Global Economic Futures Productivity in 2030 2025

The same survey reveals that service-related sectors are the ones most expected to use AI to innovate new products and business models in the coming years (see Figure 4.2). Nearly half of respondents expect information and technology services companies to generate AI opportunities, closely followed by companies in the financial services sector. The energy technology and utilities sector is also seen as a leading adopter of AI. Among other industries, more than one- fifth of executives expect companies in advanced manufacturing, engineering and construction to leverage AI in the near term. Realizing the full productivity potential of new technologies requires addressing structural barriers such as access to capital and talent, digital infrastructure gaps and diffusion of innovation. While breakthroughs at the frontier carry significant potential, improved access to simpler and more readily available technologies can unlock wider productivity gains across firms and countries. For example, the diffusion of improvements in energy and irrigation technologies is expected to drive sizeable increases in agricultural productivity,11 with the use of precision farming boosting crop yields by as much as 15%12 in some cases. Human capital The adoption and diffusion of advanced technologies are inextricably linked to human capital. Recent World Economic Forum interviews with business executives reveal that the successful deployment of AI depends as much or more on people as on the technology itself.13 This is in line with the finding that firms can boost productivity gains from 4% to 11% if they leverage complementarities between data, technology and talent, rather than focusing solely on data and technology.14 Yet despite the clear importance of human capital in maximizing productivity gains from technology, both public and private spending on workforce training has declined in recent years, with spending in OECD (Organisation for Economic Co- operation and Development) countries falling from 0.2% to 0.1% of GDP since 2008.15 Human capital is also seen as the main obstacle to AI adoption by business leaders. Nearly half of respondents cite a lack of skills as the primary bottleneck, while 43% point to a lack of vision among managers and leaders.16 By contrast, fewer than one-third of executives highlight the cost of AI products and services, and only one-fifth see regulatory constraints as key barriers.17 Ongoing digitization is accelerating a shift towards a high-skill-intensive workforce, where both technical expertise and non-cognitive skills – such as leadership and communication – are increasingly critical. The level of skills and their complementarity Top countries and sectors expected to leverage AI opportunities according to business executivesFIGURE 4 Europe Oceania South-eastern AsiaMiddle East and Northern Africa Northern America1Norway 2USA 3Finland 4Indonesia 5Israel 6Philippines 7United Arab Emirates 8Australia 9Switzerland 10 New ZealandFigure 4.1 Top 10 economies by use of AI among local businesses to enhance productivity 1Information and technology services 2Financial services and captial markets 3Energy technology and utilities 4Telecommunications 5Accommodation, food and leisure services 6Advanced manufacturing 7Education and training 8Media and publishing 9Engineering and construction 10 Medical and healthcare servicesFigure 4.2 Top 10 sectors to generate AI opportunities Source: World Economic Forum. Executive Opinion Survey 2024. Global Economic Futures: Productivity in 2030 9