BRIEFING
Economic impacts of artificial intelligence (AI)
Artificial intelligence plays an increasingly important role in our lives and economy and is already having an impact on our world in many different ways. Worldwide competition to reap its benefits is fierce, and global leaders – the US and Asia – have emerged on the scene. Al is seen by many as an engine of productivity and economic growth. It can increase the efficiency with which things are done and vastly improve the decision-making process by analysing large amounts of data. It can also spawn the creation of new products and services, markets and industries, thereby boosting consumer demand and generating new revenue streams. However, Al may also have a highly disruptive effect on the economy and society. Some warn that it could lead to the creation of super firms – hubs of wealth and knowledge – that could have detrimental effects on the wider economy. It may also widen the gap between developed and developing countries, and boost the need for workers with certain skills while rendering others redundant; this latter trend could have far-reaching consequences for the labour market. Experts also warn of its potential to increase inequality, push down wages and shrink the tax base. While these concerns remain valid, there is no consensus on whether and to what extent the related risks will materialise. They are not a given, and carefully designed policy would be able to foster the development of Al while keeping the negative effects in check. The EU has a potential to improve its standing in global competition and direct Al onto a path that benefits its economy and citizens. In order to achieve this, it first needs to agree a common strategy that would utilise its strengths and enable the pooling of Member States' resources in the most effective way.
Key Metrics & Projections
Leading research institutes provide compelling forecasts on AI's transformative potential across various economic indicators, highlighting significant growth opportunities and shifts in market dynamics.
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
The majority of studies emphasise that Al will have a significant economic impact. Research launched by consulting company Accenture covering 12 developed economies, which together generate more than 0.5 % of the world's economic output, forecasts that by 2035, Al could double annual global economic growth rates. Al will drive this growth in three important ways. First, it will lead to a strong increase in labour productivity (by up to 40%) due to innovative technologies enabling more efficient workforce-related time management. Secondly, Al will create a new virtual workforce – described as 'intelligent automation' in the report – capable of solving problems and self-learning. Third, the economy will also benefit from the diffusion of innovation, which will affect different sectors and create new revenue streams. A study by PricewaterhouseCoopers (PwC) estimates that global GDP may increase by up to 14% (the equivalent of US$15.7 trillion) by 2030 as a result of the accelerating development and take-up of Al.
Al is one of the cornerstones of the growing digitalisation of industry ('Industry 4.0'). Technologies underpinning this process – such as loT, 5G, cloud computing, big data analytics, smart sensors, augmented reality, 3D printing and robotics are likely to transform manufacturing into a single cyber-physical system in which digital technology, internet and production are merged in one. In the smart factories of the future, production processes would be connected and Al solutions would be fundamental in linking the machines, interfaces, and components (using, for example, visual recognition). Large amounts of data would be collected and fed into Al appliances, which would in turn optimise the manufacturing process. The OECD reckons this use of Al can be 'applied to most industrial activities from optimising multi-machine systems to enhancing industrial research'.
Enterprise Process Flow
McKinsey argues that Al and automation may on one hand facilitate the rise of massively scaled organisations, and on the other will enable small players and even individuals to undertake project work that is now mostly performed by bigger companies. This could spawn the emergence of very small and very large firms, the end result being a barbell-shaped economy in which mid-sized companies lose out. Other likely effects are increased competition, firms entering new areas outside their previous core business, and a deepening divide between technological leaders and laggards in every sector. 'Early adopters', that is, companies that fully absorb Al tools over the next five to seven years, will most probably benefit disproportionately.
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If indeed technologies, such as Al, robotics and automation, are widely deployed across the economy, there will be job creation (as a result of demand in sectors that arise or flourish due to this deployment), as well as job destruction (replacement of humans by technology). As a 2018 meta-study of results shows, there is no consensus among experts, with predictions ranging 'from optimistic to devastating, differing by tens of millions of jobs even when comparing similar time frames'. A forecast by think-tank Bruegel warns that as many as 54% of jobs in the EU face the probability or risk of computerisation within 20 years. The effect is likely to be more nuanced, and there seems to be a consensus among researchers that there will be significant workforce shifts across sectors of the economy, accompanied by changes in the nature and content of jobs, which would require reskilling. Furthermore, job polarisation is probable: lower-paid jobs that typically require routine manual and cognitive skills stand the highest risk of being replaced by Al and automation, while well-paid skilled jobs that typically require non-routine cognitive skills will be in higher demand.
The "Robot Tax" Debate: Funding Future Workforce Transitions
The idea of a "robot tax" to fund retraining for workers displaced by automation has gained traction, notably advocated by Bill Gates. While the European Parliament rejected an initial proposal in 2017, the debate continues, especially as countries like South Korea have adjusted tax deductions for automation investments. The core challenge is balancing innovation incentives with ensuring a just transition for the workforce and maintaining public finances amidst potential decreases in income tax receipts from automated labor. A common, international strategy is needed to define and implement such taxation effectively.
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