Euphoria Around AI and Rising Expectations

The years 2024 and 2025 will go down in investment history as a period of a massive boom around artificial intelligence. Stocks of AI-related companies have been rising at a pace reminiscent of the early days of the internet era. Investors are betting on chipmakers and computing infrastructure providers, on software platforms, as well as on industrial players in robotics and automation.

The valuations of technology giants have soared to record levels. NVIDIA has become a symbol of the “AI chip economy,” companies like OpenAI are defining a new generation of software, while industrial brands such as Boston Dynamics or ABB Robotics demonstrate that AI is no longer just about digital applications. At the same time, markets are grappling with a fundamental question: is the current wave of interest a real economic revolution — or just another overheated investment fad?

The Key Question: a Bubble or a Structural Megatrend?

Arguments from the “Bubble” Camp

Some analysts warn that current developments closely resemble the dot-com boom at the turn of the millennium. Back then, it was enough for a company to mention the internet in its name for its stock to skyrocket, even if it had no finished product or viable business model. A similar pattern can be seen today among companies that communicate an “AI strategy,” while their revenues so far are growing mainly on paper.

Concerns are reinforced by several factors:

• extremely rapid price growth over a short period of time,
• high dependence of the sector on a few dominant players,
• the risk of technological disappointment if development fails to meet inflated expectations.

Simply put: part of the market is speculating more on a story than on fundamentals — and that is a warning sign.

Arguments for “Solid Foundations”

On the other hand, there is the view that AI is not just another fashionable wave, but a technological infrastructure with an impact across the entire economy — similar to electricity or the internet in the past. Unlike the dot-com bubble, demand for AI technologies today is real, measurable, and quickly monetizable, meaning it can be translated into actual revenues relatively fast.

The main growth drivers today are not vision-driven start-ups, but companies that deliver:

• computing power and data centers,
• chips and accelerators for model training,
• automation systems in manufacturing and logistics,
• robotic solutions with an immediate impact on productivity.

Companies in industry, healthcare, or logistics are not investing in AI because it is trendy — but because it delivers lower costs, higher efficiency, and a competitive advantage. This is a fundamental difference compared to the internet euphoria of the year 2000.

AI Enters the Physical World: From Software to Robotics and Automation

For a long time, AI was associated mainly with digital services — search engines, language models, or smart applications. Today, however, a second phase is emerging: AI is moving into the physical world.

Algorithm-controlled robotic arms optimize production, autonomous vehicles streamline warehouse logistics, intelligent transport systems manage material flows in industry, and AI assistants support diagnostics in healthcare. Industry 4.0 is no longer just a vision, but increasingly a reality.

“Industry 4.0” refers to the current phase of industrial development. After the historical phase of initial mechanization (steam), followed by the use of electricity and mass production, and later automation and the use of computers in industry, today’s fourth phase connects manufacturing with digital technologies, automation, and artificial intelligence. It can be described as “smart industry,” where machines, systems, and software communicate with each other, evaluate data in real time, and part of decision-making happens automatically.

For investors, this means two things:

The importance of the “hardware layer” of AI is growing — chips, sensors, industrial systems, and robotic platforms.

Investments are made gradually and in waves — in practice, this often means that a company first purchases basic infrastructure, such as new robotic lines or computing servers for AI, and only later adds software and intelligent applications that fully leverage this hardware. A typical example is a manufacturing company that first invests in warehouse robots and only afterward implements an AI system for logistics planning and demand forecasting. Thanks to this gradual development, demand for AI technologies remains relatively stable even during weaker phases of the economy — companies have already committed capital to the transformation and need to continue building on it.

While software can experience a fashionable “hype” within a few months, robotics and automation advance step by step — but with a lasting impact on the productivity of entire industries. And it is precisely here that many investors see the deeper economic foundation of the current AI trend.

Conclusion: Short-Term Overheating, Long-Term Potential

So, is AI a bubble? In the short term, parts of the sector may indeed be “overvalued.” Some stocks have risen faster than company earnings, and a correction would not be surprising. Just as with the internet, however, it holds true that even though many projects disappeared, the technology itself changed the world — and the biggest winners remained.

Today’s valuations may include a large dose of optimism, but the long-term trend rests on solid foundations. The combination of AI, robotics, automation, and data infrastructure is not just an investment story — it is a structural transformation of the economy.

Don’t get carried away by euphoria or by simplistic headlines about bubbles. Consult with your advisor on how to intelligently leverage the megatrend of artificial intelligence in your investment strategy. At Stone & belter, we focus in detail on long-term trends and will be happy to discuss concrete solutions with you.