Recently, a German journalist sparked a debate by questioning the sustainability of the generative AI hype. The journalist argued that despite the massive investments and the fear of missing out (FOMO) driving big tech companies, the current economic impact of generative AI is not as substantial as some might think. This critique stirred significant controversy, with some accusing the journalist of lacking technical understanding. However, the journalist emphasized the importance of economic insight in this context.
The journalist highlighted that companies are investing enormous sums—Goldman Sachs estimates a trillion dollars over the next few years—in building the infrastructure for generative AI. This scale of investment would only be justified if the technology can penetrate several massive markets. For comparison, the Customer Relationship Management (CRM) sector, the largest single segment in the software market, has an annual volume of about $100 billion. Such a market for generative AI is not yet visible, although there are promising applications like programming copilots, automated customer communication, and knowledge management. Major software companies like SAP, Salesforce, and ServiceNow are integrating AI technology into their applications, making it more accessible.
Despite these advancements, widespread adoption is not yet apparent. Conversations with CIOs and project leaders reveal many innovative experiments but also debates about the economic viability of AI. Consulting firms like Accenture, Deloitte, and Bain reflect this skepticism in their studies. Large language models, while foundational, are not standalone products; they require significant integration efforts into the existing, often messy IT infrastructure of companies, making the introduction of new technologies a lengthy process.
This reality has influenced the stock market, with a sell-off in tech stocks indicating investor concerns. The leaders of Alphabet and Meta faced critical questions about over-investing during recent earnings calls. Technologies like the internet and the cloud took a decade or longer to achieve widespread adoption, and it seems generative AI might follow a similar timeline. However, the current investments in infrastructure will benefit the next generation of startups, making it easier for them to build on these foundations.
My 2 Cents
Currently, it is unclear how and where generative AI will crystallize its impact. It might even turn out that a different approach altogether will prevail. It is somewhat ironic that in Germany, we tend to question such investments on a grand scale, while we have consistently failed to keep up financially, missing out on virtually all high-tech waves of the past 30 years or ending up as market losers.
A tip for the journalist: this is the core problem that needs to be addressed if we do not want to fall behind even in traditional industries, as they increasingly depend on and must invest in high-tech solutions.
One of the few high-tech players in Europe effectively utilizing AI is Booking.com. They are leveraging AI to create personalized travel experiences, demonstrating how the technology should be used to enhance customer satisfaction and drive business growth. You can read more about their approach here.
The discussion on the sustainability of generative AI is crucial. While economic perspectives provide valuable insights, they should be balanced with an understanding of technological potentials and challenges. As history has shown, transformative technologies often take time to mature and achieve their full impact.
.jpg)
.jpg)
