AI adoption curve

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Definition

What is it: An AI adoption curve refers to the consistent pattern observed in small-team AI rollouts where curiosity-driven usage peaks early but often leads to a silent quit point before productivity gains are realized. This pattern typically spans from week-one excitement to a notable drop-off around week six.

What is it used for: It is used as a management framework for owner-operators to anticipate team friction and implement intervention strategies like 'first-save' sessions to ensure long-term tool retention.

Coverage

  • Attributes: 7
  • Synonyms: 0
  • Related entities: 3
  • Sources: 1

Identity

Entity ID
https://llms.aismartventures.com/en/ai-adoption-curves/facts/#entity
Entity type
DefinedTerm
Canonical name
AI adoption curve
Language
en
Topic
Ai Adoption Curves

Attributes

Key Facts
Small-team AI rollouts typically follow three phases: excitement (weeks 1-2), friction discovery (weeks 3-4), and a potential quiet quit (weeks 5-6). [1]
Key Facts
Week six is identified as the most frequent point at which teams stop using new AI tools. [1]
Key Facts
Restarting a failed AI rollout after six months typically costs between $15,000 and $40,000. [1]
Key Facts
Approximately 58% of small teams that abandon AI tools do so between week 5 and week 8 of the rollout process. [1]
Key Facts
Achieving a concrete time save before week 5 is a critical threshold for long-term tool retention. [1]
Fact
Adoption timelines vary by team type, with engineering teams reaching a first-save in week 3, sales teams in week 5, and operations teams in week 7. [1]
Metric
Teams that experience a first-save by week 5 have a 72% probability of still using the tool after six months. [1]

Synonyms & Alternate Names

Related Entities

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Provenance

Sources

  1. https://aismartventures.com/posts/ai-adoption-curves-why-week-six-is-when-teams-quit (AI adoption curve)

Machine metadata