The debate over whether the current surge in artificial intelligence (AI) investment signals an economic bubble or a genuine technological transformation is heating up across boardrooms, government offices, and trading floors worldwide. Recent events and commentary from leading economists, policymakers, and industry insiders reveal a landscape marked by both promise and peril, as AI reshapes economies, labor markets, and even the very metrics by which we measure progress.
At the heart of the discussion is a question that has haunted previous eras of rapid innovation: are we witnessing sustainable growth, or is this another speculative frenzy destined for a painful correction? According to the Korea JoongAng Daily, governments around the globe are ramping up AI initiatives, partly out of a fear of missing out on the next big wave of technological change. The arrival of generative AI tools like ChatGPT and DeepSeek, coupled with wild swings in the value of GPU-linked stocks and persistent commentary from the United States Federal Reserve on interest rates and liquidity, have only fueled speculation about a looming AI bubble.
The conversation is not entirely new. Back in 2016, the world watched in awe as AlphaGo defeated Go champion Lee Se-dol, an event that, as recalled by the chair of the board at KAIST and former environment minister, sparked forums and books dissecting the so-called "Fourth Industrial Revolution." The lessons of history, particularly the Great Depression that followed the roaring 1920s, loom large. As Korea JoongAng Daily notes, factors like margin trading, excess liquidity, and weak regulation set the stage for the 1929 Wall Street crash—a sobering reminder of the dangers when financial exuberance outpaces real economic fundamentals.
Ben Bernanke, the former Federal Reserve chair who steered the U.S. through the 2008 financial crisis, is often cited as a voice of caution. His Nobel Prize-winning work emphasized how the collapse of financial systems can cripple the real economy, turning downturns into disasters. Reflecting on 2008, Bernanke admitted that systemic risk had been underestimated, but his emergency liquidity measures are credited with staving off another Great Depression.
Fast-forward to October 2025, and Andrew Sorkin’s book "1929: Inside the Greatest Crash in Wall Street History" is stirring debate anew. Sorkin draws explicit parallels between the economic psychology, institutional weaknesses, and social structures of the 1920s and today. He warns that the potent mix of technological innovation, financial democratization, and credit expansion offers both opportunity and profound risk. As he puts it, "If history is forgotten, it repeats itself."
Yet, not everyone is convinced that today’s AI boom is doomed to repeat the mistakes of the past. Optimists point out that the dot-com bubble of the late 1990s lacked the digital infrastructure needed to convert innovation into productivity. In contrast, current investments in GPUs and data centers are seen as laying the groundwork for long-term gains. Stanford’s Erik Brynjolfsson describes AI as a "powerful general-purpose technology" that may experience "a phase of overheating and selective correction before delivering major gains." In other words, some bumps in the road are to be expected, but the destination could be worth the journey.
The numbers are certainly eye-catching. According to Reuters, AI-related capital expenditures contributed more to GDP growth in the first half of 2025 than consumer spending—a remarkable shift. Bespoke Investment Group estimates that roughly one-third of the global market capitalization increase since the debut of ChatGPT can be traced to just 28 AI-related companies. Trillions of dollars are pouring into the sector, driving both stock-market rallies and a shortage of critical hardware like memory chips.
But with great investment comes great anxiety. The Reuters NEXT conference in New York on December 4, 2025, was dominated by discussions about AI’s impact on the workforce. Panelists largely sidestepped the bubble question, focusing instead on how AI is transforming jobs and job growth. May Habib, CEO and co-founder of AI startup Writer, provided a stark example: "All (of our customers) are focused on slowing headcount growth. This has happened just in the last few weeks. You close a customer, you get on the phone with the CEO to kick off the project, and it’s like, Great, how soon can I whack 30% of my team?"
Such comments are not outliers. A U.S. Federal Reserve report has already documented that AI is replacing entry-level positions and causing companies to scale back hiring. The anxiety is palpable—an August 2025 Reuters/Ipsos poll found that 71% of respondents worried AI would "put too many people out of work permanently." The data backs up these fears: the U.S. Labor Department reports that recent college graduates face a 9.5% unemployment rate, more than double the national average of 4.4%.
Still, there are voices of optimism. Economist Joseph Lavorgna, counselor to the U.S. Treasury secretary, argued at the conference that "AI is an incredible tool that I think is complementary to the existing workforce. We need policies that are going to encourage businesses to invest, and AI is a complement to it." The idea is that, with the right policies, AI can enhance rather than replace human labor—a message that resonates with business leaders eager to harness technology without triggering a social backlash.
Yet, the financial underpinnings of this new economy are, if anything, even more complex than in the past. The Financial Stability Board estimates that global financial assets now total four to five times global GDP, with off-exchange derivatives and non-physical assets valued in the hundreds of trillions of dollars. The International Monetary Fund (IMF) warned in 2024 that a digital asset bubble could distort the real economy and weaken the effectiveness of monetary policy. Connecting these virtual valuations to real productivity has never been more critical.
Yale professor Robert Shiller’s "narrative economics" concept, introduced in 2019, suggests that economic behavior is shaped as much by stories as by statistics. Claims that AI will reorganize industries, replace workers, or determine geopolitical power are not just idle talk—they actively shape investment and policy decisions. As Korea JoongAng Daily observes, managing the side effects of speculative techno-capitalism is now a central policy task.
On the policy front, countries like South Korea are moving quickly. On September 8, 2025, President Lee Jae Myung addressed the launch of the National Artificial Intelligence Strategy Committee in Seoul, signaling a commitment to harnessing AI for national growth. Yet, as the Korea JoongAng Daily notes, traditional metrics like GDP struggle to capture the value and risks of virtual assets and growth decoupled from physical industry. Attempts to introduce more holistic measures—like South Korea’s short-lived "green GDP" initiative in 2001—have so far fallen short.
Looking ahead, the article calls for a new conceptual framework—perhaps "civilizational economics"—to redefine economic value in the age of AI. This would mean integrating ethical and environmental effects into policymaking, accounting for everything from electricity demand and grid strain to climate impact and public trust. Without such a shift, the sustainability of civilization itself could be at risk.
As the world stands at the crossroads of technological revolution and economic uncertainty, the challenge is not just to ride the AI wave, but to steer it wisely—balancing innovation with caution, and progress with responsibility.
