Comment Choisir une Plateforme de Recrutement IA : Checklist Acheteur

Why a Checklist Matters

The AI hiring market is growing fast, with dozens of tools claiming to "revolutionize recruitment." But behind the marketing, platforms vary dramatically in how they evaluate candidates, handle data, and comply with regulation.

This checklist focuses on the criteria that separate tools that genuinely improve hiring quality from those that just automate existing problems.

1. Evaluation Methodology

Question to ask: How does the AI evaluate candidates? Is it personality-based, keyword-based, or competency-based?

What to look for:

• Competency-based evaluation with defined scoring rubrics — not personality profiling or sentiment analysis
• Evidence-linked scores — every rating should link to specific candidate evidence, not just a number
• Structured frameworks — the platform should enforce consistent questions and scoring across candidates

Red flag: If the platform gives you a single "fit score" without explanation, you can't verify or challenge the result. Avoid black-box scoring.

2. AI Transparency and Reproducibility

Question to ask: Can I get the same evaluation result if I run it again on the same data?

What to look for:

• Deterministic AI — temperature 0, fixed seed means the same input always produces the same output
• Visible scoring logic — you should see which competencies were evaluated, what weights were used, and how the final score was calculated
• Audit trail — every evaluation, score change, and user action should be logged

Why it matters: Under the EU AI Act, you need to explain how AI decisions were made. If the platform can't reproduce its own results, you can't defend them.

3. Compliance Architecture

Question to ask: Is the platform designed for EU AI Act and GDPR compliance, or is compliance an afterthought?

Must-haves for EU organizations:

• No prohibited practices — no emotion recognition, personality profiling, social scoring, or biometric categorization
• Human oversight — AI scores shown alongside human ratings, never replacing them
• Bias detection — automated monitoring across protected categories
• GDPR consent management — granular consent categories, not a single checkbox
• DSAR support — built-in data export and erasure workflows

Red flag: "We're working on GDPR compliance" in 2026 means the platform wasn't designed with compliance in mind.

4. Data Residency and Security

Question to ask: Where is my data stored and processed? Does candidate data leave the EU?

What to look for:

• EU-hosted infrastructure — data should be stored and processed within the EU (e.g., Azure West Europe, AWS Frankfurt)
• No US data transfers — Schrems II (2020) invalidated the EU-US Privacy Shield; transfers require Standard Contractual Clauses at minimum
• Encryption — data at rest and in transit
• SOC 2 or ISO 27001 — independent security certification

5. Integration Capabilities

Question to ask: Does the platform integrate with my existing ATS and calendar tools?

Key integrations to check:

• ATS import — can you import existing candidates from your current system? Check which providers are supported (Greenhouse, Lever, Workable, Ashby, BambooHR, Recruitee are the major ones)
• Calendar sync — Google Calendar and Microsoft Outlook integration for scheduling
• Meeting recording — automatic recording and transcription for Google Meet and Microsoft Teams
• API access — for custom integrations and data export

Consider: Some platforms require you to abandon your existing ATS entirely. Others work alongside your current tools. The latter is usually lower risk for adoption.

6. Interview Modes

Question to ask: What types of interviews does the platform support?

Common modes:

• Built-in video — the platform has its own video interview tool
• AI-led screening — autonomous AI interviews for initial screening (asynchronous)
• Meeting recording — join and record external meetings (Google Meet, Teams, Zoom)
• Live interview assistance — real-time suggested questions and scoring during live interviews

The most flexible platforms support multiple modes. Your team should be able to choose the right mode for each stage of the process rather than being locked into one approach.

7. Reporting and Analytics

Question to ask: What hiring data can I see, and can I export it?

Essential reports:

• Hiring funnel conversion rates
• Time-to-hire and stage-by-stage duration
• Interviewer calibration and consistency
• Score distribution and quality metrics
• Diversity and adverse impact monitoring

Bonus: AI-generated dynamic reports where you can ask questions in plain language rather than navigating dashboards. See Key Hiring Metrics Every Team Should Track for the full list.

8. Pricing Model

Question to ask: What's the pricing model, and are there hidden costs?

Common models:

• Per-seat pricing — can get expensive fast when scaling the hiring team
• Per-job pricing — unpredictable costs for high-volume hiring
• Per-interview pricing — AI evaluation charged per use
• Flat-rate pricing — predictable monthly cost regardless of volume

Watch for hidden costs: AI evaluation add-ons, recording storage fees, ATS integration charges, and per-user overage fees. The best pricing models are transparent and predictable.

Evaluation Framework

Score each platform on these 8 criteria (1–5 scale) and weight by your priorities:

Summary

The best AI hiring platform is the one that makes structured hiring easy to implement and maintain. Focus on evaluation quality, transparency, and compliance over feature counts. A platform that gets the fundamentals right — evidence-linked scoring, deterministic AI, and human oversight — will outperform one with 50 features and no structure.

Further Reading

• What Is Structured Hiring?
• EU AI Act and Recruitment
• AI Interview Best Practices for Hiring Managers
• Key Hiring Metrics Every Team Should Track