From hype to real value: how to strategically evaluate the Hype Cycle?

Every year, Gartner publishes over 130 Hype Cycles for companies to track the potential of more than 1,900 technological innovations across different segments. This material is eagerly awaited by technology, innovation, and strategy executives worldwide. The model, which presents the trajectory of adoption and maturity of emerging technologies, has become a guide for informing investments and strategic decisions. However, for Brazilian companies, interpreting this cycle requires a more pragmatic perspective, often adapted to our economic and regulatory reality. 

In this article, we point out ways to interpret the Gartner Hype Cycle within the reality of Brazilian companies, highlighting its limitations in technological prioritization. It presents strategic questions to avoid decisions based on trends and discusses the use of the Objective Maturity Card Game as a strategic tool. Ultimately, our goal is for you to make more conscious decisions, aligned with the context and organizational maturity.

What is the Gartner Hype Cycle?

The Hype Cycle describes five phases that a technology tends to go through:

1. Technological Innovation (Innovation Trigger): when the technology emerges and gains visibility.
2. Pinnacle of Inflated Expectations (Peak of Inflated Expectations): marked by enthusiasm, promises, and often exaggerations.
3. Trough of Disillusionment (Trough of Disillusionment): when practical limitations begin to appear.
4. Slope of Enlightenment (Slope of Enlightenment): maturation and better understanding of real uses.
5. Plateau of Productivity (Plateau of Productivity): when the technology consolidates and generates consistent value.

The model is useful for signaling trends, but it should not be viewed as a linear or universal roadmap.

How can the Gartner Hype Cycle be interpreted in light of the reality of Brazilian companies?

The Gartner Hype Cycle is a tool for understanding how emerging technologies evolve, from initial enthusiasm to the point at which they truly begin to generate value. But when we look at the context of Brazilian companies, interpreting this cycle needs to go beyond theory.

In Brazil, adopting a new technology involves a more complex equation. Here, factors such as budget constraints, infrastructure, and an organizational culture that is generally more risk-averse make the adoption journey less predictable than the graph suggests.

While global companies may agilely dive into innovations that are still at the “peak of inflated expectations,” many Brazilian companies need to wait for more concrete signs of maturity before investing. And this is not necessarily a sign of weakness; it is a strategic adaptation to the reality of our market.

The secret lies in using the Hype Cycle as a critical lens and not as a manual. Instead of asking, “Is this technology a trend?” it is worth reflecting: “Does this trend make sense for my business, at my moment, with the resources I have?” Changing the perspective is essential for innovation to happen consistently and effectively.

What are the limitations of the Hype Cycle in prioritizing technologies within business strategies?

The study “An Empirical Analysis of Hype-cycle: A Case Study of Cloud Computing Technologies” analyzed the correlation between the hype cycle proposed for cloud computing technologies and real market signals, such as media mentions and online search volume. The research identified that while some phases of the cycle, like the peak of expectations or the trough of disillusionment, do manifest in the data, the timing and intensity with which this occurs can vary significantly.

This observation reinforces the importance of understanding the Hype Cycle as a decision-making support tool. Below, we point out the main limitations. 

Lack of connection to the company’s objectives

One of the main limitations of the Hype Cycle in defining technological priorities is that it does not capture the competitive context or the strategic objectives of each organization. The model suggests where a technology stands in terms of maturity and expectation, but it does not indicate its relevance in accelerating differentiation, responding to market movements, or meeting specific growth goals.

Disregard for the interdependence between technologies

Another critical point is that the Hype Cycle ignores the interdependence between technologies. In many cases, the adoption of an innovation only generates value when combined with others, such as AI with data, or automation with cloud infrastructure. By treating each technology in isolation, the model can distort its priority within a more integrated and complex digital ecosystem.

Absence of perspective on organizational readiness

The Hype Cycle also does not take into account the internal learning curve and the time needed to scale a technology within the company. Market maturity does not equate to organizational readiness. In a solid business strategy, the timing of adoption, when and how to implement, is just as important as the choice of technology itself.

Indistinction between incremental and transformational innovation

Lastly, the model does not distinguish between incremental innovations, which optimize existing processes, and transformational innovations, which can radically change the business model. For leaders who need to balance operational efficiency with exploring new strategic frontiers, this distinction is essential, and it is absent in the perspective presented by the Hype Cycle.

How does the Hype Cycle induce hasty decisions and how to avoid hype traps?

The promise of being ahead of the competition leads many companies to move quickly in the face of an emerging technology. It is precisely at this moment, when an innovation reaches the so-called “peak of inflated expectations,” that the Hype Cycle can inadvertently stimulate hasty decisions, especially in corporate environments driven by pressure for innovation.

The psychological effect of hype

When a technology gains visibility on the Hype Cycle, it naturally attracts attention from the media, suppliers, consultants, and investors. This creates a sense of urgency, the fear of “falling behind.” In this scenario, leaders may feel pressured to initiate pilots or make investments without a deeper analysis of business fit, technical maturity, or scalability.

The risks of impulsive decisions

This rush can result in poorly structured initiatives with low returns or premature abandonment. Worse: it can divert resources from more strategic and well-founded projects. Adopting something just because it is highlighted in the cycle, without a clear diagnosis of value and feasibility, is one of the most common traps observed in organizations of all sizes.

How to avoid these traps

For the Hype Cycle to be an ally, and not a source of strategic anxiety, it is important to adopt a more balanced approach:

• Evaluate internal timing, not just market timing: Before any movement, analyze whether the company is ready in terms of culture, processes, and people to adopt that technology.
• Validate with data and controlled experimentation: Use proof of concepts (PoCs) with clear and measurable objectives before scaling any solution.
• Integrate the Hype Cycle with more robust decision-making frameworks: Combine trend insights with analyses of ROI, TCO, and impact on the core business.
• Prioritize problems, not technologies: Instead of seeking an application for a new technology, start with the organization’s real challenges and look for technological solutions that make sense for them.

What questions should be asked before investing in Hype Cycle technologies?

Decision-making regarding new technologies should not be guided solely by the stage they are in on the Hype Cycle. For the choice to be strategic and sustainable, technology and business leaders need to go beyond generic analyses and provoke targeted discussions. Below are questions that help divert from excitement and align innovation with value. 

Does this technology solve a real bottleneck in operations or create a new competitive capability?

Before investing, it is essential to map whether the technology addresses a critical point. 

• For example: “We are considering RPA for automation, but our processes are already standardized and with low variability. Would the gain be marginal?”

If the answer is yes, it may be time to consider another type of innovation, such as cognitive automation or process reengineering.

Do we have the data, talent, and governance to sustain this technology in production?

Many technologies depend on invisible foundations. 

• In the case of generative AI, for example: “Are our data structured, up-to-date, and of good quality to feed AI models? Do we have a MLOps plan or just an experimental chatbot?”