What if your organisation could spot before a top performer handed in their resignation? Or tailor a career path for every employee using real-time business needs? That’s not a distant dream, it’s what today’s people analytics, powered by AI and integrated platforms, is enabling forward-looking companies to do.

Yet, while the technology has surged ahead, many organisations are still playing catch-up. Fragmented systems, siloed data, ethical concerns and a lack of strategy often hold them back from unlocking the true power of workforce data.

To explore how leaders can bridge this gap and build a future-ready talent strategy, we spoke with Sakaar Anand, India Head at BMC Software, someone who’s led  HR transformation  from back-office function to business enabler.

Moving beyond reporting: the analytics evolution

"Five or six years ago, HR analytics was really just a fancy term for reporting," Sakaar reflects. "We’d look at attrition, engagement, hiring metrics, but all of it was post-fact. There was no intelligence, no insight, no actionability."

That has now changed, thanks to the convergence of cloud computing, AI, and predictive technologies. Sakaar explains how the field has matured , from descriptive analytics (what happened), to predictive (what’s likely to happen), and now to prescriptive insights (what should we do about it). “We’ve gone from reporting numbers to building real-time, AI-informed strategies that shape business direction.”

At BMC Software, people analytics is embedded into core decision-making. Whether it’s succession planning, productivity optimisation, or learning interventions, data is now an active driver of outcomes, not just a passive report card. “The difference is integration,” he adds. “We’re no longer looking at HR metrics in isolation; we’re linking them across the employee lifecycle and correlating them directly to business KPIs.”

Fixing the silo problem

One of the biggest blockers to people's analytics success? Siloed systems.

“Most companies don't suffer from a lack of data; they suffer from too much of it, scattered across disjointed systems,” says Sakaar. Legacy tools, standalone platforms for recruitment, onboarding, payroll and performance have created fragmented ecosystems that prevent organisations from seeing the full picture.

So what’s the fix?

“The first step is not to rip everything out,” he clarifies. “It’s to unify.” Sakaar advocates for building a clean, integrated data platform, a ‘single source of truth’. Once the data is structured and centralised, advanced analytics and AI can then be layered on to identify trends, highlight early warnings, and guide strategic interventions.

This not only improves decisions, but it also drives action. “With agentic AI, we’re now looking at systems that don’t just inform managers,  they act on their behalf. They can trigger workflows, recommend learning paths, or even initiate engagement nudges based on real-time signals.”

From skills intelligence to proactive talent strategy

A major benefit of AI-powered people analytics lies in skills forecasting, mapping current capabilities against future needs. “We’re no longer waiting for skills to become obsolete,” Sakaar explains. “We can now anticipate gaps and invest in upskilling proactively.”

He cites intelligent platforms that recommend personalised learning journeys, suggest restructuring for better collaboration, and identify high-potential talent at risk of leaving. “It’s about staying ahead of trends, not trailing them. That’s what drives measurable business impact.”

Navigating ethics: innovation with responsibility

Of course, as organisations deepen their use of workforce data, concerns around privacy, bias, and fairness are inevitable and valid. But Sakaar makes one thing clear: fear shouldn’t lead to inaction.

“This is human data. Transparency is non-negotiable. People need to know what’s being captured, how it’s used, and for what purpose. And consent must be sought clearly.”

But beyond consent, he says organisations must build robust governance frameworks , ones that not only ensure legal compliance across jurisdictions but continuously audit AI algorithms to eliminate bias. “The models are only as ethical as the data and the intent behind them,” he adds.

The key, he believes, lies in human-AI collaboration. “AI doesn’t replace human judgment. It augments it. We need people who understand data, can question outcomes, and ensure that we’re solving problems with AI, not letting it make decisions in a black box.”

The Road Ahead: AI-Augmented Workforces

Looking to the future, Sakaar paints a compelling picture of AI-augmented workplaces.

Imagine employees having virtual career coaches powered by AI, bots that recommend learning modules, suggest growth paths, or highlight opportunities based on business needs and individual performance. “These agentic tools will act like a digital workforce,  supporting employees while freeing up managers to focus on innovation and leadership.”

But he’s clear about one thing: human intelligence will always matter. “AI will never replace cognitive intelligence. What it will do is elevate it, allowing us to solve more complex problems, collaborate better, and make more meaningful decisions.”

And as for the fear that AI will take away jobs?

“AI will create more jobs,  but they’ll be for people who understand how to work with data and technology. You don’t have to build AI. But you do need to know how to use and implement it.”