to AI readiness i.e., our ability to successfully implement AI. That’s largely down to a lack of data literacy.
Our research shows that high levels of data literacy across an organisation’s workforce strongly correlate to a business’s likelihood of success with AI and UK workers (mid-management and junior) are far less likely to be using data regularly. While 98% of Indian and 81% of US workers say they have performed data analysis at least once in their role, only 64% of workers in the UK said the same. Most shockingly, only 48% of UK workers said their business is data-driven, compared to 81% of workers in India and 69% in the US.
How do we increase data literacy and the availability of data scientists, to avoid a potentially catastrophic downturn in the future?
Cross functional collaboration is a good starting point. Graduate data scientists are entering the workforce in record numbers, but we still have relatively few experienced professionals. Data science isn’t just about building models, it requires a commercial understanding and the ability to build solutions that meet the needs of end users and the business as a whole. To achieve that, data scientists need to work hand-in-hand with commercial personas.
This has the advantage of exposing those commercial folks to data analysis as well. They may not be able to write code but, by working alongside data scientists, they will understand which datasets a model is pulling from and the logic that goes into the recommendations it makes. For businesses intending to adopt AI, this is critical to its ultimate success. Any substantial investment in new tech will fail if those on the front lines choose not to use it, businesses need end users to trust AI predictions and, ultimately, use them.
Educational programmes focusing on data analysis will also be a major contributor to quantifying the UK data skills gap. In Autumn 2020, DCMS and the Office for AI launched a degree conversion course programme in data science and AI, and The Department for Education is rolling out digital bootcamps in all English regions that include courses in data analysis.
These are encouraging signs but it’s key that the progress of these are monitored to ensure that foundational data skills are being taught. This burden doesn’t lie with just one party however, it should be a joint effort between government, academia, industry and other training providers.
While not every worker needs to become a data scientist, everyone will need a basic level of data literacy to operate and thrive in increasingly data-rich environments. Investing in data skills brings companies closer to reaching their objectives and is the driving force in the world’s modern economics. Additionally, data-literate individuals are more likely to benefit from and contribute in an increasingly data-driven and AI-centric economy.