The AI Bubble Is Coming — and Most Founders Are Counting on Bad Assumptions
If you’re building a startup in 2025 and your pitch deck doesn’t mention “agent” or “AI,” you’re already behind. But if your strategy assumes agents will replace people wholesale — that kind of confidence may be your undoing. The AI investment boom is entering bubble territory, and too many founders are blind to its cracks.
Investors, take note: your next failed round may not be because of market fit. It may be because the team believed hype louder than fundamentals.
The Bubble Signs Are Everywhere (And Growing Louder)
Let’s begin with what’s obvious but often dismissed. AI-labeled startups sucked up nearly two thirds of U.S. venture capital dollars in the first half of 2025. That kind of concentration—nearly 60 percent of deal value in one category—is a classic sign of capital herding.
Add to that: AI startup valuations are stretching absurd levels. Institutions are now publicly warning. Reuters reported this week that AI valuations are “raising bubble fears” as funding surges even without commensurate revenue. The IMF and the Bank of England just declared they see the plantings of a “market correction” creeping closer.
But here’s where the founders’ mistake is most dangerous: they think the human capital questions are solved. They aren’t. If anything, the human side is about to be rewritten again.
Why Founders Must Rethink Their Human Capital Strategy
When everyone runs toward AI, the winners will not just be those who build better models. Winners will be teams that integrate human judgment, resilience, ethical design, and error handling into their AI architectures. Because agents fail — often spectacularly.
Consider recent research: a Carnegie Mellon simulation found that leading AI agents failed nearly 70 percent of routine office tasks in a business environment. Another benchmark study points out that even top agents struggle in planning, execution, and multi-step logic.
We already know that knowledge workers distrust agents: in a recent U.S./U.K. survey, 62 percent of respondents said AI agents are unreliable. More than half said agents create extra work by forcing teams to clean up or redo outputs.
Leaps in model capability don’t erase these frictions overnight. If you think the agent will “magically just work,” you’re treating people as liabilities instead of assets — and that’s a strategic misfire.
The Other Founder Factors You Can’t Ignore
If you’re building in this era, here’s a candid list of what matters more than having a 10x valuation story:
Cognitive Flexibility over Domain Mastery
Models change fast. Founders who can quickly re-skill or shift focus will outperform those who cling to a single “AI thesis.”
Ethics, Explainability, and Trust Engineering
If your AI decisions can’t be audited, explained, or overridden, you’ll lose regulators, partners, and customers faster than any competitor can copy your model.
Error-Recovery Culture
You don’t just build agents. You build systems that assume they will err, detect anomalies, and fall back gracefully.
Team Fusion: Humans + Agents
The best teams will combine AI leverage and human oversight. Humans will become supervisors, orchestrators, exception handlers, and safety nets.
Psychological Durability
Startups that survive bubbles don’t just have vision. They have teams that can endure months of uncertainty, pivot hard, and rewrite themselves.
If you raise capital thinking headcount will scale linearly with product adoption, you’ll get trapped. The AI wave is near a bending point. If your people strategy is stale, you’ll crash into the wave.
The Investor’s (Uncomfortable) Role
If you’re an investor in 2025, your job is no longer just evaluating revenue multiples, TAM, and traction. Your job is to act like an agent-capital auditor.
When evaluating a founder, ask:
How many tasks are truly handled by agents vs human fallback?
Can they break down the cost or failure rates of those agents?
Are there logs, audit trails, kill switches, and human override paths?
How many engineers are dedicated to monitoring, governing, and retraining the agents?
If agent ROI drops 50 percent overnight, how resilient is the team to re-absorb tasks manually?
If a founder claims “we are agent-first” without a built-in plan for failure and recovery, that’s not ambition. It’s negligence.
How This Bubble Could Unwind
Here’s the scenario that keeps me up at night:
Sentiment shifts. A few high-profile AI failures happen (a fatal hypothetical, a regulatory breach, a misfire)
Real-world users push back. The “agent did something wrong” stories dominate news cycles
Capital slows. Valuations contract and disposable capital dries up
Founders realize their human capital neglected the hardest parts — maintenance, oversight, ethics, error modes
Teams that bet their growth on scaling alone collapse faster than ones built for resiliency
When the bubble burps, it won’t be the models that collapse first. It will be the teams whose human systems weren’t built to absorb failure.
Conclusion: The Future Belongs to Human-Agnostic Teams
If you want this op-ed to go viral, here’s the provocative thesis: the next startup failure wave will be human capital failures, not technology failures. The AI bubble is real. But your people — the culture, the oversight, the moral grounding — will determine whether you survive that burst.
Founders: don’t just ask how much money you can raise. Ask: what kind of human scaffolding will let your agents not wreck the business?
Investors: don’t ask how many agents are running. Ask: who owns them? Who reviews them? Who can kill them?
Call it “lean AI with a conscience.” Call it “agent-aware leadership.” Call it what you like. Just don’t call it naive.
