Sopra Steria: Designing a Scalable Talent Acquisition System
Using dynamic personas and AI-powered content to compete for the world's most sought-after technical talent
From vacancies to targeted audiences.
Context
Sopra Steria was recruiting in highly competitive areas including AI, cybersecurity, and DevOps. With multiple specialties, seniority levels, and geographies in play, the ambition was to make hiring more precise, responsive, and scalable.
Reframe
Rather than optimising campaigns, we shifted the focus from advertising vacancies to engaging distinct technical audiences. In a highly competitive market for scarce technical talent, differentiation depends on speaking directly to the motivations, expectations, and career stage of each candidate group.
Solution
We built a dynamic candidate persona architecture combined with an AI-powered content engine. The system generates tailored recruitment messaging by specialty and seniority while maintaining brand consistency.
Innovation
A layered data model combines motivations, technical domain, and career stage to generate persona insight dynamically. This enables scalable variation without manual persona creation.
Impact
Recruitment shifted from campaign-by-campaign execution to a scalable, self-service system the team can operate independently. The platform increased speed, precision, and relevance while positioning Sopra Steria as a more competitive employer in high-demand technical markets, attracting better quality candidates.
AI Innovation Sprints
Rapid, structured programmes that embed AI capability into a specific commercial or operational function. From problem definition to working model — in weeks, not quarters.
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