---
id: "prereq-tech-adoption-lifecycle"
type: "prereq"
source_timestamps: ["¶6"]
tags: ["business-theory"]
related: ["contrarian-education-adoption-link", "quote-challenging-adoption-assumptions"]
reason: "Provides the baseline conventional wisdom that the authors' findings directly challenge."
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"
---
# Technology Adoption Lifecycle

**Prerequisite:** Familiarity with the **Technology Adoption Lifecycle** and its standard models — the **Diffusion of Innovations** (Rogers) and the **Technology Acceptance Model (TAM)**.

**Why it's needed:** The authors repeatedly reference "a core assumption in tech adoption" — that education and understanding drive adoption ([[quote-challenging-adoption-assumptions]]). Without the baseline that innovators/early adopters are typically the most educated and tech-savvy, and that TAM predicts adoption from *perceived usefulness and ease of use*, the reader cannot appreciate why the findings are considered paradoxical and disruptive (see [[contrarian-education-adoption-link]]).

> **Enrichment:** The paradox does **not** invalidate these models — it identifies AI as a special case with strong emotional (awe) and ethical overlays. TAM still explains high-literacy *instrumental* adoption; Diffusion of Innovations is only inverted for the *creative/emotional* AI domain.