Case study ·
Kariyer.net (B): measuring AI adoption
Original title, in French: “Kariyer.net (B): Measuring AI Adoption ^ 527006”
- Publication
- Harvard Business Review (United States) · subscribers only
- Authors
- Shunyuan Zhang, Gizem Cihan Dincsoy
- Published on
- 17 September 2026 · read in the publisher's feed
Summary
This Harvard Business School teaching case focuses on Kariyer.net, an online recruitment platform in Turkey led by Fatih Uysal. The company invested in AI features designed to support hiring decisions, but found that many customers were not actively using these tools despite strong technical performance and stated demand. The team then redesigned products and workflows to build recommendations and automated decisions more fully into recruiters' daily processes, which improved activation rates and customer engagement by 2026. A new problem emerged, however: the company could track feature activation and usage, but could not tell whether recruiters actually relied on the AI's recommendations or whether these improved hiring outcomes, raising the question of how to define and measure adoption.
Summary based on the beginning of the article, the rest being restricted to subscribers.
Read the article on Harvard Business Review →Classification
- Country
- Türkiye
- Company size
- All sizes
- Industries
- Consulting, legal, accounting, business services
- Companies
- Kariyer.net (deploys AI)
- Keywords
- recruitment, ai adoption, human resources, adoption measurement, turkey
Entry written by Marsanne Studio from the cited article, with the help of an AI model (claude-sonnet-5). The rights to the article and its illustrations belong to Harvard Business Review and its authors. Entry translated from French by Claude Sonnet 5.5.