In its most recent financial stability report, the Bank of England has raised concerns that a significant drop in the value of artificial intelligence (AI) stocks could lead to a recession in the United Kingdom. The report suggests that a "price correction in AI stocks," potentially driven by changes in how productive and profitable tech companies become, could result in a 2.2 percent decrease in the UK's gross domestic product (GDP). This warning underscores the growing unease about how AI could affect not just the tech sector, but the global economy as a whole. The Bank of England's alert comes as debates about AI's true impact continue to grow. Some argue that AI is a groundbreaking technological advancement, while others believe it's just a passing trend. Looking back at the past 30 years, history shows that technology can be both a real innovation and a source of hype. The Y2K bug, for instance, was a real technical risk in the late 1990s that sparked widespread concern. Governments and companies spent billions preparing for it, but when the year 2000 arrived, the feared chaos never happened. Although the event seemed overblown in hindsight, it highlighted the importance of taking risks seriously and preparing for them. The dotcom bubble of the early 2000s provided another lesson. The internet was a real innovation, but many companies were overvalued. Some, like Boo.com, raised large sums of money but eventually failed due to unsustainable business models. The bubble burst, leading to financial losses, but the internet itself endured and evolved. Similarly, the rise of cryptocurrency in recent years showed that revolutionary ideas can sometimes be overshadowed by hype. While the underlying technology was solid, the market often focused more on speculation than practical use. Today, AI's development seems to blend elements of these past experiences. Like Y2K, AI poses risks that might seem exaggerated until they aren't. Like the dotcom era, AI is a real general-purpose technology that can already perform tasks such as writing code and summarizing documents. However, not every AI company or product is valuable. Businesses need to focus on building strong foundations, including data, people, and processes, rather than chasing the latest trend. Finally, like cryptocurrency, AI has started to take on a mythic status, with the term "AI-powered" being used loosely. For AI to be truly adopted, leaders must ask practical questions about its purpose, data usage, and accountability. The future of AI may not be clear, but those who adapt to it will likely be the most successful.