---
id: "claim-high-literacy-disinterest"
type: "claim"
source_timestamps: ["§ Assess Managers' and Employees' AI Literacy"]
tags: ["employee-behavior", "tech-savviness"]
related: ["concept-ai-demystification", "action-assess-internal-literacy"]
confidence: "high"
testable: true
speakers: ["Chiara Longoni", "Gil Appel", "Stephanie M. Tully"]
sources: ["adoption"]
sourceVaultSlug: "hbr-seg-adoption"
originDay: 9
articleStem: "hbr-edu-39-understanding-ai-not-embrace"
sourceUrl: "https://hbr.org/2025/07/why-understanding-ai-doesnt-necessarily-lead-people-to-embrace-it"
sourceTitle: "Why Understanding AI Doesn’t Necessarily Lead People to Embrace It"
---
# High AI literacy leads to disinterest due to lack of novelty

**Claim (confidence: high, testable):** Managers and employees with high AI literacy exhibit greater caution or disinterest toward AI adoption. This is **not** because they believe the AI performs poorly — it is because their technical understanding ([[concept-ai-demystification]]) strips the technology of novelty and its transformative feel, producing a less emotionally driven, highly pragmatic view of utility. This drives the management guidance in [[action-assess-internal-literacy]].

> **Validation (enrichment): Conceptually supported, needs nuance.** The [[entity-org-center-for-ai-policy]] warns "our most tech-savvy citizens might be our biggest skeptics," and the [[entity-org-gw-trustworthy-ai-initiative]] notes high-literacy individuals do not experience awe in the same way. **But** heavy adoption in developer and data-science communities (GitHub Copilot, Vertex AI, agent frameworks) shows high-literacy users are not broadly "disinterested" — their criteria differ. Per the Technology Acceptance Model, they adopt on *perceived usefulness and ease of use* (capability, speed, integration), not "wow factor." Best read: high literacy dampens **emotional** enthusiasm while it can *increase* **instrumental** adoption where benefits are clear.