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AI and the productivity paradox – why it needs more than technology to transform the economy

The hype surrounding artificial intelligence (AI) is now several years old and has hardly subsided. Expectations are huge – but the hoped-for increase in productivity has so far largely failed to materialize in macroeconomic terms. Is the use of the new technology not worth it in reality?  The answer lies in a long-term perspective because economists blame this restrained development on the productivity paradox. If the development of AI follows this model, then we will only feel the positive aspects after some delay. An optimistic outlook (in these times of uncertainty) for production and logistics.

What is the productivity paradox?

The productivity paradox describes a historical pattern in which, after the introduction of a new key technology, productivity initially grows only slowly or even collapses, only to grow very strongly a few years later. This was observed, for example, with the introduction of electricity in American factories in the 19th century. Here, productivity stagnated for more than two decades until the new technology made itself felt in strong growth. It was not until engineers changed the layout of production facilities to suit the new possibilities that productivity rose rapidly. The introduction of steam engines – the starting point of the (first) industrial revolution – even led to an actual increase in productivity in the USA only after almost 50 years.

But why does it take so long for a new technology to make itself felt in productivity? Essentially, this has to do with the fact that technology alone does not change anything, but that work itself has to be completely rethought in each case. Process transformations take time and are always accompanied by friction losses. Moreover, these are investments that play practically no role in productivity statistics. Only when the technology is an integral part of the new way of working do the positive effects also become clearly visible.

The development of AI follows the same pattern

The productivity paradox could also be observed in the recent past. In 1987, Nobel Prize winner Robert Solow noted a similar development with regard to the use of computers: “Computers are everywhere – except in the productivity statistics”. Ultimately, the success of computers only became noticeable in the USA, for example, between the years 1995 and 2005.