Deepseek’s emergence in the world of AI platforms sent shockwaves through the technology sector. Its recent launch has shaken the share prices of several semiconductor companies, as well as others making major investments in AI development. Why? With significantly lower implementation costs than its competitors, Deepseek can achieve results comparable to other AI chat systems that have benefited from much larger investments.
Technological advancements tend to follow a predictable cycle of enthusiasm, disappointment and maturation. For investors and finance professionals, understanding this process is key to making informed decisions. The Gartner Hype Cycle is one tool that can help us to visualise this trajectory and assess the true potential of new technologies.
Developed by the Gartner consultancy firm, the model outlines the evolution of a technology from its launch to widespread adoption. The cycle is represented by a curve with five distinct phases:
1. Innovation trigger: The technology appears on the market and sparks interest, but proven use cases are still lacking.
2. Peak of inflated expectations: The press and investors exaggerate the potential, causing a speculative bubble.
3. Trough of disillusionment: Many expectations go unmet, leading to a decline in investment in the technology.
4. Slope of enlightenment: Viable applications are identified, and companies refine the technology.
5. Plateau of productivity: The technology gains widespread adoption and proves its true value.
As investors, the Hype Cycle offers us a useful guide for assessing risks and opportunities. We should strive, as much as possible, to avoid the “peak of inflated expectations”, where technologies are often overvalued while companies are still struggling to monetise them.
The real opportunities lie in what is called the “Trough of Disillusionment”. When enthusiasm fades, opportunities may arise to invest at more reasonable valuations. Technologies such as blockchain have gone through this stage, with applications now beginning to gain traction.
This pattern in the evolution of technological advancements is nothing new; we have seen in before with other innovations. Asset tokenisation experienced a peak of inflated expectations during the NFT boom, then fell into the trough of disillusionment. It is now entering a consolidation phase with more sophisticated applications in financial markets. Another example is self-driving technology, which has seen its implementation forecasts scaled back after years of unfulfilled promises.
As we can see, the Gartner Hype Cycle is an essential took for assessing the evolution of emerging technologies. Artificial intelligence, in its various applications, is a clear example of how innovations can progress through this cycle. For investors, the challenge lies in identifying which advancements will eventually achieve sustainable adoption and which will fade into obscurity. This approach helps us to mitigate risks and to position ourselves strategically in emerging sectors.