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AI RecommendationsLeapsome

Provides HR teams, managers, and leaders with contextual AI-generated next steps to convert survey insights and people data into actionable plans.

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Product details

Leapsome AI Recommendations is an AI-driven guidance layer within a people platform that translates engagement surveys, performance data, and organizational context into concrete, prioritized next steps. It helps HR teams and managers move from insight to action by suggesting 1–3 targeted actions after engagements or pulse surveys, offering goal and OKR suggestions grounded in existing reviews and priorities, and drafting balanced feedback for one-on-ones or reviews. Recommendations are surfaced as editable drafts that can be refined, assigned to owners with deadlines, and tracked to completion, reducing manual planning time and decision paralysis. The system supports multiple languages, configurable thresholds, and tenant-level adaptation so suggestions improve over time based on outcomes and user feedback. By combining action planning, goal-setting assistance, and feedback phrasing, the tool aims to accelerate HR processes, improve manager effectiveness, and increase the likelihood that insights lead to measurable improvements in employee development, engagement, and retention.

Features & Benefits

  • Action Planning: Automatically translates survey findings into 1–3 suggested next steps to jumpstart remediation and focus efforts.
  • Goal & OKR Suggestions: Analyzes performance reviews, engagement results, and company priorities to propose measurable, context-aligned objectives.
  • Feedback Assistant: Provides tailored phrasing for constructive feedback, balancing strengths and concrete improvement areas to make feedback actionable and fair.
  • Editable Recommendations & Assignment: Treats suggestions as drafts that can be edited, approved, assigned to owners, given deadlines, and tracked through completion.
  • Global & Adaptive Controls: Supports multiple languages, configurable thresholds by team or module, and evolves based on tenant-specific feedback and outcomes.