Questions for the panel
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- Data Integrity vs. AI Innovation:
- With the growing adoption of generative AI, how do you maintain the integrity of your data without compromising innovation?
- Have you encountered challenges where AI-driven analytics revealed gaps in your data quality? How did you address them?
- Security Frameworks for Emerging Technologies:
- As your organisation scales its use of AI in people analytics, what new security risks have emerged, and how are you mitigating them?
- How do you adapt your existing data security frameworks to accommodate AI and other advanced analytics tools?
- Balancing Transparency and Privacy:
- How do you balance the need for transparency in AI-driven analytics with the obligation to protect employee privacy?
- Can you share an instance where privacy concerns impacted the rollout of a people analytics initiative, and how you resolved it?
- Proactive vs. Reactive Data Governance:
- In the context of HR data, how do you ensure your governance strategy remains proactive, particularly when new technologies like AI are introduced?
- How often do you audit your HR tech stack for compliance with evolving data governance standards, and what’s your process for continuous improvement?
- AI Bias and Data Quality:
- Generative AI often relies on historical data that may carry biases. How do you ensure the quality and fairness of your data to avoid perpetuating these biases in HR decision-making?
- What methods have you used to audit AI-driven insights for potential bias, and how do you correct these issues?
- Regulatory Pressure on AI-Driven HR Tech:
- How do you foresee data privacy regulations evolving as AI becomes more integrated into HR tech stacks? Are there particular future trends or legal requirements that you're preparing for?
- What strategies have been most effective in ensuring your HR systems remain compliant amid changing regulatory landscapes?
- Collaboration with IT and Legal Teams:
- How do you collaborate with IT and legal teams to ensure both technical and legal compliance when handling sensitive HR data?
- Can you share any cross-functional initiatives that have successfully strengthened your organisation's data security and governance?
- Data Minimisation in HR Analytics:
- In an era of AI, data minimisation is key to balancing insight generation with privacy concerns. How do you determine what data is necessary for analytics, and what is excessive?
- Has data minimisation led to more strategic use of people data in your organisation? How do you make these decisions?