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    RESEARCH  |  IMPACT SERIES  |  INNOVATION EDGE

    AI revolution: productivity boom and beyond

    11 Jan 2024

    The world operates in a digitised economy, yet information technology (IT) hasn’t brought the long-term boost many had hoped for. In fact, productivity growth has been on a downswing since the 2000s. In partnership with the IBM Institute for Business Value, Barclays Research explores Artificial Intelligence’s potential to power a productivity boom that bolsters economies far into the future.

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    Excitement has mounted over “generative” Artificial Intelligence – which uses powerful computer models to produce high-quality text, images and other content, based on the data they were trained on. Many are wondering whether this technology could amount to a game-changing moment in labour productivity, akin to the inventions of the steam engine, electricity and the personal computer. 

    Positive effects on productivity have historically lagged the invention of new technologies, but our Research analysts, working in partnership with analysts at the IBM Institute for Business Value, see good reasons for optimism when it comes to the potential of GenAI to boost growth. 

    For one thing, the basic technology is accessible to a very wide audience on infrastructure that already exists. A user can issue instructions to a tool such as ChatGPT, the bot developed by OpenAI and launched in November 2022, without having to learn any special programming language.

    For another, these tools are not confined to any particular task, function, problem or sector. This makes them usable across different disciplines. Once a Large Language Model is trained on a body of text, for example, it can summarise a legal document as well as it can a medical document, or an insurance document. Few occupations are likely to be unaffected. As Jerry Kaplan, a Stanford academic, put it several years ago: “automation is blind to the colour of your collar.”

    Those two core attributes – accessibility and versatility – suggest that a broad rollout of GenAI could encounter fewer obstacles than previous advances in technology, and thus provide a genuine boost to the production of goods and services.

    However, ensuring that we unlock the full potential of AI technology and limit any of its negative effects will require the right policy mix to be in place, both from a regulatory standpoint and at the enterprise level.

    Two of the biggest challenges for the global economy in coming decades are, on the one hand, ageing populations in advanced economies and, on the other, low productivity in developing economies. AI could help in both respects.

    For countries such as Japan, Germany and Italy, for example, workforces are shrinking rapidly enough to require big leaps in labour productivity, just to maintain the kind of GDP growth levels that prevailed before the pandemic.

    But such advances are possible. According to our analysts’ estimates, most countries would have to attain similar levels of growth in labour productivity that they achieved between 1990 and 1994, to reclaim the average pre-COVID rates of GDP growth in 2033.

    In the emerging world, the picture is different: working-age populations are still expanding, on the whole, and in some cases very quickly. But skills and education levels tend to be limited, on average, compared to advanced economies, which manifests in low GDP-per-hour-worked. 

    What’s more, economists are observing what some have described as a “premature de-industrialisation”, in which developing nations no longer experience the industrialisation that typically resulted in large gains in productivity and real income, as workers moved from agriculture into manufacturing. 

    With AI, however, such a productivity-boosting effect may now be possible, if such workers shift into AI-aided services industries. “Service-isation” could take on the role that industrialisation played in the past.

    Balancing AI-driven productivity potential with societal needs and safety

    The policies adopted by companies, industries, and regulators will have a large bearing on the delivery of the promised benefits of AI, and how those benefits will be distributed. Cost will be a critical factor too, as the acquisition of data and computing capacity (and the energy it requires) is not cheap. 

    Our analysts argue that two guiding principles are especially crucial in the development of AI. The first is that the technology be used as a complement to labour, rather than as a substitute for it. A recent survey by the IBM Institute for Business Value indicated that companies’ overriding aim is to allow a sharpened focus on uniquely human talents such as creativity, social and interpersonal skills, and empathy. In that context, critical skills include time management, the ability to prioritise and an affinity for working in teams.

    Second, it is vital that policies should encourage the spread of AI across the economy. Regulation around accessing data to train or to deploy specialist technology is likely to play a critical role, and questions related to security, privacy and ethics need to be addressed. Our analysts are encouraged by initiatives such as the AI Alliance, a global network of technology firms, universities, non-profits and government groups that has come together to, in its words, “responsibly maximise benefits to people and society everywhere.”

    The opportunity set for AI looks wide. Yet fully exploiting the benefits is likely to require a very human response: a collaborative effort from industries and regulators, and a wholesale reimagining of business models and workflows.

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    Barclays Research contributors

    Christian Keller

    Head of Economics Research

    Christian Keller is Head of Economics Research at Barclays, leading a global team covering both developed and emerging markets. He is based in London and joined Barclays in 2007 from the International Monetary Fund (IMF), where he had worked on programs with emerging market economies in Europe, Latin America and Asia. He graduated with a PhD in Economics from University of Köln, Germany, and holds a joined-MA in Economics and Finance from University of Köln and HEC, Paris.

    Mark Cus Babic

    Economist in the European Economics Research team

    Mark Cus Babic is an economist in the European economics team at Barclays, based in London. His areas of focus are the euro area real business cycle and macroeconomic coverage of Germany. He joined the bank in 2020. Mark holds an MA Hons in Economics from the University of Edinburgh.

    Akash Utsav

    Economist in the Global Economics Research team

    Akash Utsav is an economist in the Global Economics Research team at Barclays. He joined the bank in 2017 and contributes to global macroeconomic thematic notes, as well as to quarterly publications. He holds an MSc Economics degree from University College London (UCL), London, UK, and completed his undergraduate from Loyola College, Chennai, India.

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    IBM contributors

    Ana Paula de Jesus Assis

    Chair and General Manager for IBM Europe, Middle East and Africa (EMEA)

    Ana Paula de Jesus Assis is the Chair and General Manager for IBM Europe, Middle East and Africa (EMEA), responsible for IBM’s overall business and relationship with the European Union and other public institutions. Previously, she was GM of the Client Transition Office, IBM GM in Latin America and held multiple positions in the USA and China.

    Brian Goehring

    Associate Partner in the IBM Institute for Business Value

    Brian Goehring is an Associate Partner in the IBM Institute for Business Value, where he leads the AI business research agenda, collaborating with academics, clients, and other experts to develop data-driven thought leadership. He brings over 20 years of experience in strategy consulting with senior-level clients across most industries and business functions. He received an AB in Philosophy from Princeton University with certificates in Cognitive Studies and German.

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