Innovation should be judged by evidence, not infatuation.

Thesis: The Hype Cycle Doesn’t Chart Technology Maturity — It Charts Our Infatuation Curve

We like to think of the Hype Cycle as a tidy chart of innovation maturity. In reality, it is closer to a mirror. It reflects our emotional swings around new technology rather than the actual capability, readiness or value of the technology itself.

By drawing a familiar rise, crash and recovery pattern, it does more than describe market psychology. It can start to script it. Organisations rush in when novelty is dazzling, pull back when disappointment sets in, and then wait for permission to re-engage once the curve says the technology has become safe. The result is predictable: inflated bubbles, abandoned breakthroughs and a decision environment where sentiment can outrun evidence.

The problem becomes more serious when a technology’s position on the curve starts influencing capital allocation, executive attention and adoption timing. A premature “Peak of Inflated Expectations” can send investment stampeding towards weak use cases. A “Trough of Disillusionment” can stall promising work just when disciplined experimentation is needed. By the time the model signals that it is safe to re-engage, the need may have changed, the opportunity may have moved, or a competitor may already have converted the technology into advantage.

The Hype Cycle can also shape behaviour at both ends of the adoption curve. For the late majority, it offers comfort and a reason to wait. A “Trough” label can make delay feel like prudence, turning inaction into a socially validated strategy. For early adopters, it can create hesitation. A “Peak” can make them look like hype-chasers, while a “Trough” can make even capable innovators pause. In both cases, the chart does not simply reflect sentiment. It can influence when action feels acceptable.

Strip away the technology language and the curve starts to look like an Infatuation Curve. It is the same emotional arc we recognise in a new romance, a dream job or the hobby we were convinced would change our life. First comes fascination. Then disappointment. Then rationalisation. The curve may be useful as a study of mood, but it should not be mistaken for a reliable assessment of capability.

That is why organisations need a better basis for innovation decisions. The Innovation Fitness Scorecard offers an alternative. It evaluates real-world deployments through evidence of readiness, adoption, impact and economic viability. It asks whether the technology is working, where it is being used, what value it is delivering and whether it can scale.

The future should not be dictated by market mood swings or by the comfort of waiting for someone else to move first. It should be shaped by evidence, judgement and the disciplined assessment of what is actually fit for use.