The Human Element

The Human Element, presented by Wisq, is a podcast hosted by Barb Bidan where CHROs and senior HR leaders share candid stories and practical perspectives on how AI and innovation are shaping the future of HR. In this episode, Barb sits down with Erica Koenig, CHRO at SPS Commerce, a leader in supply chain cloud solutions helping retailers and suppliers connect, collaborate, and grow through data and automation. They talk about co-creating AI adoption with employees, building trust through transparency, and why the best HR leaders right now are operating in perpetual beta. Subscribe today.

The biggest misconception Erica Koenig sees among HR leaders approaching AI is that it can be managed like a project. "You can treat AI adoption as a project and it's not. It's a capability shift, it's a culture shift, it's a leadership shift." Projects have start dates and end dates. AI adoption has neither. Getting that framing right, she argues, changes everything about how you lead through it.

Koenig is the CHRO at SPS Commerce, where she leads global people strategy, culture, and organizational design. Her approach to AI integration is built on three interlocking principles: invite employees to co-create it, be relentlessly transparent about how it is and is not being used, and get comfortable operating in perpetual beta.

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Inviting Employees to Co-Create the Future

The first principle sounds simple but is frequently skipped. Koenig is direct about why it matters: "Really involving our employees early through pilots, helping them actually co-create some of the things that we're working on, really helps just initiate the people side and it's not being done to them, but they're actually a part of it."

The Gong pilot at SPS Commerce is the clearest example of what this looks like in practice. The sales team already had their calls recorded in Gong. Koenig's team used that data to build a coaching system that gives reps personalized feedback on their calls, tied to SPS's prescriptive selling model. The key design decision was making it self-directed as well as manager-driven. "People are doing it with their manager, but they can also do it themselves and do some self-learning around learning about things that they could do better." Giving people agency over the tool rather than having it deployed on them made a meaningful difference in how it was received.

The performance management coach SPS launched more recently follows the same logic. Koenig loaded in the leadership model, people leader expectations, and goal-setting frameworks, and built a tool to help managers prepare reviews, gather feedback, and give more continuous, actionable development conversations. She is candid that she does not have results yet. "That one I'm super excited to see how it works and I'm sure we'll have to tweak it as we go." That openness is intentional.

Building Trust Through Transparency and Ethical Guardrails

Employees will engage with AI when they understand its purpose and trust that it is being deployed responsibly. Koenig's approach starts at the top. "It's communicating from the top. We talk about it, our CEO, our chief technology officer, we're all talking about it and how we're using AI and what it means and what it doesn't mean."

The purpose framing matters as much as the frequency. "It's about speed, it's about not replacing the relationships and the humanity part of culture, but actually allowing us to focus on that by taking away some of these mundane tasks or things that AI can do better for us." SPS is a technology company, so there is a reasonable baseline of comfort with AI among employees. But Koenig does not take that for granted.

On ethical guardrails, she is specific. HR and legal are actively reviewing any algorithms involved in talent selection or performance management to check for bias. Regular auditing and human oversight are non-negotiable. "We have to be really kind of hyper vigilant in ensuring that whatever algorithms we're building or processes or feedback loops that we are ensuring the human pieces involved in that, and that we are testing it robustly."

She also makes a case for AI as a tool for personalization at scale, which itself builds trust over time. Human managers cannot tailor career development and growth opportunities to every individual on a large team. AI can. "If they're growing their careers, if they're learning, if they're getting the opportunities, then they can see the value."

What HR Leaders Need to Unlearn

Koenig has a clear-eyed view of what the current moment requires leaders to let go of, and the list is longer than most people want to hear.

Change fatigue is real, and leaders have to stop underestimating it. People are on different timelines with AI comfort and learning. Communicating once is not enough. Empathy and consistency are the tools, and neither can be automated.

The shift from process ownership to capability building is harder. The question is no longer "here are the steps to follow." It is "how do you ask AI the right questions to get what you need, and then how do you ask again?" That is a fundamentally different skill, and it requires leaders to model it before they can teach it.

Subject matter expertise as a fixed identity is also losing ground. "Gone are the days where people were these deep, deep subject matter experts and they were valued for that. And not to say they're not, but it's just the world is just changing so fast now." Learning agility and comfort with ambiguity are the new differentiators. What you knew last month may already be outdated.

The Perpetual Beta Mindset

Koenig's sharpest concept is one she calls perpetual beta, and she applies it to everything including the tools her own team is building. "Nothing's ever fully baked and nothing's ever perfect. And frankly, half the time when you roll something out, it's better to roll it out when it isn't completely done because you are going to get feedback and then you can iterate."

The performance management coach is the live example. SPS launched it and immediately invited feedback on what it did well, what it missed, and what people wished it could do. That is not a workaround for shipping something unfinished. It is the design. Transparency about the iteration builds more trust than pretending a tool arrived fully formed.

For type A leaders who struggle with shipping before something is perfect, Koenig's reframe is practical: the goal is not perfection at launch, it is accuracy over time. Feedback is the mechanism. Shipping early is how you get it.

Treat AI as Your Best Collaborator

Koenig closes with a framing she credits to someone else but has made her own: treat AI as your best collaborator, not your competitor. "Leaders who win are going to be the ones that learn how to work with the intelligent tools, not trying to like compete against them."

Her advice for HR leaders just starting out is the most personal thing she says in the episode: embrace and experiment, and start with your own life. Use ChatGPT for something personal. Try things that are low stakes. Get comfortable enough that you can talk about it with your team from a place of experience rather than theory. "In the beginning it's scary, but I think you can do some pretty fun stuff with it."

The leaders who will navigate this well are not the ones with the most sophisticated strategy on day one. They are the ones willing to stay in motion, keep iterating, and bring their teams along honestly.

To hear more conversations like this one, subscribe to The Human Element wherever you get your podcasts.