1. Start with “battlefield circulation”: go listen before you prescribe

When Patricia joined Seagate, she didn’t start by rolling out a new HR strategy from the top down. She started by listening. Coming from the military, she described it as “battlefield circulation” — getting out into the organization, seeing what’s really happening, and understanding the pain points at the tactical edge.

That mindset matters because the work that drives the business often lives far away from the executive table. Patricia said the CEO wanted to understand the pulse of the workforce, so she went straight to employees to hear what was working, what was broken, and where trust was being lost.

“It’s battlefield circulation. It’s go and listen, don’t talk. Just listen and go and tour the different parts of the company.”

One of the clearest signals she heard: employees were finding out about internal opportunities on LinkedIn or external job boards before they ever saw them inside the company. That wasn’t just a process gap — it was a trust gap. And because she heard it directly from employees, it became obvious where HR needed to move first.

2. The goal isn’t just faster work — it’s higher-value work

One of Patricia’s strongest points was that AI-assisted work still requires human judgment. Getting to an answer faster is useful, but speed alone is not the measure of performance. The real question is what the employee does with the time and insight that AI creates.

She shared the example of a junior employee who used AI to reduce a global regulatory labor research task from 16 hours to 30 minutes. That’s a huge productivity win. But Patricia’s challenge to her was: now take the time you saved and figure out what it means for Seagate.

“It’s great that you’re augmented by AI… You got to a faster result. What does that mean to bring value and revenue to the company?”

That’s the shift leaders need to make. AI can gather, summarize, and accelerate, but employees still need to understand context, assess business impact, make recommendations, and think critically. Performance in the AI era won’t just be about output. It’ll be about judgment, curiosity, adaptability, and the ability to turn faster work into better decisions.

3. Stop treating talent like it belongs to one manager

One of Patricia’s biggest cultural shifts was challenging the idea that talent “belongs” to an individual leader. In many companies, managers talk about “my team” or “Joe’s team” or “Patricia’s team.” But that language can reinforce talent hoarding and make internal movement harder than it needs to be.

Patricia brought a different frame from the Army: the talent belongs to the organization. The question isn’t, “How do I keep this person on my team?” It’s, “Where can this person create the most value for the mission?”

“No, it’s Seagate’s team. It’s Seagate’s workforce. It’s Seagate’s talent. Where is the best place for that talent to help us deliver on our objectives?”

That doesn’t mean every employee can move instantly. Sometimes a manager has a legitimate reason to hold onto someone for a critical project. But Patricia’s approach is to have the conversation: Why are you holding onto them? Could they move in six months? Are we looking at the bigger picture? Without those conversations, employees who feel blocked will eventually leave.

4. Democratizing AI means giving people access, guardrails, and permission to experiment

Seagate had already been using AI and machine learning for years in technical and manufacturing contexts. But generative AI changed the game because it could be put into the hands of employees across the business — not just specialists.

Patricia said Seagate made an intentional choice: don’t centralize AI in one function or one level of the company. Instead, build capability at scale by giving employees access to tools, learning pathways, use cases, and clear guardrails.

“Everyone gets to be an innovator. That impact is amazing.”

What’s especially practical about their approach is that they didn’t define democratization as “everyone gets one approved tool.” Different teams have different needs. Designers, engineers, HR, and sales may all need different applications. The key is getting tools safely cleared through IT and information security — and then letting people run.

5. AI transformation needs structure at every level

Seagate didn’t just hand out tools and hope adoption would happen. They built an operating model around AI.

At the top, they have an AI council made up of C-suite and senior vice president leaders. Beneath that is an AI collective of around 40 business leaders across functions who help operationalize the strategy, shape governance, think through security, and manage resourcing. Then they have around 400 AI champions who have completed training, shown proficiency, redesigned workflows, and help spread use cases across the organization.

“Sales, they’ve just built an agent. HR, you could use that same agent. Don’t reinvent the wheel.”

That structure helps avoid every function solving the same problem in isolation. It also creates a network of people who can translate AI from abstract strategy into daily workflow changes. And as employees create more agents and tools, Seagate is now building an agent management system to track who created each agent, what it does, where it lives, how it’s being used, and whether it still performs as intended.

6. Redesign roles from the workflow up

Patricia is clear that Seagate is not using AI as a reason to lay people off. Instead, the company is asking employees to redesign their roles and workflows. Where are you spending your time? What work should stop? Which processes no longer make sense? Which skills will matter next?

Seagate is also doing a full job architecture review using skills data to understand what jobs require today and what they may require in the future. Patricia emphasized that the focus should be on the skills, not the person currently sitting in the role.

“Don’t look at the person. What are the skills needed today? What are the future skills that you could see that job evolving to?”

That work is already helping Seagate see future talent needs more clearly, including specialized engineering skills they may need to help universities grow. The practical takeaway: job architecture can’t be a static HR exercise anymore. It has to become a living system that helps the company see where work is going.

7. Build the team you have — don’t be so quick to throw people away

Patricia closed with a leadership lesson from the military: you go to war with the team you have, not the team you want. That means your job as a leader is to understand the people in front of you, know their strengths, develop them, and build the capability of the unit.

It’s a powerful reminder in a moment where companies are under pressure to move faster, adopt AI, and rethink work. Yes, there will always be moments where roles change or hard decisions need to be made. But Patricia’s challenge is to start with development, not replacement.

“Don’t be so quick to throw out this precious human asset that you have.”

That might be the biggest takeaway from the whole conversation. AI may change the workflows, the skills, and even the shape of jobs. But the companies that win will be the ones that keep investing in the people they already have.

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