1. Introduction: The Growing AI Gold Rush
Artificial Intelligence has become the heartbeat of the modern tech world. Every company, from startups to global giants, is racing to integrate AI into their products. Billions are being poured into AI development, research, and acquisitions.
But amid the excitement, one voice stands out with caution — Morgan Stanley. The global investment bank recently issued a stark warning about “circular AI deals.” According to their analysis, the current AI boom could turn into a financial bust that might rival the 2008 crash.
This raises tough questions: Are AI firms overvalued? Are companies truly innovating, or just buying from each other to inflate their balance sheets? And what happens when investor confidence fades?
Let’s break down Morgan Stanley’s warning and explore whether the AI revolution is built on real value or a dangerous illusion.
2. Morgan Stanley’s Warning Explained
Morgan Stanley’s latest market note focuses on one key concern — the circular nature of AI investments.
In simple terms, many AI companies are not selling products to end consumers. Instead, they are selling services to other AI companies. These internal transactions create the appearance of massive demand, but much of it may be artificial.
For example, one AI startup might pay another for data labeling, while that same company buys AI model access from a third firm. On paper, everyone reports revenue growth. But in reality, it’s the same pool of investor cash circulating among the same players.
This type of ecosystem looks sustainable — until funding slows. Then, without real customer demand, the illusion shatters.
Morgan Stanley draws parallels between today’s AI hype and the dot-com bubble of the early 2000s, where startups inflated valuations through mutual partnerships and unsustainable spending.
The bank warns that history may be repeating itself — this time under the banner of artificial intelligence.
3. How Circular AI Deals Work
Circular deals are not new in tech. They happen when companies trade products, services, or subscriptions among themselves to boost reported revenue.
In the AI industry, this can take several forms:
- AI firms purchasing cloud credits from one another.
- Startups subscribing to each other’s APIs to inflate usage metrics.
- Companies reselling similar AI tools under different brand names.
This creates a closed loop where real market value becomes hard to measure.
Imagine a small group of AI startups, each funded by venture capital. They buy services from each other, record “growth,” and use that data to attract more investors. But when new funding dries up, there’s no outside customer base to sustain operations.
A fractional CTO, someone who provides part-time executive-level tech leadership, often spots this problem early. Unlike full-time executives caught in the growth chase, a fractional CTO evaluates the real business model. They focus on sustainable revenue streams and technology that creates real value — not just impressive metrics.
Without this kind of strategic oversight, startups can easily fall into the circular trap, chasing short-term gains instead of building long-term value.
4. Lessons from the Dot-Com and 2008 Crashes
Morgan Stanley’s caution echoes two painful chapters in financial history — the dot-com bust and the 2008 financial crisis.
During the dot-com era, startups raised billions for websites with no revenue models. Investors poured money into “potential,” not profits. When reality hit, the market collapsed, wiping out trillions in value.
The 2008 crisis followed a similar pattern — overconfidence, opaque deals, and overleveraged bets. Everyone believed the system was too big to fail until it did.
Today, AI seems to be treading a similar path. The hype is enormous, and valuations are skyrocketing. Companies worth billions may not even have a sustainable product yet.
The key lesson? Hype cannot replace fundamentals.
Investors must look for companies with measurable outcomes, customer traction, and profitability — not just powerful branding or visionary pitches.
5. What Happens When the Music Stops
The phrase “when the music stops” describes the moment the illusion breaks. In the AI industry, this could happen when venture funding tightens, or investors demand proof of profit.
If AI valuations deflate suddenly, here’s what might follow:
- Startups may collapse if they rely solely on investor money.
- Tech giants could pull back spending on experimental AI divisions.
- Layoffs and consolidations may sweep across the sector.
- Investor confidence could erode, slowing innovation.
But the biggest concern isn’t short-term loss — it’s the long-term impact on real innovation. If the market turns sour, promising AI research might lose funding before reaching maturity.
The industry could enter a “winter phase,” much like crypto did after its speculative bubbles. However, the best companies — those with strong fundamentals — will survive and eventually thrive.
6. Is There Real Value Beneath the Hype?
Despite Morgan Stanley’s warning, not everything in AI is smoke and mirrors. There’s genuine innovation happening across multiple sectors:
- Healthcare: AI is transforming diagnostics, predictive analytics, and personalized medicine.
- Finance: Fraud detection, algorithmic trading, and risk analysis are becoming smarter and faster.
- Enterprise software: AI automates workflows and enhances customer experience.
- Logistics: Machine learning optimizes supply chains and delivery routes.
These applications create measurable value. They improve efficiency, reduce costs, and generate long-term impact.
The problem arises when every startup claims to be “AI-powered” without a clear revenue model or product differentiation.
This is where fractional CTOs again play a vital role. They help startups separate real AI capability from buzzwords. A seasoned fractional CTO ensures technology decisions are driven by value, not vanity metrics.
So yes — real value exists beneath the hype, but it’s buried under layers of inflated marketing and speculative investment.
7. How Investors and Startups Can Protect Themselves
Both investors and founders need to approach the AI market with caution and strategy.
For investors:
- Look beyond growth metrics. Focus on profitability and customer retention.
- Demand transparency in revenue sources.
- Avoid companies with unclear or recycled AI models.
- Partner with experienced tech advisors or fractional CTOs to assess technology viability.
For startups:
- Build real products that solve real problems.
- Prioritize sustainable revenue over quick valuation spikes.
- Be transparent about data sources, model training, and costs.
- Foster long-term partnerships, not short-term transactional ones.
Sustainable AI growth depends on trust, accountability, and measurable value. Those who prioritize these elements will weather any downturn.
8. Conclusion: Preparing for AI’s Next Phase
Morgan Stanley’s warning is not a doomsday prophecy — it’s a reality check. The AI boom is filled with opportunity, but also with risk.
Circular deals, inflated valuations, and investor hype can make the industry look stronger than it is. When the hype fades, only those who have built genuine value will stand tall.
To survive and thrive, both investors and founders must focus on fundamentals — real customers, real revenue, and real innovation.
AI isn’t just another tech fad; it’s a transformative force. But without caution and structure, it can spiral into another bubble.
As the StartupHakk community often emphasizes, sustainable growth comes from authenticity, innovation, and purpose — not speculation. The future of AI depends on who learns that lesson before the music stops.
