The assumption that the most experienced person in a domain is also the most qualified to innovate within it is intuitive and empirically wrong in a specific and reproducible way. The cognitive mechanisms that produce expertise — schema deepening, pattern automation, and procedural chunking — are the same mechanisms that make familiar solutions dominant and non-obvious solutions structurally harder to perceive. The curse of expertise is not a character deficit or a failure of effort. It is a predictable consequence of how learning reorganises the brain.

Cognitive entrenchment

Dane’s 2010 paper in the Academy of Management Review introduced cognitive entrenchment as a formal construct: a high level of stability in one’s domain schemas — the mental representations through which an expert organises, interprets, and responds to domain-relevant information. As domain expertise deepens, schemas become larger, more complex, more interrelated, and more accurate. They also become more stable — reinforced by sustained practice, repeated application, and consistent confirmation across professional experience. This stability is the source of expert competence in stable environments and the source of expert creative limitation in changing ones. When a domain shifts, when a market disrupts, when an entrepreneurial problem requires a solution outside the established schema network, the expert’s existing representation of the problem actively suppresses search into genuinely novel territory.

The most experienced person in a domain approaches every new problem through the interpretive lens of an established schema network. They recognise what kind of problem it is, which category it belongs to, and what the appropriate response class is — automatically and often correctly in familiar conditions. But this categorisation is also the mechanism that makes the problem invisible as a novel challenge. The expert’s schema has already classified it, which means the search process that might find a genuinely new solution never fully initiates.

The Einstellung effect: familiar solutions block better ones

Bilalić, McLeod and Gobet’s chess experiments produced the most precisely documented demonstration of how expertise blocks better solutions. Expert chess players were given problems with two possible solutions: a familiar five-move checkmate sequence well-known to experts, and an optimal three-move sequence that was objectively superior but less familiar. Expert players consistently found the familiar solution first — and then, critically, failed to find the optimal solution despite reporting that they were continuing to search for it.

Eye-tracking data confirmed the mechanism. Once the familiar solution was activated, players’ visual attention continued to be directed toward the board regions associated with it — physically suppressing scanning of the regions where the optimal solution was located. The familiar solution did not just occupy their thinking. It actively redirected their attention away from the territory where the better answer was visible. Experts believe they are searching for alternatives; their attention architecture is preventing them from looking where the alternative is. The suppression is not conscious. It is an automatic consequence of schema activation.

The curse of knowledge

Camerer, Loewenstein and Weber documented the curse of knowledge in a trading experiment: participants with private information about the value of a commodity systematically overestimated how much their trading partners knew — because once information is held, the cognitive experience of not holding it becomes genuinely inaccessible. Expertise restructures memory and perception in ways that make naïve perspectives unavailable, not merely overlooked. The chess grandmaster does not see individual pieces; they see patterns. This compression makes it neurologically difficult to revert to the sequential, exploratory thinking that a novice would apply to the same problem.

The expert who cannot imagine not knowing something cannot perceive the genuine novelty that an outsider would see, cannot access the fresh question that the uninitiated would ask, and cannot generate the disruptive reframing that comes from encountering a domain without pre-existing categorical commitments. This is why the most transformative applications of a technology are often developed not by the technology’s creators but by people from adjacent domains who encountered it without established categorical commitments about what it is for.

Overconfidence and the closed schema

Tetlock’s 20-year forecasting study of nearly 300 domain experts making predictions about political and economic events produced a specific finding: experts were not significantly more accurate than non-experts in their predictions, and their greater confidence in those predictions made them systematically less responsive to disconfirming evidence. The more specialised the expert, the more coherent their explanatory framework — and the more strongly they maintained it against contradictory evidence. Broad, multi-perspective thinkers consistently outperformed deep single-framework specialists on prediction accuracy — not because they knew more, but because their shallower schema commitment made them more willing to update.

The innovation connection is structural. An expert who is overconfident in their understanding of a domain is underweighting the signals that suggest it is changing. The deep specialist certain they understand the market is least likely to register the early-warning signals of disruption — because those signals do not fit the schema their expertise has built, and overconfidence in that schema provides additional cognitive insulation against disconfirming evidence.

The InnoCentive confirmation

Analysis of InnoCentive’s open innovation platform — which posts unsolved scientific and technical problems from major organisations to a global network of external solvers — found that the provision of a winning solution was positively related to increasing distance between the solver’s field of technical expertise and the focal field of the problem. The further the problem was from the solver’s core expertise, the more likely they were to solve it. The mechanism is precisely what cognitive entrenchment and the Einstellung effect predict: peripheral expertise means the schema is related enough to generate useful search but not entrenched enough to redirect attention away from novel territory. Core expertise means the schema is so stable that novel solutions are rendered invisible by the attention-directing power of familiar approaches.

What to do with this

The practical implication is not that expertise has no value — it is that its value is most reliably in execution within an established domain, and its limitation is most reliably in perceiving what exists outside it. Deliberately introducing people with peripheral expertise, structuring problems in ways that prevent the obvious solution from being activated first, and seeking input from adjacent domains before from core domain experts are the applied interventions that the cognitive entrenchment research most directly supports.

Kodak invented the digital camera in 1975 and shelved it. Their expertise gave them a precise understanding of what digital photography would cost, how far it was from consumer readiness, and what it would do to their film business. Every assessment was accurate within the frame of their existing schema. What their expertise could not provide was the capacity to see outside the schema that defined their business. The cognitive apparatus that made them the world’s foremost experts in photographic film was the same apparatus that made the obvious strategic reframing invisible.

Book worth reading on this

Range by David Epstein is the most accessible treatment of why cognitive breadth outperforms deep specialisation in complex, changing environments. Epstein’s central argument — built across elite sport, scientific discovery, artistic innovation, and business — is that the ability to apply frameworks across domains, and the willingness to abandon a familiar framework when it stops fitting, predicts innovative performance better than the depth of investment in any single one. He covers the Einstellung effect and cognitive entrenchment research directly, and his evidence makes the case that the people most valuable in genuinely novel situations are rarely the deepest experts in the specific domain.

If the dynamics described here are significantly affecting your wellbeing, speaking with a psychologist is the right next step. UK: Samaritans (116 123, free, 24/7). Mind (0300 123 3393). BACP: bacp.co.uk/search/Therapists. Crisis Text Line — text HOME to 741741 (US, UK, Canada, Ireland). International: internationaltherapistdirectory.com.

This article is for educational and informational purposes only. Sources: Dane, E. (2010), Reconsidering the Trade-off Between Expertise and Flexibility: A Cognitive Entrenchment Perspective, Academy of Management Review, 35(4), 579–603. Bilalić, M., McLeod, P. & Gobet, F. (2008), Inflexibility of Experts — Reality or Myth? Quantifying the Einstellung Effect in Chess Masters, Cognitive Psychology, 56(2), 73–102. Bilalić, M., McLeod, P. & Gobet, F. (2010), The Mechanism of the Einstellung (Set) Effect, Current Directions in Psychological Science, 19(2), 111–115. Camerer, C., Loewenstein, G. & Weber, M. (1989), The Curse of Knowledge in Economic Settings, Journal of Political Economy, 97(5), 1232–1254. Tetlock, P.E. (2005), Expert Political Judgment, Princeton University Press. Jeppesen, L.B. & Lakhani, K.R. (2010), Marginality and Problem-Solving Effectiveness in Broadcast Search, Organization Science, 21(5), 1016–1033. Duncker, K. (1945), On Problem Solving, Psychological Monographs, 58(5). Epstein, D. (2019), Range: Why Generalists Triumph in a Specialised World, Riverhead Books. Kahneman, D. (2011), Thinking, Fast and Slow, Farrar, Straus and Giroux.