Talent Intelligence in Action: What HR Leaders Are Seeing Now

AI adoption is uneven

Across recent conversations with HR and talent leaders, one thing is clear: Everyone has AI but not everyone is ready. AI access has scaled quicker than governance-organizations are investing in AI and want to move quickly, yet most adoption is inconsistent and still driven by immediate needs rather than long-term strategy.

Technical teams are often leading the way, embedding AI into daily workflows, while HR, recruiting, and operational functions are still exploring where it fits. In many cases, usage is limited to low-risk tasks such as drafting content or supporting administrative work.

This uneven adoption highlights that AI is not arriving as a single transformation initiative; its usage varies across the workforce in pockets of comfort and experimentation. The challenge for leaders is how to expand adoption thoughtfully, without forcing uniformity across very different user groups.

Fear and trust are shaping progress

Alongside curiosity, there is a clear undercurrent of concern. Employees are questioning how AI will impact their roles and whether increased use could reduce their long-term relevance. In a recent SHL survey of more than 1,000 working US adults, 26% said they do not trust their employer to use AI responsibly, and nearly four in ten worried about job loss, privacy, and data security.

This hesitation is significant but not permanent. Leaders consistently shared that confidence grows through exposure and when individuals begin using AI in everyday contexts, their perception shifts from threat to opportunity.

It comes down to building trust. AI should be less about top-down mandates and more about creating safe, practical opportunities for people to learn and engage with it.

Governance Is catching up

While experimentation is accelerating, governance frameworks are still evolving. Across industries, AI use in hiring and talent decisions is being carefully scrutinized.

Leaders described approval processes as necessary but often slow, creating tension between innovation and compliance. Yet there is broad agreement that when decisions affect people’s careers, the bar must remain high.

The real challenge is balance. Moving quickly enough to stay competitive while ensuring AI applications are ethical, transparent, and defensible. AI is not an IT or tech issue alone, leading organizations have cross-functional representation to review AI use-cases, analyze risks and identify the value and challenges usage can bring.

Data remains the bottleneck

A quieter but persistent theme is the state of talent data. Organizations are prioritizing visibility into current skills, future gaps, and internal mobility pathways, but many organizations lack the structured, consistent data needed to fully leverage AI. Efforts are underway to clean and align skills taxonomies, standardize job architectures, and improve data capture.

This is where talent intelligence becomes practical. By connecting internal workforce data with external market insights, organizations can move from fragmented information to a more cohesive view of talent that supports better workforce planning, hiring, and development decisions.

What talent intelligence looks like in practice

I have worked with organizations across industries where talent intelligence has started to make an impact. One organization in a highly regulated industry has transformed its recruiter playbook into a customized GPT, improving consistency and efficiency while still working to demonstrate ROI. Another organization is using AI to forecast talent supply and demand, identifying hiring challenges before they materialize. Taking another step forward, some businesses have already set up a dedicated talent intelligence function that integrates external labor market trends with internal data to inform strategic decisions.

These examples illustrate a shift from isolated use cases to more connected, data-driven approaches to talent. The goal is not simply more AI, but a more connected talent strategy that moves organizations from access into AI readiness.

From AI experimentation to execution

Leaders have now entered a new phase of actively exploring how AI can lead to faster, smarter, and more strategic decision-making. This includes identifying scalable use cases, validating impact, and integrating AI into existing workflows without removing critical human judgment.

However, progress towards realizing the ROI on investments in AI depends on addressing key factors such as adoption, trust, governance, and data. Talent intelligence brings these elements together. It provides a framework for understanding workforce dynamics in real time and making informed decisions with confidence.

While others rely on guesswork or inferred data, SHL delivers actionable Talent Intelligence based on objective data you can trust.

Watch our recent event replay, Talent Intelligence in an AI-driven World to learn more about how AI is reshaping the future of talent, leadership and workforce transformation.