---
id: "entity-lisa-krayer"
type: "entity"
entityType: "person"
canonicalName: "Lisa Krayer"
aliases: []
source_timestamps: ["§ Author Bios"]
tags: ["author", "researcher", "bcg"]
related: ["entity-boston-consulting-group", "entity-bcg-henderson-institute", "framework-responsible-human-ai-collaboration"]
speakers: ["Lisa Krayer"]
sources: ["agentic", "reskilling"]
isSpeakerEntity: true
---
## Segment 6 — agentic

## Article 16 — a016

# Lisa Krayer

**Role in this source:** Co-author of *"Research: Why You Shouldn't Treat AI Agents Like Employees"* (Harvard Business Review, 2026), affiliated with [[entity-boston-consulting-group-d6]] and the [[entity-bcg-henderson-institute-d6]].

**Profile:** One of the economists/advisors on the author team whose work on human-AI collaboration and workforce transformation informs the vault's guidance on evolving human roles toward judgment, relationship building, and managing ambiguity.

**Attributed contributions to this vault:**
- Co-author of the thesis and the experimental evidence ([[claim-identity-erosion]], [[claim-adoption-drivers]], [[claim-perception-gap]]).
- Co-designer of Step 5 of the [[framework-responsible-human-ai-collaboration]] (deliberate choices about how human work evolves) and the concept of the [[concept-agentic-unit]].

## Segment 10 — reskilling

## Article 86 — a086

# Lisa Krayer

## Lisa Krayer

**Profile.** Lisa Krayer is a **[[entity-org-boston-consulting-group]] people & organization expert**, most likely a [[entity-bcg-henderson-institute-d10]] fellow or senior team member. (Detailed public biography is limited; the enrichment overlay flagged this as 'BCG profile knowledge,' findable via company and LinkedIn searches.)

**Role in this source.** One of three co-authors of *How Gen AI Could Transform Learning and Development* for [[entity-org-harvard-business-review-d86]], grounded in the Henderson Institute Gen AI tutor experiment.

**Attributed contributions (this vault).** As a co-author, attributed to the full thesis and every claim, framework, and quote here — including the core [[concept-gen-ai-tutor]] argument, the experimental claims [[claim-ai-tutor-personalization]] / [[claim-ai-tutor-efficiency]] / [[claim-lower-competency-gains]], and the closing [[concept-second-wave-gen-ai]] framing quoted in [[quote-second-wave]].