---
id: "action-assess-internal-literacy"
type: "action-item"
source_timestamps: ["§ Assess Managers' and Employees' AI Literacy"]
tags: ["management", "hr", "strategy"]
related: ["concept-ai-receptivity-paradox", "claim-high-literacy-disinterest"]
action: "Assess the AI literacy of managers and employees to prevent both overenthusiastic misuse and unwarranted underutilization."
outcome: "Calibrated AI adoption strategies that avoid blind spots in staffing and customer trust."
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"
---
# Assess Internal AI Literacy

**Action:** Assess the AI literacy of managers and employees to prevent both overenthusiastic misuse and unwarranted underutilization.

**Detail:** Managers must actively gauge the AI literacy of themselves and their teams to calibrate adoption strategies. *Low* literacy can lead to overenthusiastic deployment in suboptimal areas (the [[concept-ai-magic-effect]] misapplied); *high* literacy can cause unwarranted disinterest ([[claim-high-literacy-disinterest]] via [[concept-ai-demystification]]). Assessment tools surface these blind spots before they distort strategy — the internal-facing corollary of the [[concept-ai-receptivity-paradox]].

**Outcome:** Calibrated AI-adoption strategies that avoid blind spots in staffing and customer trust.

> **Enrichment:** Emerging AI-literacy frameworks distinguish conceptual understanding, practical skill, and critical reflection — so assessment should measure *critical* literacy, not just familiarity, to avoid both blind enthusiasm and blanket rejection.


## Related across articles
- [[action-invest-ai-literacy]]