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HDI Service & Support World
April 25-29, 2027
Caesars PalaceLas Vegas, NV
How The University of Notre Dame’s Help Desk Evolved into a Service Desk

For more than 30 years, The University of Notre Dame’s Help Desk had been seen as a “beloved institution.” It consistently earned high marks on campus satisfaction surveys from students, faculty and staff.

But at some point, beloved isn’t enough.

During a session at HDI’s Service & Support World, Chris Gillis, the director of the service desk, Mike Voss, manager of the service desk; and Hannah Elliott, manager of the service desk, walked through what it takes to evolve a function that everyone loves into something that the university can’t function without.

To understand why change was necessary, you have to understand how IT works at the University of Notre Dame. It’s not one monolithic department. Here’s a snapshot of what’s going on:

  • Central OIT handles enterprise infrastructure (networking, Gmail, endpoint management).
  • Some areas, like athletics, have embedded IT staff funded through OIT.
  • Schools like the Mendoza College of Business and the law school have their own dedicated IT directors and technicians.
  • And then there’s everyone else, departments without dedicated support who funnel everything through the Help Desk on an as-needed basis.

Got it? Sheesh! That’s a lot of complexity for one team to navigate. And for years, the Help Desk did it through institutional knowledge and goodwill.

“It was reactive support,” Gillis says. “People called, people walked in and that was the support provided. It was the definition of a traditional Help Desk.”

What it wasn’t: proactive, scalable or set up to tell a story to leadership about the value it was delivering.


The case for change

When a longtime Help Desk manager retired, Gillis saw an opening to rethink the model. At the time, he was managing a separate team called Help Desk Dispatch, which had started blending Tier 1 and Tier 2 work. The two teams were doing similar work under different names, confusing everyone outside the department. He decided it was best to combine everyone into one team.

Next, he and Voss built a career pipeline program, hiring early-career people as temp-on-call staff with the goal of bringing them into full-time roles. They created promotion paths — IT Assistant 1 to IT Assistant 2 — with more pay and responsibility at each level.

“That is one of the things I’m most proud of that our team has done,” Gillis says. “We made career growth very intentional.”


Operationalizing the merge

Once the Service Desk launched, Voss took on the work of making it function. The first move was to collapse the phone system into a single queue with a single number. No more pressing 1 for this team and 2 for that team.

Then, came the harder work. The team decided what Tier 1 work looked like, versus what needed escalation to embedded IT consultants. They created a secondary assignment group in ServiceNow so that when a ticket came in from, say, the School of Architecture, both the service desk and the School of Architecture IT team could see it in real time, not after the fact.

“That created better collaboration and communication to make sure we’re taking care of our customers in a streamlined way,” Voss says.

Standardized handoff language, a shared Google group with IT consultants across campus, daily standup meetings were aimed at the same goal: making sure a customer never fell through the cracks between teams.

They also ran a skills assessment to identify technical gaps across the staff and built training to help them ramp up. The cross-training that followed was the hardest part, Voss says. That’s because everybody on the team only did specific tasks: some people only answered phones, worked in imaging or handled walks-in.

“Having everybody do everything is hard, but critical to the success of what we’re able to do,” Voss says. “But now, if an MFA reset floods the queue or an on-campus event needs extra hands, we can flex the team wherever it’s needed.”

But letting staff know about all these changes is important, Gillis says.

“We communicated a lot and we would always share what was coming,” Gillis says. “And we’d still hear, ‘Well, this is the first we’re hearing about this.’ We had to really understand how to communicate with people on the team to make sure they’re ready to receive the information the way they need to, to internalize it.”


The culture of yes (and its consequences)

The University of Notre Dame’s Service Desk adopted a culture of yes. Campus partners started coming to them with new services to take on and the answer was almost always yes. That’s how the scope exploded: Mendoza College of Business frontline calls, classroom support dispatching, computer builds and deploys and early conversations about onboarding the procurement office’s help desk (which would make the University of Notre Dame’s Service Desk the first to handle a non-IT function).

“We branded ourselves very specifically as the Service Desk, not the IT Service Desk,” Gillis says. “The vision is one place you go for help for service on campus.”

But “yes” has a cost. Services were getting added before training was complete. Sometimes, things weren’t documented. And the staff was getting exhausted.

“Growth is only successful if it is sustainable,” Voss says. “A team that is 100% utilized has 0% capacity for innovation and empathy.”

Here’s how they slowed down:

  • Took deliberate pauses after major rollouts to make sure the team was solid before the next change came through.
  • Pilot phases, where a handful of team members would pressure-test changes before they went live.
  • Memorizing this sentence: “Yes, but maybe not this month. Could we start two months from now?”


Building structure without building silos

All the changes were exciting, but it was taking a toll on Gillis and Voss. At one point, Gillis had 14 direct reports, plus a rotating pool of up to 25 temp-on-call staff. Even though everything lived in one ServiceNow assignment group (incidents, requests, interactions, loaner programs, classroom work, field deployments), reporting was getting to be difficult.

The solution was to split the work into two operational areas: Service Desk Operations and Service Desk Field Services. Elliott was hired to lead Service Desk Operations. Her department covers what happens behind the scenes: phones, chat, triage, imaging, inventory. Field Services covers what the campus sees: deployments, classroom support, in-person visits. However, everyone still cross-trains with both departments.

“Having two managers in place makes it easier when people have questions,” Elliott says. “It allows people to have that go-to resource while still allowing Mike and me to keep our heads clear. We want every person who steps foot in our university to know that if they have a problem, Service Desk is going to fix it.”

Editor's Note: This article is an editorial recap of a conference session based on the reporter's notes, observations, and interpretation of the discussion. It is intended to highlight key themes and takeaways and should not be considered a transcript or an official representation of the speaker's or organization's views.

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Bridging the Gap: 5 Tips for Cross-Functional Collaboration That Enables AI Transformation

Ask ten executives who owns AI at their company, and you’ll get ten different answers. IT says it’s not their call. Legal gets blamed for slowing everything down. HR figures it’s someone else’s department. Meanwhile, teams are buying tools nobody signed off on, duplicating work and hoping it all sorts itself out. Sound familiar?

Lisa Duerre spent the last year studying why that happens. As part of an applied research project for her leadership consulting collective, RLD Group, she studied where AI adoption breaks down inside organizations, and where it works. The findings from RLD Group’s research helped inform a collaboration on the CONVERSATIONS WORTH HAVING®: The Human Accelerator for Artificial Intelligence Quick Start Guide, which is available as a digital download.

Duerre views organizations through what she calls an I–WE–US leadership framework, defined like this:

  • I: individual judgment and accountability

  • WE: workflows and cross-functional coordination

  • US: governance, decision rights and organizational measures

“All three levels are contributing to the breakdown or the alignment, whether people realize it or not,” Duerre says. “AI is amplifying whatever’s already true in your system. The teams that were disconnected before AI showed up are more disconnected now. The ones that talked to each other are moving faster, together.”

If your company is ready to collaborate better with AI tools, Duerre shared the following tips. Take a look.

Form a cross-functional AI committee

Duerre’s background is in HR, and she says most HR leaders assume AI ownership belongs to IT. It doesn’t, at least not exclusively.

“Ownership needs to sit at the system level,” Duerre says. “Each function carries a piece of it, based on what they do, how well they understand that part of the business and how their work depends on everyone else’s. AI is flattening how we work. You can’t just keep it in your own business unit anymore. You have to look all around you.”

For starters, she suggests building a cross-functional AI committee instead of having one department make all the AI decisions. Legal, IT, cybersecurity and HR should be on the committee, Duerre says.

“If you have a C in front of your title, you should be on that committee,” Duerre says. “That’s how I look at it, because it’s a system-level solution.”

During these meetings, Duerre says you’ll find out that some departments are racing ahead with AI and others are holding back.

“Both sides need to name the trade-offs aloud,” Duerre says. “With teams moving too cautiously, you have to talk about the opportunity cost of falling behind. With teams sprinting ahead, you have to ask them what happens if they don’t bring everyone else along with them.”

Figure out how to use AI strategically

Most companies spent the past two years telling employees to use AI with anything, without much strategy behind it. Duerre says that’s starting to catch up with organizations as finance teams scrutinize the cost.

Her rule of thumb: if you can’t articulate the goal and how you’ll measure success, don’t roll it out yet.

“Teams that use AI well have a strategy behind it,” Duerre says. “They’ve kicked the tires on what they’re trying to solve it for. You need to ask yourself, ‘Which business outcome are we trying to improve, and what must be aligned for AI to create measurable value?’”

Here are a few examples of how to use AI strategically:

  • A company could select a workflow that regularly creates delays, redesign it with AI and test the new approach. Then, measure whether it improves time, cost, quality or capacity.

  • Use AI to support early sales outreach and qualification across markets and languages. AI can help a business reach and assess more potential opportunities, while people remain responsible for understanding the customer and building trust.

  • Flag patterns in customer complaints across multiple channels with AI, so leadership can see recurring problems before it shows up in satisfaction scores.

Check-in regularly during an AI rollout

Duerre recommends a minimum weekly check-in during any AI rollout, sometimes daily depending on complexity. But the format matters more than the frequency. Status updates don’t cut it.

“Ask, ‘What are we learning and what are we surprised by?’ That’s a question that helps you with your check-ins, versus, ‘It’s in three products now and we’ve tested six,’” Duerre says. “That doesn't help, because you’re having these meetings to figure out what’s working and why. If you ask more strategic questions, you can move even faster.”

Publish AI guardrails

Employees who don’t know what’s allowed with AI will either freeze or go around the system entirely, Duerre says. She recommends publishing clear, specific guardrails on what’s okay and what’s not. Come up with some real examples, and pair them with an intake process that doesn’t require writing a thesis to get an approval for using it.

"The approval path should be lightweight, not bureaucratic,” Duerre says. “Something like, ‘If you’re going to use AI, here’s the path. And if it needs approval, here’s three or four quick questions for you to answer.’”

Take employee anxiety about AI seriously

“AI is just a tool” is a phrase Duerre hears at nearly every conference she attends, but she doesn’t buy it.

“Saying it’s a tool is underselling what’s happening at companies right now,” Duerre says. “AI is changing how we work. It’s changing how we lead teams.”

Duerre wants leaders to remember that a lot of employees are fearful of AI. Pew Research Center found 52% of U.S. workers are worried about the future impact of AI in the workplace.

Employees who feel AI is being “done to them,” instead of built alongside them are especially anxious, she says.

“Leaders need to recognize that anxiety is contagious,” Duerre says. “As a leader, this is your opportunity to show up as the safe, steady person who is showing what you’re learning with AI. And don’t be afraid to show how you’ve failed using AI, too.”

Duerre asks every executive she works with: “Who am I with AI?” and encourages them to pass this mindset question along to their employees, too.

“AI is now your teammate,” Duerre says. “Phrasing it as, ‘who am I with AI?’ is different than, ‘what’s going to happen to me with AI?’ You really want your team to feel empowered with AI and show them how it can help accelerate their career.”

Put these ideas into action

Rewiring your organization for AI requires more than the right tools. It takes shared language, practical frameworks, and a willingness to keep learning. Here are a few resources to help you take the next step.

  • Enterprise AI Playbook: Practical frameworks and executive discussion questions to help IT, HR, and business leaders align around AI that delivers measurable value.

  • Work-First AI Use Case Assessment: Identify the workflows where AI can have the greatest impact before you invest in new tools.

  • The REWIRED Brief: Get weekly insights, real-world case studies, and practical advice on leading AI transformation.