Talent Acquisition

Description

Talent acquisition is part of the recruitment strategy and is one of the core functions of an HR department. It's the process of attracting and hiring skilled employees to fulfill a company's business needs and includes the development, implementation and evaluation of systems for sourcing, recruiting, hiring and orienting. As part of talent acquisition a business needs to create a strong employer brand and proactively nurture applicant pipelines to meet the needs of the company.

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Stage 3 - Talent
Oct 21, 2026
10:00 AM10:30 AM
Talent AcquisitionArtificial Intelligence

The Talent Power Shift

Cecilia CrossleyHow HR Leaders Change the World podcastFounder, Uplifting People | HostAndy DoyleKantarChief People and Agents OfficerKatarina BergOnChief Human Resources Officer
Description
  • Rebuilding Trust, Judgment and Operating Models In AI-Driven Hiring
  • Distinguishing weak tools from poor data and broken operating models
  • How AI is shifting power and accountability in talent decisions
  • Rebuilding trust between HR, recruiters, and hiring managers
  • Balancing automation speed with human judgment
Stage 3 - Talent
Oct 21, 2026
2:15 PM2:45 PM
Talent AcquisitionArtificial Intelligence

Using AI in Talent Acquisition Across The Enterprise, Mis-trust and Responsible AI in Practice

Dominik A. HahnAllianz SEGlobal Head of Group Talent Acquisition
Description

Drawing on real experience, it explores where adoption stalled, where trust weakened, what failed, and which Responsible AI measures proved essential to regain confidence and move forward.

  • What worked and what failed when scaling AI across talent acquisition at the enterprise level
  • Why adoption often breaks down in practice across recruiters, hiring managers and business leaders
  • Where mistrust in AI comes from and how to distinguish cultural resistance from valid operational concern
  • How to introduce Responsible AI measures that strengthen fairness, transparency, accountability and confidence in hiring decisions
  • Lessons learned in balancing automation, speed and efficiency with human judgment and oversight
  • What TA leaders should do differently to improve adoption, rebuild trust and scale AI more responsibly
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