Artificial intelligence is everywhere right now. We use it to write emails, generate images, recommend videos, and even help study English. Some people believe AI will completely change the world, just like the internet did. Others are more sceptical and worry that the excitement has gone too far.
Every day on the news, we hear about new AI startups worth billions of dollars, governments investing huge amounts of money, and tech companies racing to become the next AI leader. There is a lot of optimism, but also a lot of hype.
Some people are starting to question whether we are we seeing real, long-term growth, or are we living through an AI bubble?
In todayโs episode of Thinking in English, weโll explore what an economic bubble really is, look at famous bubbles from history, and ask whether artificial intelligence is following the same pattern or whether this time is different. At the same time, weโll learn some useful English vocabulary!
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Vocabulary
- Economic bubble (noun): a situation where prices rise far above real value and then suddenly collapse.
- The dot-com boom became an economic bubble when company prices rose too fast and then crashed.
- Hype (noun): excitement that makes something seem more important or valuable than it really is.
- There is a lot of hype around AI, with some people believing it will change everything.
- Valuation (noun): an estimate of how much a company or asset is worth.
- The companyโs valuation reached billions of dollars, even though it was not making profit.
- Speculation (noun): investing or making decisions based on guesses about the future rather than solid evidence.
- Many people invested in AI companies based on speculation, not real results.
- Overvaluation (noun): when something is priced much higher than its true or real value.
- Some experts worry that AI start-ups are facing serious overvaluation.
- Investor (noun): a person or organisation that puts money into something hoping to make a profit.
- Each investor hoped the AI company would grow and make them money.
- Crash (noun): a sudden and dramatic fall in prices or value.
- After the bubble burst, the stock market experienced a major crash.
AI in 2026
Artificial intelligence, or AI, is changing the world very quickly.
You have definitely heard of tools like ChatGPT or Google Gemini. They can write emails for you, generate example questions for an IELTS test, and [00:04:00] instantly process long articles into bullet points.
There are also image generators that can create pictures from words, and many companies are using AI to automate tasks that used to need people, like answering customer questions or analyzing data. Even driving cars.
AI is becoming part of everyday life, I think. AI is used in schools, hospitals, offices, entertainment.
At the same time, AI is growing very fast in business. Startups and new companies are appearing all over the world. Some of these companies are reaching billion dollar valuations in just a few years. This means investors think these companies are worth a lot of money, even if they’re not yet making big profits.
Governments are also investing heavily in AI research and technology.
So all of this growth and excitement creates a lot of attention and investment. People talk about AI as if it will change everything. It will change education, medicine, business, daily lives and more.
But is this growth real? Is this growth sustainable? Or is it like a bubble, where prices and expectations are higher than the real value?
Defining Economic Bubbles
Actually, we should probably define the term “bubble” in this context.
A bubble [00:06:00] is a situation in economics or finance when the price of something, like houses or companies, becomes much higher than its real value. People pay more money than the thing is really worth because they expect the price to keep going up.
Bubbles usually happen when there is a lot of hype or excitement about a new opportunity. People see others making money and they do not want to miss out. This feeling is now commonly called FOMO, the Fear Of Missing Out.
There are some key features of a bubble.
The first thing is speculation.
This is where people speculate about the price, which means they form an idea or a theory based on guesses, without any real evidence.
People buy something or invest in something because they expect the price to rise, not [00:07:00] because of the real value. They are guessing that the price is going to be higher in the future.
The next thing is overvaluation. Overvaluation means that the price goes far above the true value of the product or the company or the asset.
A good example of overvaluation is in the early days of the COVID pandemic, when things like antibacterial hand sanitizer and masks, which typically are quite cheap, were being sold for really high amounts of money.
The next feature of a bubble is rapid growth. Prices increase quickly in a short time.
Bubbles are not always bad. They often happen when new technology or new [00:08:00] ideas excite people. Even if a bubble bursts, it can leave behind useful innovation, useful technology.
For example, the dot-com bubble in the early 2000s, which I’ll discuss very soon, caused many companies to fail, but the internet continued to grow and is now part of everyday life.
So in short, a bubble is a mix of hope, excitement, and too much optimism. People believe something is more valuable than it really is, and this can create a risky situation.
Examples of Bubbles
To understand whether AI could be a bubble, I think it would be helpful to look at some famous examples from history.
I’ll discuss three of the most famous historical bubbles, which show how bubbles start, grow, and eventually burst.
Historical Bubbles: Tulip Mania
One of the earliest recorded financial bubbles [00:09:00] is Tulip Mania, which occurred in the Netherlands during the 1630s.
If you don’t know, a tulip is a type of flower. In the 17th century, tulips were new to Europe. Their bright colors and unusual patterns made them extremely popular among wealthy people.
Some tulips were rare or had broken colors caused by a virus, which made them even more desirable. Initially, tulips were just a simple luxury flower for gardens, but speculation soon took over.
People began buying tulips to sell them for profit. Prices started to rise rapidly. More people began to speculate on the price. They would buy tulip bulbs with the hope or the idea that they would be able to sell them for more money in the future.
Ordinary people and [00:10:00] merchants began investing their savings in tulips, believing the prices would continue to increase.
At the peak of tulip mania, some rare flowers were reportedly worth more than 10 times the annual income of a skilled worker and more than the price of a normal house.
However, in 1637, the market collapsed. People realized that tulip bulbs had no value. They had no real value other than being a flower.
Buyers quickly disappeared and people who owned tulips, had invested their money, now just had some flowers dying in their store rooms.
Prices fell dramatically. People were financially ruined. And actually the Dutch economy suffered a temporary shock.
Historical Bubbles: The Dot-Com Bubble
Another bubble happened in the 1990s and the early 2000s. We now call it the [00:11:00] dot-com bubble.
The dot-com bubble happened during the 1990s when the internet became widely available and widely popular.
New technology companies, often called “dot-coms” because of their “.com” website addresses promised to revolutionize business, communication and shopping by using the internet.
This sounds obvious today, but in the 1990s and early 2000s, it was a new and exciting thing. And investors were really eager to put money into internet companies.
They invested even if the company had no profits. Or actually had no product, in some cases. Companies like pets.com became famous examples. They raised millions of dollars from investors, even though their business models were unrealistic.
But the hype of the dot-com bubble led to pets.com becoming a public company in the year 2000. They raised over $300 million from investors. Less than a year later, the company was bankrupt and gone.
In the dot-com bubble, stock prices of these tech companies rose rapidly, and people felt the fear of missing out. They bought shares, they hoped the price would keep rising.
At the peak of the bubble, many companies had market valuations far higher than the value of their actual business. By 2000, reality began to catch up.
Many [00:13:00] companies failed and went bankrupt. The NASDAQ Stock Index, which included many tech companies, lost nearly 80% of its value. Millions of investors lost money, and the US economy entered a mild recession.
However, companies like Amazon, Google, and eBay survived. They became profitable and eventually dominated the digital economy.
Even though the bubble burst, some valuable innovation remained and grew.
Historical Bubbles: The Housing Bubble
The housing bubble of the 2000s is another recent and well-known example.
[00:14:00] Basically, the banks were giving people mortgages, loans, who couldn’t afford those loans. Many people used this money to buy houses as investments. They believed that property values would always rise, houses would always become more expensive.
Financial institutions also created complex financial products called mortgage backed securities, which basically bundled many risky loans together and then sold them. Investors around the world bought these securities believing they were safe.
By 2007, the bubble had grown very large. Eventually, too many homeowners could not pay their loans, and the housing market began to collapse.
Prices fell sharply. Banks failed or needed government bailouts. And the world entered a financial crisis in 2008. Millions of [00:15:00] people lost their jobs, lost their savings, and lost their homes.
Is AI a Bubble?
So now we have looked at those examples of past bubbles, is AI a bubble?
The valuation of many businesses connected to AI are skyrocketing. I mentioned Nvidia earlier in this episode, which is now the most valuable company in the world. Many AI startups are also reaching billion dollar valuations.
However, there is a problem with many AI startups. They’re not making money. Many are not making significant profits. They’re losing money.
Investors right now are paying for future potential rather than real results. Just like in historical bubbles, there is a lot of hype.
Media headlines suggest AI is going to change everything, and people fear missing out, which leads to [00:16:00] more investment.
I think there are also some unrealistic expectations about AI. Some companies and investors overstate the capabilities of AI.
Now, we all know AI is powerful, but it’s not perfect. It may become better in the future or it may not. Overconfidence can create this imbalance where the perceived value and the actual value are different.
And while AI is expanding quickly, some models are very expensive to train and run. And not every AI application will generate a profit. This situation is similar to the dot-com companies that had huge hype but no solid revenue.
I think some companies that exist now will definitely become massive and successful giant corporations like the survivors from the dot-com bubble, [00:17:00] maybe Google and Amazon.
But it’s also likely some of these startups will be more similar to pets.com.
Maybe AI is not a bubble…
However, there are of course people who believe AI is not a bubble.
Unlike past bubbles, AI is already solving real problems. It’s used in medicine, translation, customer service, research, and creative industries.
The transcript for this episode you are listening to right now is created using AI technology.
It’s not like a tulip bulb from the 1700s, AI is actually a useful thing. Governments and large corporations are also building systems and platforms based on AI. I think this suggests some long-term investment rather than short term speculation.
And even if some AI companies fail and some will fail, the technology will continue to grow just as the internet survived the dot-com bubble.
Potential Consequences of an AI Bubble Burst
[00:18:00] So, if AI is in a bubble, what could happen if it bursts?
A burst bubble happens when prices, investments, or expectations suddenly fall. And reality no longer matches the hype. And as we saw earlier in this episode, burst bubbles can have serious consequences.
People who invested in overvalued AI companies could see their investments drop sharply in value.
As we saw with the dot-com bubble, this could also mean a collapse in the value of stock exchanges as well as individual companies.
So this doesn’t just affect people investing directly in the company, but also people who maybe their pension is tracked along to a stock exchange. If the stock exchange falls, so does your pension.
Startups or even larger companies that rely on this hype rather than solid business models probably will go bankrupt. [00:19:00] And if companies fail, then workers will lose their jobs.
There is also a risk that too much money is being invested in AI and not enough in other useful areas. Money might go to these trendy AI projects instead of practical solutions or better technology.
Some AI products will fail to meet our expectations, and companies may choose to use the label “AI powered” for hype rather than true technological advancement. If AI does not meet people’s high expectations, then our trust in the technology could decrease.
Overhyped claims can create fear about AI taking jobs or making decisions, even when the technology is not yet able to do that. And governments may delay some regulation because of overconfidence or panic after a bubble bursts.
However, even when [00:20:00] bubbles burst, not everything is lost. Just like the internet survived the dot-com bubble, AI could continue to grow and improve. The key difference is that today AI already has real applications and real value, which I think could make it more resilient than past bubbles.
Final Thought
We have explored the idea of a “bubble” in this episode, looking at history and asking whether AI might be in one.
A bubble happens when people expect more value than something actually has. Bubbles are driven by excitement, speculation, and sometimes the fear of missing out. History shows us that bubbles can be risky, but they often leave behind innovation and new technology.
When it comes to AI, the picture is [00:21:00] mixed. There are signs of hype and overvaluation, which is very typical of bubbles. At the same time, AI already has real value. It’s solving problems in medicine and business, education and entertainment.
Even if some AI companies fail, I think the technology itself will likely continue to grow and change the world.
But what do you think? Is AI a bubble? How can we use AI responsibly?
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