Artificial Intelligence is undoubtedly one of the most discussed and promising technologies in recent years. However, despite the enormous media and financial hype, companies are encountering significant difficulties both in effectively promoting AI-based services and in successfully implementing them. These challenges, combined with extremely optimistic market forecasts, are fueling growing fears of a possible speculative bubble in the sector.
Major tech companies are struggling to find the right way to promote their AI services, as demonstrated by some recent examples of controversial advertising campaigns. Google, for instance, had to withdraw its “Dear Sydney” commercial for the Paris Olympics after receiving numerous criticisms. The advertisement showed a father using AI to write an inspirational letter for his daughter, an aspiring athlete. Many found the spot cold and uninspiring, criticizing the idea of delegating important moments between parents and children to a machine.
Similarly, an advertisement by Meta for its generative AI suite sparked analogous controversies. The commercial showed people asking AI to generate workout plans or historical images, tasks that many believe should not be delegated to technology. Microsoft also promoted its Copilot chatbot with an Olympic spot that raised concerns about the safety and reliability of AI applications in health and sports.
These advertising campaigns have highlighted some common problems in AI promotion: they tend to show applications that are not really new or exclusive to AI, propose delegating to technology activities that many people would prefer to manage personally, and often do not address the most useful and widespread applications of AI, such as email writing or code generation, probably to avoid controversies about the future of certain professions.
The difficulties are not limited to promotion but extend to the practical implementation of AI in companies. McDonald’s, for example, discontinued a two-year experiment with IBM for an AI voice recognition system in drive-throughs, due to constant errors and comprehension problems. Other companies like Verizon, Starbucks, and ADP have experimented with AI systems to offer personalized advice or customer assistance, but often with unclear or dubious results.
These examples suggest that many companies feel pressured to implement AI-based solutions even when there is no real need or when the added value is unclear. This rush to implement AI seems to be fueled in part by consulting firms, which are reaping significant benefits from the AI boom. Companies like Boston Consulting Group, IBM Consulting, Accenture, KPMG International, and McKinsey are recording significant revenues from AI-related services, with some predicting that up to 40% of their turnover will come from generative AI this year.
Consulting firms tend to produce reports that magnify the transformative potential of AI, generating a market of supply and demand for consulting services for companies wanting to exploit these technologies. However, forecasts on the future value of the generative AI market vary enormously, from $167 billion by 2032 according to Future Market Insight, up to $1.3 trillion according to Bloomberg Intelligence.
These vastly different estimates raise doubts about the methodology used and the real understanding of AI’s economic potential. Some predictions appear particularly optimistic, such as McKinsey’s estimate of an annual added value between $2.6 and $4.4 trillion to the world economy, or Goldman Sachs’ forecast of a 7% increase in global GDP (about $7 trillion) thanks to generative AI.
These astronomical numbers are reminiscent of similar predictions made in the past for other technologies like the metaverse or blockchain, which did not materialize. For example, the metaverse, which according to some estimates should have been worth $800 billion in 2024, currently has an estimated market value of around $74 billion.
The current situation of AI in the business world presents several challenges and contradictions. On one hand, there is enormous interest and investment in the sector, fueled by extremely optimistic forecasts. On the other hand, companies struggle to find practical and meaningful applications for these technologies and encounter difficulties in effectively promoting them to the public. The risk of a speculative bubble in the AI sector is concrete, as demonstrated by the huge discrepancies in market forecasts and the historical precedents of other “revolutionary” technologies. It is essential that companies approach AI with caution, focusing on concrete and measurable applications, rather than chasing trends based on unrealistic promises. Only in this way will it be possible to fully exploit the potential of AI while avoiding the excesses of a possible speculative bubble.
