Opinion: Keeping pace in the AI race

Governments around the world are vying to make their national economies leaders in the development and adoption of artificial intelligence (AI).

Why? Because AI promises transformative design, production and operating capabilities – particularly in the vital engineering and manufacturing sectors. AI solutions like machine intelligence can help firms in this space to gain unprecedented value from the huge volumes of data they generate.

So how is the global AI race shaping up – and crucially, how competitive is the UK?

The leader board

The USA and China are leading the pack, with the UK currently some way behind.

Analysis from US think tank The Centre for Data Innovation found America substantially ahead on AI talent development, R&D, and hardware and data adoption – with China closing the gap.

Its report compared funding of AI start-ups to the end of 2019. Firms in the US had raised more than $14bn from venture capital (VC) and private equity – compared to $6bn in China.

A year on, VC investment in the UK AI sector had only reached $3.4bn, according to Tech Nation.

There are, however, are some encouraging trends domestically. Tech Nation found there were 1,300 AI companies in the country as of June 2021 – up 600 per cent in a decade – with a combined turnover approaching $2bn.

Meanwhile, non-AI companies are embracing this revolutionary technology. Government figures show they spent around £63bn on AI tech and talent in 2020. This is forecast to exceed £200bn by 2040, by which time 1.3 million businesses will be making use of AI.

Strategic shortcomings

Like any nascent industry, the UK’s AI sector will require a clear national strategy and roadmap if it’s to become a world leader. And that’s where the country may be falling short.

The recent launch of a pilot AI Standards Hub is a case in point. It’s a welcome step, but lacks detail and a clear pathway to success.

The same could be said of the UK’s national AI strategy, unveiled in September last year, and intended to make the country a “global AI superpower” within the decade.

The framework doesn’t set out what funding will be made available to help businesses adopt AI. Or how that funding can be accessed by legacy businesses, which are the backbone of key sectors such as manufacturing and engineering.

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The government needs to shed light on this – and fast. Businesses need that level of detail to give them the confidence to plan and implement their AI strategies.

Contrast this lack of practical input with the situation in the US. Its National AI Research Resource Task Force has been created to drive the country’s strategy. Or in South Korea, where the government is spending $330m to open a National AI Industrial Convergence Complex in 2024.

Without similar commitments, the UK risks falling further behind, as businesses struggle with the perceived complexity of AI solutions.

Democratising best practice

Getting the most from the AI race requires more than technological expertise. A report from McKinsey identified six critical success factors: strategy; talent and leadership; ways of working; models, tools and technology; data; and adoption.

Clearly, these have implications for all aspects of the organisation. And according to McKinsey, following best practice in these areas is crucial to embedding AI at scale, and deriving full value from it.

But for the moment, many firms lack the necessary skills. As a result, 74 per cent of manufacturing AI initiatives get stuck at the pilot stage, separate McKinsey analysis found.

A dedicated AI task force would democratise access to the resources and tools needed to take on these practices; embed AI at scale; and manage the associated risks.

AI is propelling manufacturing and engineering into the future. And UK businesses are keen to get on board. But clear and practical government support is needed now to seize this opportunity to join the world’s AI superpowers.

Saar Yoskovitz is CEO at Augury