No country comes close to the United States and China, the world’s stand-out leaders on the development of artificial intelligence (AI) technologies, but the United Kingdom is one of Europe’s leaders.
Diffusion and adoption are still at relatively early stages, but there is already evidence on the ground of the transformational change—both within organizations and in the economy as a whole—that these technologies can bring. A concerted, joined-up, and forward-looking effort from businesses and the government can deliver the positive disruption for which the United Kingdom is relatively well positioned.
In this briefing note, we build on previous research on AI globally and in Europe. We explore the prospective benefits to the economy and companies that could result from scaling up AI, and outline the priorities for businesses in the United Kingdom in order to reap those benefits.
Among the key findings are:
- AI could potentially deliver a 22 percent boost to the UK economy by 2030. This is somewhat larger than the global average potential of 16 percent, reflecting the fact that the United Kingdom is relatively more ready for AI than others.
- Within Europe, the ability to capture the full potential of AI varies significantly among countries. Currently, the United Kingdom is ahead of the EU-28 pack on MGI’s AI Readiness Index.
- AI is a competitive race—the frontier does not remain static. The AI gap between Europe and the frontier (represented by the United States) has already increased by 20 percent in the past three years. The imperative for the United Kingdom, therefore, is to move ahead on AI boldly and at scale.
- The United Kingdom has strengths and weaknesses:
- It has a strong innovation culture, but is failing to scale these innovations.
- It has a large pool of talent, but still faces a shortage of people with advanced technological skills.
- It has strong academic institutions, but is struggling to turn those into business and commercial success.
- UK companies can unlock productivity and scale through AI by focusing on three areas: (1) push beyond experimentation to deliver AI impact at scale; (2) invest in new and existing talent; and (3) forge links between cutting-edge research and commercial success to drive innovation.
