AI technology has become indispensable in the strategies of software companies, cloud providers, and hardware manufacturers in recent years. The use of AI is also growing within SMEs, for example, for customer service, data analysis, process automation, and fraud detection. But the question arises: are investments and expectations outpacing actual returns?
For entrepreneurs, this means critically examining where AI truly adds value. The technology is not going away, but a realistic reassessment is looming. Not every AI project yields immediate scalable profits. And in 2026, there will likely be more focus on this.
Why the Term 'AI Bubble' Is Circulating
The comparison with previous technological hypes, such as the dot-com crisis in the early 2000s, is not unfounded. Stock prices of companies positioning themselves as AI providers have soared, data centers are springing up, and investments in infrastructure are reaching record highs.
For entrepreneurs, it is important to understand that many of these investments are aimed at strategic positioning, not immediate profit. As long as confidence in future value remains, valuations stay high. But once market sentiment shifts, for example, due to economic pressure, a correction can follow quickly.
Higher Interest Rates and Economic Pressure
AI solutions are capital-intensive. This means they thrive best in an economy with low interest rates and readily available capital. If those conditions change, as is the case with persistent inflation and higher interest rates, the emphasis shifts to short-term returns.
For established technology companies with strong cash flows, this is often manageable. For young AI startups or businesses investing without a clear revenue model, it becomes more challenging. Companies using AI must increasingly demonstrate what the concrete added value is. Otherwise, you risk fading into the margins.
Using AI Smartly
Unlike during the internet bubble, AI is not a standalone product without application. It is deeply woven into business software, cloud solutions, and process automation. Think of applications like smart chatbots, predictive data analysis, and AI-supported reporting.
For entrepreneurs, it is especially important to see AI not as a 'standalone tool' but as an enhancement of existing IT processes. In many organizations, AI is already helping to work more efficiently, make faster decisions, or automate repetitive tasks.
Yet, the difference in results is significant. While some companies fundamentally improve their processes with AI, others mainly use it as a marketing tool. The distinction between hype and real impact will become sharper in 2026.
The AI Bubble in 2026
If 2026 becomes the moment when market expectations collide with reality, it will actually create opportunities for entrepreneurs. Technology will become more affordable, suppliers will compete more aggressively on price and service, and it will become clearer which applications are profitable.
Companies that systematically use AI for customer interaction, internal efficiency, or decision-making will be better prepared. At the same time, there will be less room for casual AI projects without clear ROI.
Whether or not the 'AI bubble' bursts: it is crucial for entrepreneurs to approach AI not as a hype but as a strategic tool. Here’s how to do it:
- Focus on Proven Applications: Concentrate on AI applications that directly contribute to time savings, customer satisfaction, or more efficient processes.
- Integrate AI into Your IT Strategy: Ensure that AI is not a standalone tool but an extension of existing systems.
- Look Beyond Marketing Claims: Not every AI feature delivers value. Select critically based on substantiation, practical experience, and scalability.
- Prepare for Sharper Choices: The time for casual experimentation is over. AI must contribute to results.
Stay Realistic
AI is not going away, but the context in which it is used is changing. A potential correction in 2026 does not mean a crash, but a maturation of the market. Companies that are already making clear choices, linking AI to business objectives, and not being swayed by hype are building sustainable digital resilience.
