AI in HR: Rethinking the Analytics Mandate for HR Tech Leaders
AI in HR mandates push tech leaders to deliver measurable workforce results. Discover trends on human-augmented AI, GenAI data democratization, and flexible stacks for people intelligence.
Artificial intelligence has already pushed executives into investing heavily in AI, and it remains the number one priority for CHROs in the following years too.
As AI investment scales, CEOs are now asking every function, including HR, to prove where AI is driving productivity, cost, and experience gains, not just technology experimentation.
Leaders who own and support HR technology are being asked to modernize tech stacks, prepare workforce data for AI, and support new analytics and automation capabilities. All this while having to protect sensitive employee data and maintain trust within the company.
After reading my colleague's Trends 2026 report , I began reflecting on how some of the core trends she revealed affect the HR tech leaders I connect with every day. Turns out, the CHRO and HRIT are more aligned than ever when it comes to trends to focus on for 2026 (and beyond). Here's a look at how AI, analytics, and tools are redefining what HR technology leadership looks like today and in the near future.
Trend 1: AI will be the first mate, not the captain
While most organizations are expecting to rely on AI to deliver value in all aspects of their business, its main priority remains clear: enhancing human decision-making rather than replacing it. This places AI as a “first mate” that can speed up insight generation, make accurate recommendations, and automate repetitive work.
In this picture, it's the humans behind the tools who remain accountable for judgment, ethics, and organizational context.
Organizations will get stronger results only when AI and humans operate in partnership. AI excels at synthesizing data, identifying patterns, and generating recommendations, while humans remain critical for interpretation, building trust, and making the final decisions.
Employees, regulators, and executives also expect more transparency into how AI-driven decisions are made. This speeds up demand for auditable AI that enables human oversight. After all, AI agents only create value when they operate on governed, contextualized people data and when they support end-to-end human workflows.
How to prepare your HR Tech roadmap:
Prioritize AI projects that augment, not replace, humans. While AI agents should be part of diverse workflows like hiring, workforce planning, and performance management, human judgment should remain central to decision-making. Solutions like Visier’s people analytics AI agent, Vee, support this, bringing workforce insights and recommendations directly into decision workflows while letting you maintain human oversight.
Incorporate explainable AI that allows leaders to review, override, and audit AI recommendations. This supports transparency and auditability, which is essential for adoption, regulatory compliance, and employee trust.
Assess whether vendors design AI to augment human decision-making or attempt to replace it. HR tech leaders should be in charge of setting policies, accountability standards, and oversight for using AI across the organization.
Trend 2: GenAI will extend the reach of people analytics
Data generation volumes grew 792% between 2019 and 2024, but most still aren't using it effectively for strategic people decisions. Only 23% of executive teams incorporate people data into their planning.
HR technology leaders can use generative AI to democratize workforce data by enabling natural-language querying directly into HR systems and everyday workplace tools. This lets business leaders, managers, and HR partners access people analytics without requiring BI expertise or technical data skills.
Operationalizing GenAI within the HR tech stack enables organizations to scale data-driven decision-making across the enterprise. By delivering insights directly in the flow of work, such as validating workforce assumptions during planning or supporting real-time scenario exploration, GenAI accelerates speed to insights, improves business agility, and helps organizations respond faster to change.
On the other end, GenAI capabilities help users discover questions they didn't know to ask in the first place. For example, it can surface hidden questions like “Why is employee attrition rising in one region?”, “Which teams are at risk of burnout?”, or “What early signals suggest a project may fail?” This helps users speed up decision-making, get insights faster, and respond to challenges before they escalate.
Still, expanding access to workforce data through generative AI also introduces new risks if not implemented responsibly.
No strong data governance, security controls, and validation mechanisms? Without them, organizations may expose sensitive employee information, amplify biased or incomplete data, or generate inaccurate insights that erode trust in people analytics. As GenAI lowers the barrier to accessing workforce data, HR technology leaders must ensure safeguards scale at the same pace as accessibility.
How to prepare your HR Tech roadmap:
Establish data foundations first. Audit and unify HR data to get a complete, end-to-end view of your workforce, rather than relying on fragmented or siloed sources. This richer, more connected dataset provides GenAI with greater context, which ultimately leads to more accurate, relevant, and trustworthy insights.
Secure democratization with controls. Implement role-based access and granular permissions to ensure insights reach the right people without exposing sensitive data.
Build governance for scale. Define clear ownership, ethical guardrails, data usage standards, and measurable success criteria tied to business impact. Ensure trust and safety while allowing teams to experiment and expand GenAI use cases.
Trend 3: The HR solution stack will be under pressure
To accelerate AI adoption safely, organizations first need to audit their HR tech stack:
What’s creating data silos?
What’s causing integration headaches?
Where are the governance gaps?
Where are teams spending valuable resources on maintenance and upkeep instead of enabling or accelerating AI use?
When you identify those bottlenecks and risks, you can better understand how to prioritize your HR tech roadmap.
Choose platforms that safely speed up AI enablement by unifying your people data into a secure, AI-ready insights layer.
More and more companies are turning to workforce intelligence platforms like Visier Workforce AI to go from siloed systems to unified, trusted intelligence that makes it easy to connect workforce decisions to real business value.
How to prepare your HR Tech roadmap:
HR tech leaders should be assessing their vendors/tools through the lens of AI readiness. Evaluate tools on speed, safety, and ease of AI enablement, prioritizing those supporting business AI goals without adding risk.
Choose tools that support the points made above. AI analytics platforms should come with explainable, auditable recommendations, human-in-the-loop controls, and support augmentation over replacement.
Bring all your data to one place for AI to work best. Consider which tools are creating data silos vs. which tools help enhance or prepare your data foundation or architecture for AI.
Look into how HR tech tools integrate with broader data and AI initiatives. Opt for HR technology vendors that integrate with and enhance your enterprise architecture, rather than duplicating tools or creating friction.
AI pressures are real—and your moment is now
HR technology leaders now sit at the center of whether AI in HR actually delivers value or remains an expensive experiment. Integrating AI capabilities into the HR tech stack right is no longer optional: it’s the only way to turn fragmented people data into trusted, scalable workforce intelligence that leaders can act on.
HR technology leaders need to be informed, vocal, and proactive. They need to challenge legacy architectures, advocate for flexible and interoperable platforms that accelerate AI safely, and clearly articulate how data, models, and governance work together to produce measurable business outcomes.
When HR leads that conversation, AI stops being a black box tool and becomes a trusted partner, continuously surfacing people insights without creating new silos, security risks, or runaway costs.
Ready to learn how to accelerate your HR tech strategy and advance AI securely? Grab our free whitepaper to learn how to embrace the future of AI and analytics.
