The AI boom: How powerful new technologies transform economies
M Kabir Hassan and Ayoub Ghalim :
Recently, economists started being more attentive to Artificial intelligence (AI) due to its potential of positively impacting economic growth. A lot of research has been done on the matter, where economists were trying to understand how to use AI in order to drive productivity growth specifically. The fact that AI is a general-purpose technology (GPT) gives it the potential to be applied and adopted in a variety of sectors for the purpose of increasing efficiency.
One of the main reasons why economists hold a positive outlook towards the potential of AI to drive economic prosperity is that it has the potential to enable significant productivity gains. AI has the potential to automate mundane and repetitive tasks, freeing up human resources to concentrate on more intricate and imaginative assignments. This, in turn, can enhance efficiency and boost overall productivity, as well as new innovations and business models. A research by Goldman Sachs suggests that the progress made in generative artificial intelligence will probably result in substantial transformations to the world economy. The adoption of these tools, which rely on advancements in natural language processing is projected to have a 1.5 per cent increase in productivity growth and a 7 per cent surge in global GDP over a span of 10 years.
However, despite the fact that over the last ten years, artificial intelligence (AI) and other digital technologies have advanced significantly, records of their ability to improve prosperity and drive widespread economic growth have been disappointing.
This is mainly because of a considerable time gap (lag) between the advancement of technology and the commercialization of new and innovative concepts that are based on these advancements, often necessitating supplementary investments. In other words, it takes time for businesses and industries to adapt to new technologies and develop complementary investments and innovations that fully realize the potential of the technology. This is particularly noticeable in the instance of GPTs, such as AI, which have the potential to transform entire industries and require significant investments in infrastructure, training, and other complementary resources to fully realize their potential.
One reason for this lag is that the development and adoption of new technologies can be expensive and time-consuming. Businesses must invest in research and development to create new products and services based on the technology, as well as in training and education to ensure that their employees have the skills to use the technology effectively. Furthermore, the adoption of new technologies can also be disruptive, particularly for traditional industries and workers. Such circumstances can cause opposition and hesitancy towards the adoption of new technologies, causing a further delay in the realization of their potential benefits.
Indeed, many opponents of AI have voiced their opinion regarding this aspect. Several studies have analyzed the different tasks performed by humans in their workplaces, with the McKinsey Global Institute’s research suggesting that the hotel and restaurant industry and manufacturing have a high potential for automation. Conversely, in the education and services sector, the proportion of automatable tasks is relatively low. The financial sector falls somewhere in the middle, with a medium potential for automation, which suggests that if the threat is serious, AI is not only coming for blue collar jobs but also for white collars.
However, another issue may arise. AI technologies have the potential to create a discernible performance disparity between companies that rapidly adopt AI tools across their entire organization (front-runners) and those who don’t adopt AI technology or delay integration until a later time (nonadopters). The front-runners are expected to benefit significantly, resulting in increased profitability. These are usually companies with a robust IT foundation, a greater propensity to invest in AI, and favorable opinions about the business rationale for AI and are more inclined to embrace the technology. On the other hand, companies that choose not to adopt AI tools may experience a reduction in their profits. A contributing factor to this decrease could be the intense competitive landscape that favors early adopters and could result in a transfer of market share from those who lag behind to those at the forefront of innovation. This has sparked discussions about the equitable distribution of the benefits of AI.
The same can happen on a larger scale, AI could potentially widen the existing digital divide between countries, and varying AI adoption rates might require different strategies and responses from different nations. Countries that are already advanced in AI adoption could further amplify their economic advantages compared to less advanced nations. They have the potential to attain additional economic benefits compared to what they currently have, while developing countries might have an even worse lag.
Advanced nations might not have any alternative but to embrace AI technologies to attain improved productivity rates because of their sluggish economic growth due to aging populations. Besides, the higher cost of human labor in these economies provides greater motivation to substitute it with automation compared to low wage developing countries.
On the other hand, developing countries typically have other ways to increase productivity, such as adopting best practices and restructuring their industries. Therefore, they might have less motivation to prioritize AI, which may provide them with relatively lower economic benefits compared to advanced economies.
Considering these arguments, artificial intelligence can significantly alter the economy. While the prospect of a boost in efficiency and outputs is promising, considering the prolonged decline in prosperity rate when it comes to advanced economies, there are also concerns about potential labor disruption and gaps creation between companies and nations resulting from AI. These disruptions could worsen existing labor force issues, including the declining male participation rates, and the levels of economic prosperity, industrialization, and overall development between different nations or regions of the world. Economic research has suggested that AI can increase productivity growth, but the effects on labor and different economies around the world are uncertain. Only the future will tell and help us have a better understanding of the circumstances under which AI can replace or supplement human labor, as well as other potential consequences.
( Kabir Hassan is a Professor of Finance at the University of New Orleans, USA and Ayoub is a PhD
student at the University of New Orleans, USA).
