---
id: "concept-tacit-knowledge-d32"
type: "concept"
source_timestamps: ["§ What's Different About AI-Era Expertise"]
tags: ["epistemology", "expertise"]
related: ["concept-reverse-mastery", "entity-michael-polanyi", "entity-hubert-stuart-dreyfus"]
definition: "Deeply internalized, intuitive expertise that a professional can act upon without being able to fully explain or articulate it."
sources: ["reskilling"]
sourceVaultSlug: "hbr-seg-reskilling"
originDay: 10
articleStem: "hbr-edu-32-help-employees-get-better-with-ai"
sourceUrl: "https://hbr.org/2026/06/help-employees-get-better-not-just-faster-with-ai"
sourceTitle: "Help Employees Get Better—Not Just Faster—with AI"
---
# Tacit Knowledge

**Tacit knowledge** — a term popularized by scientist-turned-philosopher [[entity-michael-polanyi|Michael Polanyi]] — names the endpoint of traditional professional mastery: *'knowing more than we can tell.'* It aligns with the **Dreyfus model of skill acquisition** ([[entity-hubert-stuart-dreyfus|Hubert and Stuart Dreyfus]]), in which professionals move from consciously applying explicit rules (novice) to acting on deeply internalized intuition (expert).

Canonical examples from the source: a litigator who reads courtroom dynamics instantly, or a facilitator who senses unspoken criticisms in a workshop. Historically, expertise *rewarded* this internalization because the skill lived entirely inside the practitioner's head and was exercised directly.

The article's pivot is that AI inverts this incentive — see [[concept-reverse-mastery|reverse mastery]] and the [[contrarian-reverse-mastery|contrarian insight that intuition is now a liability]]. Tacit knowledge also explains why [[question-junior-employee-baseline|novices struggle to form a valid initial POV]]: they have not yet internalized what 'good' looks like.


## Related across articles
- [[concept-tacit-knowledge-d51]]
- [[prereq-tacit-vs-explicit-knowledge-d10]]
- [[concept-unconscious-competence]]