Demo contentIllustrative record — no real organizations, statistics or outcomes.
Internal mobility
Internal Job Matching
Semantic matching recommends internal roles based on skills and career interests.
The problem
Employees miss relevant internal openings because job search is keyword-limited.
The opportunity
AI can reduce repetitive effort and surface options humans still decide — when grounded in the right data and oversight.
What the solution does
Semantic matching recommends internal roles based on skills and career interests.
How it works
Employee profiles and requisitions are embedded; ranked matches include explainable fit reasons.
Who uses it
- Employees
- Career coaches
- Talent marketplace owners
Data required
- Relevant HRIS / ATS records
- Role or policy context
- Access and consent rules
AI / technology patterns
- Semantic search
- Recommendation
- Embeddings
Reported impact
No independently reported impact recorded for this item yet.
Impact categories
- Experience
- Efficiency
Limitations and risks
Bias inheritance, stale data, privacy obligations and over-automation of people decisions. Keep humans accountable for outcomes that affect careers.
What implementation requires
Start narrow, define evaluation criteria, involve legal/HR governance early, and measure adoption plus quality — not only model accuracy.
Updated 2026-08-09