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Sizing the prize

Sizing the prize

[vc_row][vc_column][vc_column_text]Jul 2017 What’s the real value of AI for your business and how can you capitalise? Drawing on a detailed analysis of the business impact of AI, Sizing the prize outlines the economies that are set to gain the most from AI. AI will contribute USD15.7 trillion to the global economy in 2030, more than the current output of China and India combined. Labour productivity improvements are expected to account for over half of all economic gains from AI over the period 2016-2030. Increased consumer demand resulting from AI-enabled product enhancements will account for the rest. The greatest economic gains from AI will be in China (26% boost to GDP in 2030) and North America (14.5% boost), equivalent to a total of USD10.7 trillion and accounting for almost 70% of the global economic impact. • North America will experience productivity gains faster than China initially, driven by its readiness for AI and the high fraction of jobs that are susceptible to replacement by more-productive technologies. • China will begin to pull ahead of the US’s AI productivity gains in ten years, after it catches up on a slower build up to the technology and expertise needed. • Europe and developed Asia will also experience significant economic gains from AI (9-12% of GDP in 2030) • Developing countries will experience more modest increases (less than 6% of GDP) due the much lower rates of adoption of AI technologies expected (including Latin America, Africa). Overall, the biggest absolute sector gains will be in retail, financial services, and healthcare as AI increases productivity, product value, and consumption. By 2030, an additional USD 9 trillion of GDP will be added from product enhancements and shifts in consumer demand, behaviour, as AI driven consumption gains overtake those of productivity. The analysis underlines how the scale of the opportunity of AI needs to be underpinned by both more robust governance and new operating models to realise its full potential. Effective controls need to be built into the design and implementation phase to ensure AI’s positive potential is secured, and address stakeholder concerns about it operating beyond the boundaries of reasonable control. We need to adopt a responsible approach to the design and deployment of technology. Cutting across all considerations about business models, investment targets and how it can help performance, is trust and transparency, to help human understanding of what AI can do, and how it can be used effectively.”[/vc_column_text][/vc_column][/vc_row]