As talent shortages persist across Europe, organizations are seeking smarter, fairer ways to evaluate communication skills, which is the number-one success factor in customer-facing and team-based roles. Yet traditional language testing methods often pose barriers to inclusion and scale.
This presentation shares a real-world European case study in which Rosetta Stone partnered with Otonomee to implement AI-powered language assessments across multiple recruitment and training pipelines. Together, we deployed a fully automated, adaptive assessment engine that evaluates grammar, speaking, and writing proficiency—available 24/7, on any device, in nine global languages.
Key focus areas will include:
Innovation: How adaptive testing and AI-powered scoring created faster, more accurate candidate evaluations


Candidate Experience: How automated language testing improved access, flexibility, and fairness for diverse applicants across Europe


Collaboration: How our embedding the assessment into the hiring process ensured cultural and operational alignment across borders


Outcomes achieved:
- Faster time-to-hire
- Enhanced diversity in applicant pools
- Reduced attrition and improved onboarding outcomes
- Granular learner diagnostics used to personalize development plans

We will also discuss the ethical and operational implications of AI in assessment, including:
- Mitigating bias in automated scoring
- Balancing automation with human oversight
- Navigating GDPR and data privacy concerns in the European context