---
id: "prereq-tacit-vs-explicit-knowledge-d6"
type: "prereq"
source_timestamps: ["§ Where and When to Use Generative AI"]
tags: ["knowledge-management", "epistemology"]
related: ["concept-knowledge-type-tacit-vs-explicit", "framework-gen-ai-deployment"]
reason: "Forms the horizontal axis of the core strategic framework."
source_url: "https://hbr.org/2025/11/the-gen-ai-playbook-for-organizations"
source_title: "The Gen AI Playbook for Organizations"
sources: ["agentic"]
sourceVaultSlug: "hbr-seg-agentic"
originDay: 6
articleStem: "hbr-cl-87-genai-playbook-orgs"
sourceUrl: "https://hbr.org/2025/11/the-gen-ai-playbook-for-organizations"
sourceTitle: "The Gen AI Playbook for Organizations"
---
# Epistemology of Knowledge Work (Polanyi)

**Prerequisite knowledge.** While the authors define explicit and tacit knowledge within the text, a foundational grasp of **Michael Polanyi's** concept of *tacit knowledge* — that which cannot be easily codified or transferred ("we know more than we can tell") — helps one deeply understand why AI struggles in the [[concept-human-first-zone|Human-First]] and [[concept-creative-catalyst-zone|Creative Catalyst]] zones.

**Why it's required.** It forms the **horizontal axis** of the core [[framework-gen-ai-deployment|deployment framework]] (see [[concept-knowledge-type-tacit-vs-explicit]]). Subsequent knowledge-management literature explores the limits of codification and automation in tacit domains such as leadership, strategy, and therapy — the same domains the framework flags as resistant to full automation.