AI: an additive for boosting growth?

Artificial intelligence could be a key tool in the evolving functions of capital and labour, and thus a new lever for the economy.

Fabien Seraidarian
Director of Knwoledge Transfer and of the Global Executive MBA, SKEMA Business School

AI enables us to take action on the performance of our company’s activities, which are striving to make the most of this constantly changing technological potential. Even if the productivity paradox lurks, reminding us that “we see computers everywhere, except in productivity statistics” (1987), the impact of AI seems to be significantly established in the macro-economic statistics for 2030. Almost half the uses of AI involve automating processes and information systems, but AI is also being used to make up for labour shortages and boost productivity in this area. By 2035, AI could increase this growth by a weighted average of 1.7% in 16 major industries.

How can we decipher the mechanisms that contribute to this impact? If companies increase returns and the productivity of factors (labour and capital), this is a lever for growth because it boosts wealth creation. In macroeconomic terms, growth is expressed in terms of the state’s GDP/GNP, which statistically means a rise in its inhabitants’ standard of living. But what is the microeconomic situation at company level?

INCREASING AND DIMINISHING RETURNS

Several theoretical perspectives describe the dynamics at work. Adam Smith demonstrated that a company’s productivity increases through the division of labour, and from this deduced the law of increasing returns. David Ricardo set out the possibility of a decline in productivity in certain sectors, particularly agriculture, a major sector of the economy at the time. This is the law of diminishing returns: in the example of agricultural land, the most fertile land is cultivated first, then the least productive, and there comes a point at which marginal productivity (the production of an additional unit) eventually falls. Alfred Marshall sought to understand the relationship between these two laws: a company tends to increase its productivity by improving its organisation, but is faced with multiple challenges that cause returns to first increase and then diminish: an expression of the law of non-proportional returns.

But today, sectors dominated by the law of diminishing returns are more the exception than the rule, with agriculture accounting for less than 5% of global GDP. “Heterodox” economists believe that decision-makers set the prices of goods and services by calculating their average cost of production and adding a mark-up. But “orthodox” economists consider that, in the markets, prices depend on marginal cost, i.e. the price is equal to the marginal cost corresponding to the cost of the last unit produced. The quest for increasing returns or the least diminishing returns for large companies has historically been reflected in the search for growth (internal/external): all sectors experience concentration movements (vertical, horizontal) which may be amplified by globalisation and the development of transnational firms, enabling a territorial decoupling of company functions.

AI can play a major role in various sectors, by replacing capital with labour via automated processes, overcoming the scarcity of human resources and employees and improving overall productivity. However, beyond the data, there is the issue of access to information processing infrastructures, which raises questions about environmental sustainability. Technology thus plays a major role in maximising increasing returns, in particular through AI, which seems highly accessible given the adoption rates. The next few years will transform value chains and make AI a major lever for the evolution of “capital times labour” functions.