Artificial intelligence has been a hot topic lately, with generative AI technology making waves in various industries. However, there is growing concern that the hype surrounding this technology is starting to fade. As more money is poured into AI development, questions arise about its sustainability and practical applications.

A recent analysis by Gartner, a well-known research firm, predicts that global IT spending will exceed $5.5 trillion in 2025, with significant growth expected in sectors like data centers, devices, and software. This growth is largely driven by upgrades in generative AI hardware.

Despite the massive increase in spending, there is a lack of standout functionality in these segments. The ability to deliver real benefits will be crucial for the future success of AI products, as stakeholders and clients demand more from their investments.

Gartner’s research VP, John-David Lovelock, warns that generative AI is approaching the “trough of disillusionment” on the Gartner hype cycle. This phase signifies a decline in expectations for the technology, even as spending continues to rise.

AI companies are heavily investing in generative AI development despite growing skepticism about its practical applications. This shift in perception could signal a challenging phase for AI, with diminishing returns and decreasing expectations.

According to Lovelock, the journey towards the trough of disillusionment may not be fully realized until 2026, but 2025 is expected to be a pivotal year in this trajectory.

This forecast raises important questions about the economic, environmental, and societal impacts of AI development. If AI models fail to offer compelling use cases that benefit society, pouring trillions of dollars into this technology may not be sustainable in the long run.

In a world where advancements in AI only lead to “leaked photos of heaven,” it becomes essential to reassess who truly benefits from these technological advances. Without meaningful applications that serve the greater good, the relentless pursuit of AI innovation could be as futile as a one-way trip to Mars.