Is the AI Bubble About to Burst? Separating Hype From Reality in 2026

Over the last few years, we have heard some bold claims about AI. OpenAI’s CEO warned about an AI bubble. An MIT report suggested that 95 percent of generative AI projects fail inside companies. The Anthropic CEO predicted that 90 percent of coding would be automated within six months. Elon Musk claimed we would reach AGI by 2025. 


Now pause for a moment and look around. Are we really living in that future? 

Big AI Claims vs What Actually Happened 

Let’s test one of the strongest predictions. If 90 percent of coding was automated, the impact on large IT services companies should have been massive. 

Take a company like TCS. It has around 600,000 employees. Even if we assume 400,000 of them are doing coding, a 90 percent automation scenario would mean roughly 360,000 people losing their jobs. 

What actually happened? 

TCS laid off around 12,000 employees. That is roughly 2 percent. Even if the number is slightly higher, say 3 or 4 percent, it is nowhere close to 90 percent. 

This simple comparison shows a clear gap between predictions and reality. 

The same applies to AGI. We are now well into 2025, and we are nowhere close to artificial general intelligence. AI is impressive, but it is not thinking, reasoning, and adapting like a human across all domains. 

AI and the Dotcom Bubble Parallel

This situation feels familiar if you look at history. 

In the late 1990s, the internet was booming. Valuations were skyrocketing. CEOs were making massive promises. Every company with “dotcom” in its name was attracting investors. 

Then came the year 2000. 

The dotcom bubble burst. Many companies went bankrupt. Most of the promises failed. But the internet itself did not disappear. It stabilized, matured, and eventually transformed our lives. Companies like Amazon and Google survived and became giants. 

AI appears to be following a very similar cycle. 

Right now, we are in the hype phase. Valuations are extremely high. Expectations are unrealistic. Big promises are everywhere. That does not mean AI is useless. It means the market expectations are inflated. 

The Real Warning Sign: AI Capital Expenditure 

One of the strongest arguments for an AI bubble comes from capital expenditure. 

In 2018, the combined capital expenditure of major tech companies like Amazon, Meta, and Google was under $100 billion. Capital expenditure, or capex, includes spending on data centers, infrastructure, and R&D. 

Fast forward to 2026. 

AI-related capex is projected to exceed $400 billion, and in some estimates, close to $500 billion in the US alone. 

Now compare that to revenue. 

Total revenue generated from AI services today is roughly $12 billion. 

That gap is enormous.  

Think of it like running a shop where you spend $500,000 every year but generate only $12,000 in revenue. You can survive for a while using investor money, but eventually the business must generate more revenue than it spends. Otherwise, the model collapses. 

This imbalance is a key reason why many analysts believe the AI bubble in 2026 may pop. 

Sky-High Valuations With No Products 

Another example that raises eyebrows is the valuation of new AI startups. 

An OpenAI executive recently launched a new company valued at $10 billion. The company has no publicly known product and zero customers. 

The valuation exists largely because of reputation and expectations. 

That does not mean the company will fail. It may succeed. But a $10 billion valuation with no product or revenue is a classic bubble signal. 

We saw similar behavior during the dotcom era. 

What Happens After the Bubble Bursts? 

If history is any guide, this is what usually happens: 

• The hype reaches a peak 

• Investor patience runs out 

• Stock prices crash 

• Weak companies disappear 

• Strong companies survive 

• The technology stabilizes and matures 

AI will not disappear. Just like the internet, it will become more practical, less hyped, and more integrated into real-world systems. 

What This Means for Your Career 

This is the most important part. 

Many people hear AI headlines and conclude that programming jobs are dead or that learning technology is pointless. 

That thinking is dangerous. 

If AI can automate coding, it can automate almost anything. Farming, medicine, and many other professions would also be at risk. So what should you do? Sit idle and do nothing? That approach will hurt the most. 

There are two mindsets you can choose from. 

The Pessimist Mindset 

• AI will take all tech jobs 

• Learning programming is useless 

• I should avoid technology 

This mindset leads to fear, inaction, and missed opportunities. 

The Optimist Mindset 

• AI is a powerful tool 

• I can use AI to boost my productivity 

• I can learn timeless skills like problem-solving, communication, and critical thinking 

• I can combine domain knowledge with AI tools 

This mindset turns AI into a career accelerator instead of a threat. 

Conclusion 

AI is powerful, just like the internet was powerful in the 1990s. But hype and reality are not the same thing. Many CEO statements and media narratives are exaggerated. The real impact of AI will be slower, more uneven, and more grounded than the headlines suggest. 

The bubble may burst, but AI will remain. Jobs will remain. Programming will remain. What will change is how we work. 

The smart move is not to fear AI, but to learn how to use it effectively. 

If you have questions or want to discuss how to prepare your career in the age of AI, drop them in the comments and let’s talk. 

Key Takeaways: 

• AI hype today closely resembles the dotcom bubble of the late 1990s 

• Massive AI spending is not yet matched by real revenue 

• AI will not replace all jobs but will reshape how we work 

• The best strategy is to use AI as a productivity tool, not fear it