Artificial intelligence (AI) is often portrayed as a revolution capable of radically transforming our societies and economies. However, the exorbitant costs associated with its development and the enormous gap between promises and current achievements have led some experts to speak of a bubble. This article analyzes the financial aspects of AI, highlighting lucrative promises while underscoring the potential pitfalls related to this emerging technology.
Lucrative promises of artificial intelligence
Proponents of artificial intelligence often tout the diverse and potentially highly lucrative applications of this technology. From personalized medicine to optimized online commerce, through finance and industry, the opportunities seem endless.
In the medical sector, for example, AI promises faster and more accurate diagnostics, thus optimizing treatments and reducing healthcare costs. In e-commerce, it enables the personalization of shopping experiences, increasing conversion rates and customer satisfaction. Similarly, in the financial sector, AI algorithms promise robust predictive analyses, improving risk management and investment strategies.
Massive investments and high expectations
The promises of AI attract significant investments from businesses and governments. Billions of dollars are being injected into research and development, infrastructure, and the recruitment of specialized talents. Investments in this field are estimated to have reached historical highs, with major players like Google, Microsoft, and Amazon leading the charge.
However, expectations are immense, and the pressure to deliver concrete results is high. This situation creates an environment where hopes can easily outpace the current technological and commercial realities.
Exorbitant costs and revenue shortfalls
Unfortunately, the financial reality of artificial intelligence does not always align with expectations. The costs associated with the development of AI, particularly those related to computational power and computer infrastructure, are astronomical. These expenses often far exceed the revenues generated by current AI applications.
For example, training AI models requires colossal computational capabilities, involving considerable investments in hardware and energy. Infrastructure costs continue to rise, while revenues from industrial and commercial AI applications struggle to keep pace.
The emergence of a speculative bubble
This gap between investments and revenues fuels fears of a speculative bubble in the artificial intelligence sector. The discrepancies between ambitious public announcements and concrete results are beginning to be felt. Unfulfilled promises have the potential to disappoint investors, leading to a sharp drop in stock prices of tech companies heavily invested in AI.
The most emblematic example is that of ChatGPT, developed by OpenAI, which generated considerable excitement in 2022. Expectations were high, but the costs of maintenance and development revealed a still-fragile economic model.
Impacts and potential pitfalls
Beyond strictly economic aspects, artificial intelligence raises ethical and social questions. The massive implementation of AI technologies raises concerns regarding privacy, safety, and transparency.
The risks associated with algorithmic biases and automated decisions without human oversight can have serious consequences for individuals and societies. The growing reliance on these systems also raises the question of the loss of certain human skills and the increase in inequalities.
