1. Automate the work that requires the least judgment first

In a people-powered business, AI should not start with the work that makes the company distinctive. It should start with the administrative, repetitive, low-judgment tasks that consume employees’ time without making full use of their capabilities.

At Moxie, the goal is to create more time for the work humans are uniquely positioned to do: building relationships, developing strategy, exercising judgment, and telling compelling stories. That means using AI for things like formatting, first drafts, standardization, and internal knowledge retrieval before applying a human layer.

The practical question for leaders is not, “Where can we use AI?” It’s:

What work is taking time away from our highest-value activities?

“The admin, low-judgment work is what gets automated first.”

That framing helps organizations avoid using AI simply because the technology exists. Start with the work that drains time, then reinvest the capacity you create into better outcomes for customers.

2. Secure the house before you start building

Moxie’s AI strategy began with safety, not experimentation.

Because the company handles confidential client information, Kate and the team first developed a detailed AI-use policy with support from cybersecurity and technology advisors. They also strengthened the underlying systems around data privacy, encryption, access controls, and information security.

Only after those foundations were in place did the company begin expanding its use of AI tools.

“We’ve secured the house, we have processes in place, we rolled it out to the team.”

For People leaders, this is an important sequencing lesson. Before encouraging adoption, define what tools employees can use, what information can be entered, how vendors will be evaluated, and what enterprise protections are required.

Innovation moves faster when employees understand the boundaries.

3. Your AI roadmap should be visible to the entire company

AI should not be treated like a side project owned by a few executives.

At Moxie, AI initiatives sit on the company’s strategic roadmap and are discussed in regular team meetings. Employees hear about current pilots, tools being tested, and platforms being built internally.

That transparency matters because employees will form their own story when leadership leaves an information vacuum. And the story they create may be more threatening than the company’s actual intentions.

“What I don’t want to happen is people build their own perception or their own idea of what they think is going to happen with AI.”

Leaders should explain not only what they are implementing, but why. At Moxie, the message is that AI is intended to extend employees’ capabilities, help them become more strategic, and improve the work they deliver to clients.

The more visible the roadmap is, the less mysterious the transformation feels.

4. Build your strategy with the people doing the work

One of Moxie’s first steps was hosting small-group workshops with employees to understand what was actually consuming their time.

The team was asked which tasks they wished could be automated and which changes would meaningfully improve their output. Those conversations helped create a prioritized list of problems to solve.

This is a more effective starting point than selecting a tool and then searching for a use case.

“I hosted a number of workshops with the team directly to really understand what is taking up time in your day-to-day.”

The people closest to the work usually know where the friction is. Bring them into the discovery process, gather specific workflow problems, and prioritize them based on time saved, business impact, risk, and feasibility.

AI adoption becomes much more tangible when it solves a problem employees already feel.

5. Make AI training active, ongoing, and social

A single webinar will not change how people work.

Moxie supports adoption through recurring conversations, hands-on platform training, and monthly AI hackathons. During those sessions, employees work together to solve problems, automate workflows, and share techniques they have learned.

The company deliberately avoids passive training. When a new platform is introduced, employees open their laptops, turn on their cameras, and practice using it together.

“AI can’t just sit with me and the leadership team. It has to be brought up through the team.”

This is how AI becomes part of the culture rather than another tool employees forget about. Create regular spaces where people can experiment, show their work, share prompts, compare use cases, and learn from one another.

Adoption is not an announcement. It is a habit built through repetition.

6. People programs have to reflect the reality of the business

Kate’s career has consistently sat at the intersection of operations and people, and that has shaped how she approaches HR.

People initiatives cannot be designed in isolation from revenue, customer needs, product challenges, or operational constraints. A program may sound attractive from an HR perspective and still be completely mismatched to what the organization needs at that moment.

“You can’t ignore what’s happening on other sides of the business.”

That requires strong relationships with cross-functional leaders and a working understanding of their priorities. People leaders should know where the business is growing, where it is under pressure, and what employees are experiencing in real time.

The same principle applies to retention. Moxie does not assume it knows what will make people stay. The company asks employees directly, listens to the answers, and reallocates resources accordingly.

When the team said the office was no longer creating meaningful connection, Moxie moved fully remote and redirected the investment into compensation, retreats, and intentional in-person development.

The lesson: do not build programs based on tradition. Build them around the environment your people and business are operating in today.

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