AI in HR: 4 Lessons Shared by Global HR Leaders at Outsmart London 2026
The HR teams pulling ahead with AI aren't chasing more dashboards. They're feeding AI the right context, putting it where leaders already work, and spending the time saved on strategy.
Workforce Intelligence & People Analytics
Explore themes such as analytics strategy, data governance, HR data integration, workforce insights, and measuring business impact.
Back to blog
13 Employee Retention Strategies for Keeping Your Best Talent
What Is Workforce Context? The Missing Layer Between AI and Your People Data
Definitions, Ownership, Trust: The Non-Negotiables of AI-Ready Workforce Data
Latest on Workforce Intelligence & People Analytics
The Workforce Productivity Survey: What 50 Executives Actually Think
Visier Research surveyed 50 business leaders outside HR to uncover the workforce productivity statistics that matter most: how executives define productivity, and which metrics they're missing. Biggest takeaway? 65% say inefficient processes—not bad data—are the biggest obstacle.
Why You Absolutely Shouldn’t Use an LLM for Workforce Data
HR data is unlike almost any other data your organization holds—volatile, legally sensitive, and deeply contextual. Most AI deployments treat it like any other data source and pay the price. Here's what the architecture actually needs: a context layer, durable guardrails, and a semantic foundation that travels with the data wherever it goes.
The Employee Perspective on AI's Impact in Software Development: What's Really Changing
The headlines say AI is eliminating software jobs. Visier's analysis of 3.6 million employee records—paired with employee interviews— tells a different story: roles are despecializing and reorganizing, and the real costs (mentorship, team cohesion, skill atrophy) don't show up in headcount data at all.
What Is an HR Dashboard and How Can I Use It?
An HR dashboard is a visual reporting tool that pulls workforce data into one real-time view that makes people metrics easy to read, share, and act on.
3 Reasons Why AI in HR Tech Fails
HR tech leaders are under pressure to ship AI, not just evaluate it. But most projects stall before they reach production. The model isn't wrong, but the workforce data underneath it isn't ready. Here are the three structural problems that kill momentum: data you can't trust, complexity that slows your launch, and costs that scale faster than anyone planned for.
9 Criteria to Evaluate People Analytics and Workforce Intelligence Solutions
A practical framework for HR tech leaders evaluating people analytics vendors—covering the criteria most RFPs overlook, from data model maturity to total cost of ownership.
