Editorial
HR cannot afford to wait and see on AI. If we don’t join the conversation now, we risk solving the wrong problems faster.
We’ve been here before. New tools are scoped. Automation plans take shape. Use cases are drafted. And HR is brought in after the design is nearly complete. We are asked to manage rollout, lead training or provide user feedback.
This isn’t necessarily due to a lack of interest in HR’s perspective. But historically, HR has waited to be included, either because we hesitate, or we’re overwhelmed or because we thought the people in the room already understood what was needed.
That assumption doesn’t hold. It’s not about bad intent. It’s about incomplete insight.
AI is not an independent actor. It reflects the priorities, values and perspectives of the people who train, configure and deploy it. HR leaders who want to use artificial intelligence must participate early in the process to ensure the technology addresses real organizational needs.
Without HR, AI Development Teams Solve the Surface and Miss the System
The AI development teams asked to solve pressing business problems are operating with incomplete insight. They iterate and build models and tools designed to automate, predict or streamline based on summaries of employee challenges.
But those summaries often stop at the symptom:
- “Reduce time-to-productivity during onboarding.”
- “Identify employees at risk of burnout.”
- “Screen resumes more efficiently and fairly.”
These requests are valid, but they leave out the organizational context behind the issue.
AI engineers can’t fix what they don’t fully understand. And many of the problems they are designing AI systems to address are rooted in the very systems HR understands best. The systems that seem like they have obvious answers that should have been solved long ago don't because only we hold the context to know why those problems are so sticky.
AI for Burnout
Take burnout, for example. Several platforms now use AI to monitor indicators like email volume, calendar density and after-hours activity to flag potential risk. Microsoft Viva, for instance, provides productivity insights and nudges employees to schedule focus time or reduce evening communication. These recommendations aren’t inherently wrong — but they’re incomplete.
Because AI systems track behavior, not context.
AI can detect burnout signals but requires HR expertise to interpret them properly. They might flag an employee for late-night work patterns, but miss that this same employee intentionally flexes their schedule to start mornings with exercise — a habit that actually improves their well-being. Without insight into personal rhythms, team norms or broader organizational expectations, the tools reduce burnout to a calendar metric.
AI in Hiring
Or consider AI in hiring. Many systems claim to identify “highly skilled” candidates faster, often by analyzing resumes, job titles or online presence. But what exactly counts as “highly skilled”? That part is usually left vague.
Defining the skills a role requires is the easy part. The hard part is measuring them — fairly, ethically and at scale. That’s why many hiring processes still rely on proxies: where someone worked, where they went to school, or how confidently they present themselves on paper.
These stand-ins can perpetuate bias and overlook capable candidates who don’t follow conventional paths.
Without HR’s input, AI systems will keep optimizing for what’s measurable, not what matters.
The result? We don’t get to utilize the capabilities of AI to fix our long-standing problems, we just add automation to what is already there and the problem simply moves faster.
HR Must Step Up to the Artificial Intelligence Challenge
Sustainable change requires more than identifying patterns. It requires understanding why they’re happening in the first place. And that’s where HR insight is irreplaceable.
HR doesn’t just know where the pain points are — we know why they’ve been so hard to solve.
We understand the processes that look fine on paper but fall apart in practice. We see where teams are quietly building workarounds to keep things moving. We can spot the difference between a policy that meets legal standards and one that actually works for people.
That context is essential in the early design phase, because otherwise AI tools automate inefficiencies rather than address them. The system becomes faster, but not smarter.
When HR is involved in AI design from the beginning, we help frame the problem more accurately. We challenge assumptions baked into the initial prompt. We bring insight into human behavior, team dynamics, operational friction and cultural nuance that data alone can’t surface.
That shift — from efficiency for its own sake to thoughtful, context-aware design — is where AI begins to truly enable better work.
Some Constraints Are Strategic — and Intentional
While IT may view HR’s involvement as an impediment, not all friction is a design flaw. Some friction reflects deliberate choices to protect people and preserve trust.
HR brings an understanding of legal boundaries, ethical norms and cultural dynamics that don’t always surface in technical planning.
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For example, AI workplace tools designed to track productivity or sentiment can quickly become invasive if they fail to account for privacy expectations or historical misuse of monitoring practices. AI systems that recommend candidates based on behavioral patterns may unintentionally reinforce bias if fairness isn’t intentionally built into their design.
HR’s role is to ensure artificial intelligence innovation respects human boundaries. We aren’t there to slow progress, but to guide it toward outcomes that people can trust and adopt.
HR Has Seen What Happens When We're Too Late
Most of us have worked with HR software that looked good in demos but didn’t work in practice. These tools were technically impressive but fell short. They failed to match how managers actually give feedback, how employees move through roles, or how learning really happens on the job.
We’ve lived through:
- Systems that automate broken processes instead of fixing them.
- Portals that make simple tasks harder.
- Dashboards that measure what’s easy to track, not what matters.
When HR is left out of the design process, we’re left to clean up the mismatch between intent and experience. HR technology implementations fail when they don't align with actual workplace behaviors.
We can’t let that happen again with AI. This time, we need to help design the system, not just test it.
From Frameworks to Action: Rethinking HR’s Role in AI Implementation
HR brings deep expertise in models of motivation, behavior and change. But frameworks are only as useful as the questions we pair them with.
Too often, we default to questions that reinforce existing structures:
- How do we stay compliant?
- How do we make this more efficient?
Those questions have their place. But when it comes to designing AI systems that actually improve work, we need to ask different questions. Questions that surface complexity, center human experience and challenge old assumptions.
Try these instead:
- Who is this system truly serving … and who might it unintentionally leave behind?
- What are people trying to accomplish that this process gets in the way of?
- What human signals are we ignoring because they’re hard to measure?
- Where have we accepted workarounds as permanent solutions?
- If we were starting from scratch, what would we build?
These kinds of questions move HR from enforcer to enabler.
They help us use our frameworks not as rules, but as lenses to see more clearly.
Discomfort Isn’t a Red Flag. It’s a Starting Point.
Many HR teams feel behind on AI. The pace of development is fast, and the language around it can feel foreign. It would be easy to just step back and wait to see what the engineers deliver.
But waiting until we’re comfortable is not an option. The earlier we engage, the more influence we have.
We don’t need to be technical experts. We need to be curious contributors.
Start small: try out AI tools. Read the prompts. Challenge their logic. Ask questions about what they’re optimizing for and what assumptions they’re reinforcing.
Discomfort is not a reason to sit out. It’s a signal to begin.
This Is the Moment to Step In
The question is not what AI can do for HR: it’s what kind of workplace we are teaching it to support.
We have the insight, the context and the tools to shape AI thoughtfully.
What we need is the willingness to show up, to be brave. To be in the room early, consistently and with the courage to ask better questions.
Because the future of work is not something we should just react to.
It’s something we, as HR professionals, should help build.
Editor's Note: Read more about the relationship between HR and AI:
- How HR Leaders Bridge Human Potential and AI Innovation — Four ways HR leaders can rise up to the challenge and integrate technology and the employee experience.
- Rethink Your HR Strategy to Include AI Agents — As AI agents make their way into our workforce, HR is called to adapt its workforce strategy.
- AI Powered Career Development Brings Great Potential. It Also Brings Ethical Risks — AI's potential to democratize and scale learning and development is evident. What may not be as evident are these ethical concerns it raises.
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