---
id: "action-shift-ai-training-focus"
type: "action-item"
source_timestamps: ["§ Build AI competence."]
tags: ["ai-training", "prompt-engineering", "contextual-learning"]
related: ["framework-ai-competence-skills", "claim-ai-competence-gap"]
action: "Transition AI training from generic workshops to contextual, in-platform experimentation focused on problem framing and critical evaluation."
outcome: "Unlocking the promised 10-20% productivity gains and 30-50% efficiency enhancements by building true AI competence rather than mere tool adoption."
speakers: ["Sagar Goel", "Shubhankar Sohoni", "Lisa Krayer"]
sources: ["reskilling"]
sourceVaultSlug: "hbr-seg-reskilling"
originDay: 10
articleStem: "hbr-cl-86-genai-transform-l-and-d"
sourceUrl: "https://hbr.org/2025/09/how-gen-ai-could-transform-learning-and-development"
sourceTitle: "How Gen AI Could Transform Learning and Development"
---
# Shift AI Training from Adoption to Competence

## Action: Shift AI Training from Adoption to Competence

**Action.** Move away from generic 'Gen AI 101' workshops and e-learning modules. Instead, **embed internal learning tools directly onto Gen AI platforms** so employees practice [[concept-problem-framing]], discover **role-specific use cases**, and learn to **critically evaluate AI outputs** through contextual experimentation and feedback loops. This is the operational form of [[framework-ai-competence-skills]].

**Expected outcome.** Unlocking the promised **10–20% productivity gains** and **30–50% efficiency enhancements** by building **true AI competence** rather than mere tool adoption — the gap quantified in [[claim-ai-competence-gap]].

**Watch-out (expert overlay).** BCG's own research shows AI used *outside* its competence frontier can *reduce* performance (~23% worse on business problem-solving), and many users fail to challenge AI even when warned. Competence training must therefore explicitly teach **when to distrust** the tool, not just how to prompt it.