We recently held our 2026 HR Lab and brought Minnesota’s HR leaders and their technology counterparts into a room and asked them to skip the theories around AI. What is actually working inside your organization? What has failed? What are you still figuring out? The conversation that followed was refreshingly honest.
Along with moderator Kathy Robideau, Chief Growth Officer at Versique Executive, Professional & Interim Recruiting, our speaker panel featured:
- Carita Hibben, Vice President of HR and AI Policy Deployment Lead at C.H. Robinson
- Julie Avchen, Director of Continuous Improvement and Process Control at C.H. Robinson
- Kristen Gaarder, Chief People Officer at Perforce Software
- Mike Halvorson, Vice President of IT at Perforce Software
Each leader shared how AI strategy is unfolding inside their organization, what is working, what has failed, and what they are still refining. What became clear throughout the discussion is that AI strategy in the workplace is not primarily about tools. It is about structure, leadership, and people.
AI Strategy Requires Structure
AI does not scale through enthusiasm alone. It scales when it is embedded into how the business operates.
At C.H. Robinson, AI strategy is built into the company’s operating model. It is reviewed through monthly scorecards, tied to measurable business outcomes, and supported by executive accountability. If metrics remain red for three months, leaders engage in deeper problem-solving.
AI is not treated as a side initiative. It is part of how the organization runs.
Perforce shared a different approach, forming a cross-functional AI Council to explore use cases and foster innovation across the enterprise. Their model is collaborative and grassroots.
Two different paths. Both effective. The common denominator is ownership and clarity.
Adoption Is the Real Work
Rolling out AI tools is relatively easy. Driving adoption is where leadership shows up.
One organization built dashboards that track AI adoption down to the individual employee level. Leaders can see who is using new capabilities and who is not. When adoption lags, the response is conversation, not punishment. Why is this not working? What needs refinement? Is additional training required?
That feedback loop turns AI implementation into an ongoing dialogue.
This is especially true for AI in HR. Whether it is performance review prompts, talent screening tools, or AI-assisted internal search, success depends on trust and consistent usage. If employees do not see value, they will not adopt it.
Addressing Employee Concerns Directly
No AI strategy in the workplace can succeed without addressing fear.
The most common concern raised during the discussion was job displacement. In one example, when a new feature automated repetitive updates, an employee responded, “This is how I add value.”
That moment reflects the broader shift organizations are facing. If AI handles transactional work, value moves up the stack toward customer engagement, strategic thinking, and growth giving team members more time to spend with clients or make sales calls.
Panelists were clear in their messaging. AI is about increasing velocity and competitiveness, not quietly eliminating roles. At the same time, adaptability is required. Organizations were transparent that expectations are evolving.
Clarity reduces speculation. Silence fuels it.
Human in the Loop Is Essential
Another consistent theme was the importance of human oversight.
One example shared involved an AI agent that reads customer emails and generates freight quotes. While the technology could send those quotes directly to customers, about 90 percent are reviewed by a human first.
Context matters. Relationships matter. Strategy matters.
AI may generate a recommendation. A human determines whether it aligns with customer history or long-term business goals. This is human in the loop AI in practice.
The same principle applies to AI in HR. Tools like Copilot or generative AI can accelerate drafting and summarizing. They cannot replace discernment. AI may get teams part of the way there. Judgment remains essential.
Balancing Speed and AI Governance
A thoughtful AI strategy must balance speed with AI governance.
Some organizations initially restricted AI use while assessing data security risks. Over time, they enabled usage within approved platforms to keep corporate data protected. Ethical AI training ensured employees understood appropriate use.
Others described a fail fast approach. Launch. Learn. Refine. Relaunch. The key is not perfection at rollout, but the willingness to adjust quickly while maintaining governance guardrails.
AI governance is not about slowing progress. It is about enabling responsible innovation.
The Skills Shift Is Underway
As AI handles more repetitive work, expectations around critical thinking, curiosity, leadership, and communication increase.
What were once labeled soft skills are becoming core competencies. Employees must evaluate AI outputs, question assumptions, and apply insight strategically. Leaders must develop teams who can operate effectively in this environment.
Freeing up time only creates value if that time is redirected intentionally. Growth conversations. Customer engagement. Innovation.
AI strategy in the workplace quickly becomes a workforce transformation strategy.
Opportunity and Complexity Go Hand in Hand
We also acknowledged that AI introduces new challenges. Talent acquisition teams are navigating synthetic applicants and additional verification processes. Efficiency gains are real, but so are new risks.
AI is not purely additive. It requires new systems, new oversight, and new thinking.
Looking Ahead
If there is one takeaway from this year’s HR Lab, it is that AI strategy is no longer optional. It is becoming embedded in how organizations operate.
The companies making meaningful progress are not chasing every new tool. They are embedding AI strategy into their operating model, measuring adoption, reinforcing human judgment, investing in leadership development, and building strong AI governance frameworks.
HR plays a central role in that journey. From AI in HR processes to enterprise-wide change management, we are helping shape how this transformation unfolds.
I am grateful to our panelists for their transparency and to the Minnesota leaders who joined us for the conversation. We are learning in real time.
The future of work will not be defined by AI alone. It will be defined by how intentionally we lead through it.
