Predictive analytics in retention analytics is not new, however the key to adoption of this solution in decision making needs a productized solution that is rolled out to the people partners and line managers where they can view multiple leading indicators of attrition on this tool and take decisions to retain critical talent within their teams. In this session, you will learn:

• Forecasting the exit numbers
• Identifying the key hotspots of attrition
• Determining the key factors influencing attrition
• Linking retention variables with Engagement data
• Conducting bi-variate analysis to understand the impact of a particular variable on probability of attrition

This panel discussion will explore the transformative potential of AI in enhancing analytics, particularly in HR, by improving efficiency, accessibility, and driving more value. However, it will also address the risks associated with AI implementation, such as bias, data security, and transparency. Panelists will share insights on how organizations can strike a balance between leveraging AI’s capabilities and mitigating potential challenges, ensuring sustainable, ethical, and impactful outcomes. Discussion questions:

• How can AI improve the efficiency and accessibility of HR analytics across the organization?
• What are the key risks associated with using AI in HR analytics, and how can organizations mitigate them?
• How do we effectively measure the value AI brings to our analytics processes and outcomes?
• In what ways can AI create more value in HR analytics without compromising data security or ethics?
• How can organizations ensure that AI tools remain accessible, transparent, and equitable for all users within the company?