Newsletter

EN | FR

The HR Leader's Edge — Edition #4

AI and HR: Why I'm Still a Believer (and What You Need to Watch Out For)

By Heidi Klotz, Professional Goal-Centric Coach | Fractional CHRO

Published June 3, 2026

II have a confession. Back in 2020, while most people were baking sourdough and reorganizing their closets during the pandemic, I went back to school.

I enrolled in a master's program in analytics at Smith School of Business at Queen's University. I learned to code. I started running algorithms. And somewhere in the middle of all of it, I became genuinely excited about what AI could mean for HR.

Fast forward to today, and I've spoken at conferences about it, written about it for Smith Business Insight (including a deep dive into how natural language processing is transforming HR analytics), and been featured on the Smith Business Insight podcast talking about AI-powered HR. I've watched the conversation explode. Generative AI, ChatGPT, Claude, Copilot, whatever you're calling it this month, it is everywhere. And HR professionals are right in the middle of trying to figure out what to do with it.

So for this June edition, I want to share where I stand. The honest version.

The Numbers Are Hard to Ignore

Let's start with some context. According to SHRM's 2025 Talent Trends report, 43% of organizations now use AI for HR tasks, up from just 26% in 2024. In recruiting alone, 66% use AI to write job descriptions and 44% use it to screen resumes. And 89% of HR professionals using AI in recruiting say it saves them time.

That's not hype. That's a real shift happening in real organizations.

As AI strategist Allie K. Miller puts it, organizations that resist AI adoption risk falling behind as accessibility to AI tools expands globally. I've been following Allie's work for a while now, and her core message is that AI adoption isn't really a technology question. It's a people, process, and culture question. That resonates with everything I've seen in HR.

Where AI Genuinely Helps Us

Here's what I know from both research and practice.

It frees up your time for the work that actually matters. According to TechTarget's 2025 HR technology research, generative AI can handle routine employee inquiries, like questions about vacation allocation or the leave of absence process, freeing HR professionals for more nuanced, strategic work.

It makes us better at analytics and decision-making. Visier's 2025 people analytics report found that AI algorithms can analyze large volumes of data to identify patterns and make predictions, helping HR professionals make more informed decisions and improve overall organizational effectiveness. For those of us who want to move from reactive to strategic, this is the real opportunity. It's also exactly why I wrote about natural language processing for Smith Business Insight back in 2022 and why I've championed people analytics in every organization I've worked with since.

It improves the quality of outputs. A May 2025 study published in Harvard Business Review, led by researchers at Zhejiang University and involving over 3,500 participants, found that generative AI collaboration produced work that was more efficient and often superior in quality, whether it was drafting performance reviews, brainstorming, or writing emails.

The Concerns Are Real Too

I'm an optimist about AI, but I'm not naive about it. There are legitimate risks HR leaders need to take seriously.

Data privacy is the big one. A 2025 Talentech survey found that 55% of HR professionals are worried about AI data privacy, and 63% cite data security as their top concern when implementing AI tools. And for good reason. HR teams hold some of the most sensitive data in any organization: performance reviews, compensation information, health-related accommodations, personal details. As SHRM noted in its 2025 coverage of AI in the workplace, providing AI access to core HR data, including employees' personally identifiable information, performance reviews, and compensation data, involves incredibly sensitive information.

Free tools are not enterprise tools. This is something I see overlooked constantly. According to OpenAI's own June 2025 data, 27% of ChatGPT consumer messages were work-related, and much of that is happening on personal, free accounts rather than secure enterprise versions. If you're typing confidential employee information into a free AI tool, you need to understand what happens to that data. In many cases, it's being stored and potentially used to train future models.

The engagement risk is real. That same Harvard Business Review study I mentioned above found a hidden trade-off worth paying attention to. Participants who used generative AI on one task and then moved to a different task without AI support reported an average 11% drop in intrinsic motivation and a 20% increase in boredom, compared to colleagues who completed tasks without AI assistance throughout. The researchers found that AI tends to remove the most cognitively stimulating parts of work, which are often the parts that make it meaningful.

Bias doesn't disappear, it just gets automated. AI is only as good as the data it's trained on. In HR, that means historical biases in hiring, promotion, and performance management can get baked into the tools we're using. Human oversight isn't optional here. I talked about this directly on the Smith Business Insight podcast, and it's something I come back to again and again in my work.

My Bottom Line

I went back to school in 2020 because I believed AI was going to transform HR, and I wanted to be someone who understood it well enough to lead that conversation rather than just react to it.

Six years later, I'm more convinced than ever. But I've also learned that the leaders who get the most value from AI are the ones who combine genuine curiosity with critical thinking. They're not just asking "can we use this?" They're asking "should we, how, and with what guardrails?"