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Is AI a Bubble? Understanding Technology Waves, Speculation, and Smart Investment Strategies
The artificial intelligence boom has sparked intense debate about whether we're witnessing genuine technological progress or dangerous market speculation. The truth, according to seasoned investors, is more nuanced than a simple yes or no answer.
Key Takeaways
- Real technology waves and speculative bubbles typically occur together, not separately
- Major tech companies are engaging in questionable "circular deals" to fund AI ventures
- Retail investors face significant risks from unvetted SPV investment vehicles
- Smart angel investing focuses on AI applications in specialized verticals, not core AI development
- Institutional investors currently show zero interest in non-AI deals
Why Technology Waves Always Come With Bubbles
Drawing insights from Carlota Perez's seminal work Technological Revolutions and Financial Capital, investors note that genuine technology waves inevitably attract speculators and opportunists. This isn't a sign that the technology is fake—it's actually evidence that it's real.
Every time there's been a technology wave that leads to wealth creation, especially fast wealth creation, that will inherently invite speculators, carpet baggers, interlopers that want to come take advantage of it. Think of the gold rush.
The false dichotomy between believing in AI versus calling it a bubble misses this fundamental point. As one investor explains: If the wave is real, then you're going to have bubble-like behavior. They come together as a pair precisely because rapid wealth creation attracts participation from all types of investors.
Industrial Bubbles vs Financial Bubbles
Jeff Bezos recently distinguished between destructive financial bubbles (like 2008) and productive industrial bubbles (like the dot-com era of 1999-2000). While the dot-com crash was painful, it left behind crucial infrastructure and technology that powered the next generation of entrepreneurs and economic growth.
Most experts believe AI falls into the industrial bubble category—meaning real value is being created despite the speculative excess.
Warning Signs: Circular Deals and Market Manipulation
Even sophisticated companies are engaging in questionable practices that raise red flags about market speculation:
- Circular investment deals: Microsoft invests in OpenAI, which then buys services from Microsoft
- Vendor financing schemes: Companies like Nvidia provide funding to startups that then purchase Nvidia's services
- Accounting concerns: When asked why they engage in these practices if they're "not material," companies struggle to provide clear answers
When Dario was on stage at DealBook last week, he said, "Oh, I can explain this. It's not that hard. Amazon wanted us to spend money we didn't have, so they gave us even more money." And I'm like, well, that's precisely why this is a questionable behavior.
Retail Investor Risks: The SPV Problem
Retail investors face particular dangers from the proliferation of Special Purpose Vehicles (SPVs) promising access to hot AI investments. These single-investment funds often involve:
- Promoters who don't actually have access to the underlying investments
- Inexperienced investors who don't understand that 60-80% of venture investments go to zero
- Poor information transparency compared to public markets
- Significant psychological and financial impact when investments fail
The investments that have already generated 100x+ returns were made years ago, before the current speculation began. While incremental AI investments can still make money, the odds right now are really, really low.
Smart Angel Investing in the AI Era
For those still interested in angel investing, the strategy should focus on finding entrepreneurs who combine deep domain expertise with AI capabilities:
Look for Industry-AI Intersections
The best opportunities exist at the intersection of AI tools and specific industry knowledge. Ideal founders are those who could simultaneously be the smartest users of AI in their particular vertical or genre.
Stay Away from Core AI Development
Individual angels cannot compete in the foundation model space, which now requires billion-dollar investments. Instead, focus on applications that major AI companies are unlikely to prioritize.
Focus on Workflows and Proprietary Data
The most defensible AI businesses combine:
- Proprietary datasets specific to their industry
- Complex workflows that can be automated and integrated
- Deep vertical expertise that takes time to replicate
For example, real estate technology involves booking property tours, mortgage processing, paperwork approvals, and numerous other tasks that can be automated. The more workflows you can build into a system, the better protected you are from simple AI models that just answer questions.
The Current Investment Reality
There's an important reality that all entrepreneurs and investors must understand: institutional investors currently have zero interest in non-AI deals. This creates both opportunity and risk:
- Non-AI companies may struggle to raise follow-on funding
- AI companies have easier access to capital but face more competition
- Everyone should be experimenting with AI tools to stay relevant in their careers
I don't care what field you're in, you should be playing with this stuff. It has the potential to impact your role and your career. The best way to protect against any risk of your career being eliminated by AI is to be the most AI-enabled version of yourself you can possibly be.
Conclusion: Navigate Carefully But Stay Engaged
The AI revolution represents both genuine technological progress and speculative excess—and that's exactly what we should expect from a real technology wave. While retail investors should be extremely cautious about speculative vehicles and circular deals, the underlying technology demands attention and experimentation.
For angel investors, success lies in finding the intersection of deep domain expertise and AI capabilities in verticals that won't be immediate priorities for the tech giants. Focus on proprietary data, complex workflows, and specialized knowledge that takes time to replicate.
Most importantly, regardless of your investment strategy, start experimenting with AI tools in your own field. The best protection against disruption is becoming the most AI-enabled version of yourself possible.
