Informa helps businesses and professionals in hundreds of ways.

Our international portfolio of live events, world-leading research publications, and innovative digital services provide specialists with the knowledge and connections they need to thrive.

HDI Service & Support World
April 25-29, 2027
Caesars PalaceLas Vegas, NV
Why Your Team is Struggling So Much

A while ago, I supported a Service Desk team as their leader that looked strong on paper. Tickets were being closed. SLAs were being met. The team was skilled and committed.

But something felt off. They were always busy, yet always behind. Analysts were drained. Tickets kept bouncing. Everything was marked urgent. Nothing was clearly broken. But nothing was truly working.

That experience taught me a simple truth: Service Desks don’t struggle because people aren’t working hard. They struggle because they’re not working on the right work.

In my last article, I talked about shifting the mindset, from seeing the Service Desk as a cost center to a value driver. But once you make that shift, a harder question shows up: Are we helping our teams focus on what matters?

That capable Service Desk team struggled, not due to skill gaps, but because work arrived through messy queues, shared inboxes, spreadsheets and side messages. Urgency wasn’t visible, and priorities depended on who noticed something first. Analysts spent more time scanning than solving and second‑guessed decisions. Instead of pushing harder, we redesigned intake and queues around intent, separated different work types, and made urgency clear. The change was immediate: less noise, fewer interruptions, stronger judgment, and a calmer, more confident team, without adding headcount or pressure.

In most Service Desks, the issue isn’t talent. It’s design. Work comes in messy. Requests lack context. Emails turn into tickets without clarity. Everything feels urgent. Queues become a mix of high-value work and repetitive noise. Your best people don’t spend time solving problems. They spend time figuring out what the problem is. They chase missing details, re-categorize tickets and escalate just to stay safe. Over time, this creates fatigue, not because the work is hard, but because it is unclear.

We often treat intake as a technical setup, forms, fields, routing rules. It’s not. It’s a leadership decision about where attention goes. And attention is limited. If your intake is unclear, your team will waste energy trying to interpret work instead of solving it.

A simple shift that changes everything is moving from skill-based routing to intent-based thinking. Instead of asking, “Who knows this system?” ask: “What is the customer trying to do?”

When you design around intent, tickets become clearer, back-and-forth reduces, and decisions become faster. Clarity does most of the work.

Queues are not just lists of work. They drive how people act. If your queues mix everything together, hide urgency, and force constant switching, performance will drop, even with great people.

Before asking your team to do more, reduce the load on their brain. Separate work types. Make priorities visible. Allow focus. When queues are designed well, people don’t need to guess what matters.

Most leaders track volume. Few understand demand. Volume tells you how much work is coming in. Demand tells you why. And that “why” is where improvement lives. Every ticket shows a pattern, repeat issues, broken processes or gaps in knowledge. The biggest gains don’t come from pushing teams harder. They come from fixing what keeps showing up. When you treat your Service Desk as a source of insight, it stops being reactive and starts adding real value.

Teams don’t need more pressure. They need clear guardrails. When priorities are clear, exceptions are known, and escalation paths are simple, people make better decisions. That’s when true ownership shows up.

Leaders can assess whether effort is being misdirected before resolution even begins by asking:

  • Do our intake paths reflect customer intent or just our org chart?
  • Is urgency visible without relying on tribal knowledge (or whoever’s been here the longest)?
  • Are analysts repeatedly re‑categorizing, clarifying or “fixing” the same tickets on arrival?
  • Do queues separate fundamentally different work types so people can actually focus?
  • Do we learn from demand patterns or just report volume and call it a day?

And here’s the part nobody loves to say out loud: the Service Desk is often the least invested department while being one of the most critical functions. We’re expected to be good, fast and cheap at the same time, sometimes with tooling, processes and headcount that were clearly approved by someone who’s never had to read a 12‑email thread titled “Issue” or “Help.”

If several answers are “no,” the Service Desk isn’t under‑resourced, it’s under‑designed.

If your team is reworking tickets, struggling with priorities, or feeling overwhelmed, pause before asking for more effort. Look at the system. Because most of the time, the issue isn’t capacity. It’s design.

When intake is clear, queues are structured, and demand is understood, your team doesn’t have to fight the system. They start delivering value by default.

Related news

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.