AI is rewriting the rules of people analytics – and HR leaders must adapt fast

For years, HR teams have been climbing a maturity curve in people analytics –from basic headcount reports to sophisticated predictive models. But according to Justin Angsuwat, chief people officer at Culture Amp, that entire progression now represents just the starting point of a far more transformative shift.

"When you zoom out, you're like, wow, that people analytics view itself is actually the start of the maturity curve of an AI version of that," Angsuwat explained. The implication is stark: the analytics capabilities HR teams spent years building are being fundamentally reimagined by artificial intelligence.

Traditional HR has been "very workflow based," Angsuwat noted, pointing to performance reviews as an example where processes move sequentially through self-reflection, peer review, manager review, and feedback delivery.

While AI initially "starts to accelerate that workflow," the more profound question emerging is: "do we need a workflow at all?" This same logic applies to analytics –do HR teams still need to spend weeks designing studies and requesting data cuts, or can AI surface insights in real time?

The practical implications of this shift are already visible in how Culture Amp approaches employee engagement. The company has "moved now from you know your engagement score is 72 to 'This specific issue is going to cost you $3 million if you don't address it,'" fundamentally changing conversations with boards and executive teams.

Organisations can now "use AI to go through all of your survey data and understand how do you move this organisation" from underperforming states to peak performance.

In one example, Angsuwat worked with a function where employees were engaged but didn't believe they could win as a team. AI analysis revealed "the single biggest driver of that is they didn't believe that people were going to act on poor performance" – providing a clear, actionable intervention point.

"All of a sudden this organisation is like, wow, I've got this thing that I can do now, address that, and I know it can drive performance for the company," Angsuwat said.

Given this technology-driven transformation, must HR leaders become data scientists? Not necessarily, according to Angsuwat, who brings a computer science background to his people leadership role.

While previously "you need to be quite deep in data and analytics to do people analytics well," the AI era changes the equation. Now "you can just tell AI where it is you want to go and it will work out how to get there."

The new competency requirement is "being able to know what AI is capable of and being able to ask the right questions and how the technology functions."

But this isn't a passive learning process. "You have to be curious. You have to find the latest examples. You have to read papers," Angsuwat emphasized, noting there isn't a linear path to AI fluency.

A critical caution for organisations rushing to implement AI analytics tools: technology alone won't solve fundamental people problems.

"AI is only as good as the culture it lands in," Angsuwat warned. "If your people don't trust leadership, no amount of AI tooling is going to really fix that. But if the trust is there, AI becomes a genuine multiplier."

This is why "so many HR leaders are the ones driving AI adoption across the organisation" – they understand the cultural prerequisites for successful technology deployment.

Predictive analytics in action

Culture Amp's own journey illustrates the progression from descriptive to predictive analytics. Initially, the company "worked on the descriptive first. So one we had to clean up the data," Angsuwat said, then moved to understanding why employees were leaving.

"Where it started to change the game was we get into predictive and prescriptive people analytics." One critical insight emerged: "high performing women in engineering were at one of the highest interest and risk levels for our organisation."

Armed with this foresight, Angsuwat could "share that with my PX organisation and we can really serve resources in this one critical area and know how to address this very specific employee need."

Perhaps the most significant transformation enabled by AI is putting analytical power directly in the hands of line managers. At Culture Amp, "every leader in our organisation understands what drives engagement and performance in their part of the organisation," Angsuwat added.

Leaders "don't have to sift through the raw data. They don't need to look at another cut. They don't need us to pull a different version of the data." Instead, they "can have a conversation with our AI coach and learn what drives their organisation and then they can go take action on that."

This approach means "these AI coaches that we have can go sift through all of your organisational data to find the right insight that a people analytics team might have missed."

No more waiting

For HR leaders still deliberating whether to invest in data and analytics capabilities, Angsuwat's message is unambiguous: "It's here whether you're ready or not," he says of the AI transformation sweeping through HR.

The competitive advantage will belong to organisations that move quickly to establish solid data foundations, cultivate AI literacy among their HR teams, and reimagine how people insights can drive business performance. The analytics maturity curve hasn't disappeared – it's simply become the foundation for an entirely new level of strategic capability.