Manager Agents for HR – Faster Reviews, Better Coaching

A pre-IPO tech company tasked People Analytics with People Tech and HR's AI roadmap. Yuyan Sun shows how manager agents draft and validate reviews, answer HR queries and prompt calibrations within policy-as-code guard-rails and audit trails. She outlines the architecture, AI-Ops operating model and CIO partnership, plus an AI-literacy campaign that turned sceptics into users. Expect outcomes, limits and a reusable pattern you can adapt.

• Definition and authority model: what the agent does vs what remains human, with explainability.
• Three live use-cases: review copilot, HR ops chatbot and calibration nudges, with guard-rails and key metrics.
• Architecture: policy-as-code, competency models, HRIS data, access controls, override paths and audit logs.
• AI-Ops operating model: roles, backlog, evaluation loop, CIO partnership and release cadence.
• Adoption playbook: AI literacy as marketing, champion network, clear messaging and adoption telemetry.

• Design manager agents with explicit authority boundaries and explainability using policy-as-code.
• Establish an AI-Ops function and evaluation loop with CIO and HR leadership to ship safely.
• Run an AI-literacy campaign that secures manager and HR adoption.
• Measure impact using time saved, review-quality alignment, usage curves and override/escalation rates.
• Update career architecture to reward technical leads while raising expectations of people managers.

Yuyan Sun

Head of People Analytics · Motive

Managers face expanding administrative load while HR pursues speed, consistency and compliance under rising AI expectations. Automating repeatable tasks without eroding trust demands clear authority boundaries, privacy controls and auditability. Getting this right unlocks better coaching time, safer decisions and faster cycles across reviews, policy queries and calibration.