People data & People Analytics Leader At IBM | AI | Enterprise Data Platforms | Data Transformation
❓Should We Use GenAI to serve People Data & Insights? Yes, but... ⁉️ The question remains open, and while we’re seeing early successes, scaling GenAI in people analytics introduces unique challenges. Kas Attanapola, MBA and Aradhana P.’s article below offers a great look into this "new era of BI." Personally, I strongly believe GenAI offers great opportunity as channel for serving People data insights for 2 main reasons: Data Democratization Beyond HR: For effective scaling, access to people data must go beyond HR. For example, 40% of our People Data Report users are outside HR (excluding managers and employees accessing data through other channels). GenAI’s intuitive interface makes this even more feasible! Moving from Insights to Action: Insights alone aren’t enough—action must be enabled. Integrating BI and automation combines diagnosis and action into one seamless experience. At IBM, we’re embedding more and more BI deeper into AskHR, HR flagship AI Digital Assistant used by all IBMers Today and built on IBM watsonx Orchestrate. Putting authorization aside (I recently wrote an article on this in my People Data Platform newsletter if you're interested), there are a few key challenges to keep in mind: Embedding HR and Corporate Knowledge: Delivering relevant, actionable insights requires a deep understanding of HR and company strategy. This is not new to Gen AI. For instance, while a predictive model might flag attrition risks, it doesn’t automatically mean a salary adjustment is possible. However, when insights are democratized via GenAI, addressing these nuances becomes more complex. Managing Subtle Hallucinations: A tight governance is essential. A simple question like “What is IBM’s HR headcount?” can yield different answers depending if and how part-time staff, students, or employees on leave are included in the definition of Headcount. IF not controlled, it would be a massive step-back on our ability to serve consistent metrics. Breaking Domain Barriers: As people data reaches users outside HR, it’s essential to eliminate data silos, facilitating integration between HR-owned and business-unit-owned data. This approach will also empowers HR with measurable financial metrics to guide decisions. However, it is definitely more complex one might hope. At IBM, we’re fortunate to address these (and others) challenges through a close partnership between HR, our Chief Analytics Office, and our Software Group teams. I look forward to sharing more insights from our journey soon. Thanks to Jon Lester John M. Jenkins Anjit Karn Timothy Humphrey Usa Kerdnunvong Kelsey Gonzalez, PhD Bruno Aziza Kas Attanapola, MBA Lena Woolf Omair Raza (among many others) for your help and guidance on the success of this initiative! #genAi #peopleAnalytics #enterpriseData
I recently shared insights on why many BI tools struggle with adoption—often due to complexity and lack of personalization. In today’s fast-paced environment, people need BI tools that are intuitive, understands data/business context, and accessible to everyone, enabling faster, smarter decisions. Take a look at the full blog here to learn more about the problems we are solving here at IBM Data & AI: https://lnkd.in/gNtXcpXb
Program Director, Product Management Leader @ IBM Data & AI | DeGroote MBA
1moLove this Pietro Mazzoleni ! Love collaborating with your team and the work you are doing to make IBM more data driven!