Introduction: The AI Bubble 

The “AI bubble” describes the current surge of investment and excitement surrounding artificial intelligence technologies. Much like previous economic bubbles, this one is fueled by high expectations for huge financial returns and massive impact, prompting investors to pour vast amounts of capital into AI startups and established tech giants. While we cannot understate the promise of AI, the rapid influx of funding overlooks underlying risks and long-term sustainability. As a result, the AI bubble raises critical questions about whether society is sacrificing essential investments in infrastructure, education, and security in favor of chasing technological breakthroughs.  

Are we prepared for the societal changes that widespread AI adoption could bring?

Global Competition and Resource Allocation 

Clarity is required to examine the economic choices that we face as individuals and as a society. The United States desperately needs to keep pace with China and other countries that have large technology industries. Globally, massive amounts of capital are being deployed in a race for artificial intelligence dominance because there is a lot at stake in being left behind. This gold rush-like excitement of investment is taking resources from other important priorities that the public rely on, such as America’s crumbling infrastructure, failing schools, and the never-ending demand for security, locally and globally.  

Signs of an Economic Bubble 

The credit markets are showing strong signs of an economic bubble because investors are deploying enormous amounts of capital for what they hope are significant returns on investment, ignoring some of the risks. One major risk of AI investment is whether the value of AI implementation will justify the debt load that companies must absorb. If the AI monetization lags debt service payments, companies will find themselves over-leveraged and at risk of insolvency. If returns do not materialize, there is a risk of painful market corrections that trigger broader economic disruptions.  

Oversight and the Knowledge Gap 

Who should be responsible for overseeing AI’s impact on the economy and our way of life?

To fully understand the trade-offs of the AI investment surge, it’s essential to examine how weak oversight and regulatory gaps can magnify economic and societal risks

Much of the capital being deployed is supplied by private credit, which has weak oversight and regulatory requirements compared to public debt. AI tools are outpacing the governmental framework that is expected to provide oversight, and there is a huge mismatch in the level of knowledge that the heads of technology firms have compared to public governing bodies. The chart below breaks down the knowledge mismatch between governments and technology companies: 

Dimension	Governments	Tech Companies
Data Volume	Massive, but fragmented across agencies; often siloed and outdated	Vast, centralized, real-time behavioral data from billions of users
Analytic Capacity	Often limited by legacy systems, procurement cycles, talent constraints	Cutting-edge AI/ML infrastructure; top-tier talent and proprietary models
Incentives	Public accountability, equity, national security, regulatory compliance	Profit maximization, market dominance, data monetization
Transparency	Subject to FOIA, audits, and public inquiries	Opaque algorithms, proprietary data, limited external oversight
Policy Influence	Formal authority, but slow-moving and reactive	Increasingly proactive in shaping policy through lobbying, think tanks, and “soft power”

Tech companies have a huge advantage because often they know more about citizens than governments do. This is a big competitive advantage because it provides tech companies the power to persuade public opinions about policy and beliefs. Algorithms have enormous influence on people’s opinions which shapes policy, providing tech companies with soft power needed to influence government decisions. The entire policy process is being shaped by Big Tech because they decide which policy recommendations are even heard. They have vast amounts of control over the public narrative.  

“We will have for the first time something smarter than the smartest human. It’s hard to say exactly what that moment is, but there will come a point where no job is needed.”
— Elon Musk

Workforce Implications 

Most of the articles that I have read focus on how AI will affect the workforce and jobs in the future. There are reports coming out on how banks and other institutions will rely on AI to replace entry-level positions to drive value to the bottom line. That is short-sighted because companies will lose their pipeline of new talent. How will companies plan for future success if they focus on short-term gains?  

We are beginning to see more layoffs and there will be more to come. The workforce implications are huge for individuals and society at large because how will people sustain themselves and find meaning through work.  Recently, there have been large layoffs including: 

• UPS: 48,000 employees 

• Amazon: 30,000 employees 

• Intel:  24,000 employees 

• Nestle 16,000 employees 

• Accenture and Ford:  11,000 employees each  

• Novo Nordisk:  9,000 employees 

• Microsoft: 7,000 employees  

^{The Kobeissi Letter @KobeissiLetter} 

Conclusion: What Are We Sacrificing?

Are we prioritizing innovation at the expense of long-term societal needs?

The rush to fund AI is not without consequences. As capital flows into artificial intelligence, society risks neglecting critical investments in infrastructure, education, and security. The imbalance created by the AI bubble could have lasting effects, not only on the economy but also on the fabric of society. To ensure sustainable progress, it is essential to balance innovation with the needs of the public and to strengthen oversight and long-term planning.  

Join the conversation. Advocate for responsible AI policies and investments that protect society’s long-term interests.