Aaron Lael, Utah Department of Government Operations, Division of Technology Services, IT Architect, of the State of Utah, is a Maestro in the Genesys Orchestrators program, a distinction earned through his commitment to continuous learning and shared knowledge. He values Orchestrators as a hands-on community where Genesys customers can test ideas and solve real-world CX challenges together. 

In this article, Lael shares his perspective on leading customer experience in the AI era — offering a thoughtful, pragmatic approach to innovation in the experience economy (as told to Ginger Conlon).

 

My career has been shaped by curiosity, credibility and community. I’ve always had a deep love of expanding my subject matter expertise, especially as new technologies emerge.

I started as a contact center agent on a help desk supporting a large fast-food organization — everything from kitchen equipment to point-of-sale systems. Eventually, I moved into IT and then, somewhat unexpectedly, telecom. When no one wanted to take over a massive, aging Nortel PBX system, I raised my hand and said, “Sure. I’ll learn something new.” That decision opened doors, including opportunities to work on customer experience (CX) systems in the UK and eventually with solutions from Interactive Intelligence, which later became part of Genesys.

About 10 years ago, I joined the State of Utah, where I’ve steadily taken on more responsibility. Right now, I’m exactly where I want to be. I enjoy fixing things, solving problems and making systems better — which is why the Genesys Orchestrators™ program has been such a natural fit for me.

The webinars, ad hoc sessions and hands-on labs available in the program give me a way to explore features in a low-risk environment and then bring meaningful ideas back to the state agencies I support.

Just as important, the Genesys Orchestrators community itself has become a trusted network — a place where we can compare notes, share scripts and work through complex problems together. That sense of shared learning and accountability matters.

That perspective has influenced how I think about leadership.

Learning as a Leadership Strategy

I don’t see myself as a leader of people so much as a leader of ideas and technologies. Over time, I’ve built credibility with the state agencies we support, and I use that trust to help influence better technology decisions. Often, that means slowing things down — especially when a vendor is making big promises that aren’t grounded in the realities of the underlying systems. Leadership, for me, comes down to trust and influence.

This approach has become even more important in the age of AI.

With AI adoption, there’s a lot of excitement — and a lot of risk. For example, I’ve had to help teams understand that automated workflows require deep integrations across systems and real organizational buy-in. Without that, AI promises quickly fall apart.

Sometimes leadership is simply about level-setting expectations and making sure teams understand what it actually takes to succeed.

Establishing Trust in an AI-Driven World

My own thinking about AI has been shaped by caution as much as curiosity. Two books that influenced me early on — Automating Inequality and Weapons of Math Destruction — explore how algorithms can unintentionally disenfranchise people through bias or poor design. That perspective has stayed with me.

While I’ve grown more open to constituent-facing AI solutions, I consistently push for systems that are measurable, reproducible and auditable. If an algorithm influences crucial decisions about benefits, such as food stamps eligibility or deadline extensions for child support payments, there must be a clear, step-by-step explanation of how that decision was made. And there needs to be a way for people to understand and respond.

In my own work, I use AI very deliberately. I see it as a development copilot — a way to mock data, generate realistic sample profiles for presentations or summarize large data sets.

What I don’t do is outsource judgment. When I need insight or context, I still prefer to go to the human experts within my organization. AI supports the work, but it doesn’t replace the relationships.

That human focus is especially important in government CX.

Our constituents and our employees are all residents of Utah. Their experiences are not abstract; they’re personal. And they’re directly tied to why we exist as an organization. The goal at the State of Utah is to make sure happy, supported employees are serving people who need assistance with as little friction as possible.

While self-service and automation play a role, our experience shows that satisfaction ultimately comes from resolving issues with — or at least following through — a human connection.

That belief reflects my own background in contact centers. I value seeing a problem through from start to finish and knowing I’ve helped someone leave in a better place than when they started.

Turning Insight into Impact

What I enjoy most about my CX role today is the visibility. I work across many agencies, which gives me insight into what’s working, what isn’t and where ideas can transfer. In many ways, I act as a value-added connector — helping agencies get more from the platforms they’re already investing in and ensuring those investments produce real outcomes.

When colleagues tell us we’re the most responsive IT team they’ve worked with, that feedback means everything. Responsiveness and accountability are the foundations of trust.

Looking ahead, I’m excited for the AI space to mature. I want to see the dust settle — to see clearly where AI truly delivers value, where it can become lighter-weight and more efficient to better support sustainability, and where it provides measurable ROI. Rationalization, not hype, is what will move AI forward in customer experience.

Personally, I’m revisiting fundamentals — data structures, algorithms and core programming concepts — while also evaluating emerging tools like Genesys Cloud™ AI Guides as compared to traditional voicebots.

Learning never stops; it just shifts focus.

That brings me back to the Genesys Orchestrators program.

If you’re a Genesys Cloud customer and you want to truly understand the platform, I challenge you to find a better learning environment. The live and recorded trainings, access to demos and labs, and the ability to experiment without risk are invaluable. Add in the gamification and the growing community, and it becomes more than a program — it becomes a shared journey of growth. That’s why I keep coming back.

In the AI era, leadership isn’t about chasing every new tool. It’s about earning trust, asking hard questions and making thoughtful choices — together.