The HR AI Playbook Nobody's Talking About: Automate Before You AI

AI in HR: Where to Start When There's No Roadmap

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The pressure to adopt AI is everywhere. Boardrooms want it. Vendors promise it. LinkedIn won't stop talking about it. But for most HR teams, the reality is far messier than the hype suggests. There's no playbook, no clear destination, and most organizations haven't even mapped their existing workflows well enough to know where AI could help.

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On this episode of Pulse by HRBench, host Logan sits down with Kristin McDonald and Dani Woods, two HR technology leaders with deep experience in HRIS, Workday implementations, M&A integrations, and private equity environments, to break down what AI adoption actually looks like from the inside.

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Designing the Plane While Flying It

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The episode opens with a question most HR professionals are living right now: how do you lead AI initiatives when there isn't a clear path? Kristin set the tone immediately.

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"AI solves everything, right? That's the message. We need AI and what does that actually mean is very unclear," she said. "We're being asked to fly this plane or design the plane while flying it. And I think we don't even have a flight plan yet. We don't know who's the pilot. We don't even have a destination."

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That lack of foundational readiness is a thread that runs through the entire conversation. Both guests emphasized that the real work isn't choosing an AI tool. It's understanding your processes well enough to know where any tool, AI or otherwise, could make a difference.

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Dani shared her own experience experimenting with ChatGPT for Workday-specific tasks. The results were mixed. "I spent more time actually trying to understand what AI was telling me to do, translating it to Workday lingo, and then figuring out in the system, from when I could have just done it myself from years of experience."

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She described plugging an EIB template into ChatGPT and asking it to identify the required fields. "It was giving me the wrong information left and right. And I'm like, yeah, we're not there yet."

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The consensus: AI is a solid starting point for summarization, email drafting, policy writing, and general thought partnership. But for anything system-specific or deeply operational, the human in the loop isn't optional.

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Measuring AI Impact Beyond Headcount

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One of the sharpest parts of the conversation centered on measurement. When leadership asks "what's the ROI of AI," the default answer tends to land on headcount reduction. Both Kristin and Dani pushed back on that framing.

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"Ask yourself, is it causing more issues than the problems it's solving?" Dani said. She pointed out that companies often rush to implement AI-powered tools like chatbots without having the foundational content, such as policies, to feed into them. "It can take like two years to go into actual transformations depending on what maturity level they're at."

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Kristin brought it back to business impact. "Are we making employees' lives easier or managers' lives easier, allowing each other to be more strategic? And that's the impact, not like less clicks or one less transaction. It's where we're opening up time to be more strategic, which I think so many people want."

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Dani also shared a practical approach she's used across multiple companies: mapping time spent on manual tasks before making any technology decisions. "I will go nitty gritty. This is the amount of hours, this is the amount of people that it's hit. Just because one person complains too many times about one task does not mean you need to stick AI on top of it."

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Automate Before You AI

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Perhaps the most actionable insight from the episode was the distinction between automation and AI. Both guests made the case that many HR teams are jumping to AI when basic automation hasn't been implemented yet.

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"We don't need to layer on AI, but we just need to automate it first and then we can stick in AI," Dani explained. "I always started with the biggest time sucks in an entire day."

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She described a project at a previous company where her team tracked hours saved from automating manual tasks. "Come performance time, I could go to leadership and say this HRIS team just saved a thousand hours of productivity. That in itself is why we want to get into the world of AI, but it's not necessarily using AI. It was just automating things that were never thought of because no one knew what they were doing."

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That documentation effort had a secondary benefit in private equity environments with frequent transactions and turnover: it created a knowledge repository that de-risked the organization during transitions.

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Kristin reinforced this with a pointed question for HR leaders: "If you go into your business process in Workday for hire or for termination, do you actually know what that looks like end to end?" Her answer: most people don't. And that's exactly where the opportunity lives.

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The Fear Factor: Career Anxiety and AI

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The conversation took a candid turn when Dani recalled asking team members to document their workflows and being met with a direct question: "So are you going to take my job with technology?"

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Kristin connected this anxiety to a broader trust problem. "All the layoffs, no wonder people don't trust AI. Companies are laying off employees, and for cost cutting or whatever the messaging is. No wonder people don't trust AI."

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Both guests acknowledged the reality: jobs will change. But they framed it as an opportunity rather than a threat.

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Dani was direct: "Job security is never in the company that you're working with. It's going to be in what you can bring to an organization." She recommended HRIS professionals focus on payroll, integrations, and advanced compensation, the areas she sees as most durable. "Basic report writing, I think eventually is going to go away."

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Kristin's advice was to carve out dedicated time to experiment with AI tools. "I carve out AI time to play around, whether that's in ChatGPT or Co-Pilot or take a course. I only feel comfortable with where I'm at now because I've continued to play in it."

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Dani compared the process to exposure therapy. "If you have a fear of roller coasters, go stand by a roller coaster. Get in line. Act like you're going to do it so you start to normalize your nervous system to it. That's what you have to do with AI."

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The One Thing to Remember

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Kristin closed with a reminder that HR is no stranger to being thrown curveballs. "Give yourself grace. We're all in the same place. We're all starting down this journey." Her advice: start with business outcomes, not AI for its own sake. Understand where the organization is ready, and build from there.

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Dani left listeners with a weight-loss metaphor that landed. "You cannot lose 40 pounds in 40 days, but you might at the end of the year. Initiative after initiative will compound, and by the end of the year, your department might be completely different."

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The takeaway for HR leaders heading deeper into 2026: don't freeze, don't rush, and don't mistake AI for a silver bullet. Map your processes, automate what you can, and stay curious. The destination isn't fixed, but standing still isn't an option either.