Why HR Must Lead the AI Conversation w/Kristin McDonald

In this episode of Pulse by HRBench, we sit down with Kristin McDonald, a seasoned HR tech strategist who’s spent her career navigating the evolving landscape of HR systems, implementation roadmaps, and — most recently — the rise of AI.

‍

If your inbox is full of vendors claiming their solution is “AI-powered,” or your executive team is asking how HR can use more AI, this episode will help you separate signal from noise.

‍

Here’s what stood out from our conversation with Kristin — and why it matters for HR leaders, especially in fast-moving, private equity-backed environments.

‍

HR’s Role in the Age of AI: From Sidelined to Strategic

‍

Kristin’s perspective is clear: HR shouldn’t be reacting to AI — it should be leading it.

‍

“AI touches every strategy in your business. HR needs to have a seat at the table — not just to adopt AI, but to help define how it’s used, what skills we need, and how to prepare the workforce for it.”

‍

That leadership starts with basic AI literacy. Kristin points out that most HR leaders aren’t being given the support or education they need to confidently contribute to AI discussions — yet they’re expected to guide adoption, upskilling, and ethical use across the org.

‍

Her advice? Start small:

• Understand the difference between gen AI, agents, and LLMs
• Play with tools like ChatGPT and Microsoft Copilot
• Build a learning community internally — because everyone is figuring this out in real-time

‍

Building an AI Roadmap: It’s Not Just Plug-and-Play

‍

One of the most valuable parts of the episode is Kristin’s breakdown of how to actually build an AI roadmap for HR.

‍

She emphasizes that you don’t start with the tools — you start with your data and your processes.

‍

“Garbage in, garbage out still applies. If your data is poor or your processes aren’t documented, your AI implementation will fail — or worse, erode trust.”

‍

Here’s a simplified version of Kristin’s AI roadmap:

1. Audit your data – Is it clean, centralized, and structured? Can your knowledge agents find the right information?
2. Map your processes – What are people doing today? Where are the bottlenecks? What’s repetitive?
3. Identify opportunities – Where can automation help people be more strategic or save time?
4. Pilot AI use cases – Start with what’s already available in your existing tech (e.g. Copilot, Workday AI modules)
5. Define governance – Build internal policies around ethics, data privacy, and vendor selection

‍

Build vs. Buy: The AI Edition

‍

Kristin also dives into the build vs. buy debate — especially when it comes to embedding AI into your HR tech stack.

‍

There’s a temptation to buy flashy new AI tools. But she warns that without thoughtful integration and governance, you’re setting yourself up for fragmented employee experiences and risk exposure.

‍

“The worst thing you can do is tack AI onto a broken system or a disconnected stack. Integration matters — and so does internal readiness.”

‍

So what should HR leaders do instead?

• Talk to your existing vendors. Many already have AI features that can be activated now.
• Bring IT into the conversation early — especially for security and integrations.
• Be clear about ROI. Is this solving a real business problem? Or just adding another tool to manage?

‍

Tech Implementation: Why It Still Fails (Even Without AI)

‍

Long before AI took center stage, Kristin was deep in the weeds of HR tech implementations — especially large-scale projects like Workday.

‍

She shares hard-earned wisdom on what still goes wrong:

• No process documentation: HR teams often can’t articulate how things currently work — which makes configuration a guessing game.
• No post-launch support team: The system goes live, but no one owns it internally.
• No training during implementation: Teams aren’t upskilled alongside consultants, so when issues arise, they’re stuck waiting on answers.
• Lack of internal trust: When tech doesn’t work right out of the gate, employees blame the system — and HR loses credibility.

‍

Her recommendation? Treat implementation as a training program, not just a project. Build internal capability from day one.

‍

Where HR Tech Should “Live” and Why It Matters for AI

‍

One of the more nuanced debates covered is where HR tech should sit — under IT or within HR itself?

‍

Some companies are consolidating all tech under a single Chief Technology Officer. But Kristin argues that if HR is funding it, managing it, and relying on it for core processes, it should be supported by a dedicated HR tech team.

‍

“You need people who understand both the system and the HR language. That’s the only way you can translate business needs into tech strategy — and vice versa.”

‍

This point becomes even more important with AI:

• HR needs to help define how AI is used across orgs
• HR systems are increasingly connected to enterprise-wide agents
• AI governance often starts with employee experience, training, and compliance

‍

In short: HR can’t influence what it doesn’t own.

‍

Final Advice: Start Somewhere — and Start Now

‍

Kristin closes with a bit of encouragement that every HR leader needs to hear:

‍

“Just have grace — we’re all learning together. You’re not behind. Even experimenting puts you ahead.”

‍

She reminds us that doing nothing is the only real mistake. Whether it’s turning on Copilot, mapping a basic workflow, or simply asking better questions — every step builds literacy and credibility.

‍

Key Takeaways

‍

• HR should lead the AI conversation, not just follow vendor hype
• Building an AI roadmap starts with data quality and process clarity‍
• Integration, governance, and employee trust are more important than shiny features
• HR tech should be owned by HR — especially if it supports core talent strategies
• You don’t need to be an expert — just be willing to learn and experiment