If you’re a public-sector IT director in 2026, the mandate is clear: automate services, modernize infrastructure and prove ROI, all while budgets stay flat and staffing stays lean. The pressure is real, and it’s coming from every direction. Residents expect digital-first experiences. Federal frameworks are pushing AI adoption. And leadership wants results, not pilots.
Here’s the uncomfortable truth most software vendors won’t say out loud: AI doesn’t fix a broken foundation. Fragmented ticketing systems, invisible workloads and siloed departments don’t get smarter when you add AI on top of them. They just fail in more sophisticated ways.
Every dollar spent on AI capability built on top of unstructured, unverified data is a dollar that won’t deliver the ROI anyone is expecting.
The state and local agencies that deliver on the AI mandate aren’t the ones who move fastest to spin up a chatbot. They’re the ones who ask a harder question first: Is our IT operation mature enough to support these new initiatives?
San Joaquin County in California and the city of Worcester in Massachusetts asked exactly that question. Their answers offer a practical road map for any state or local IT leader trying to build a solid foundation that’s ready for what comes next in the IT modernization journey.
THE STARTING POINT MOST IT TEAMS KNOW TOO WELL
When then-CIO Mark Thomas arrived at San Joaquin County, the IT operation had almost no visibility into its own work. The legacy ticketing system was so underutilized that management had, in Thomas’ words, “zero insight into where the work was happening or if it was even being tracked.”
HR managed services through spreadsheets and email. As a 100 percent chargeback organization, IT staff manually coded every billable hour, a process prone to error and difficult to audit.
The city of Worcester presented a similar picture.
When Samantha Sendrowski arrived as director of IT administration in 2022, she found a department at a “basic ticketing level” with processes that were “very disjointed, and some didn’t exist,” she said. Over 100 open projects were tracked in Excel by a team of 34. The knowledge base was unsearchable PDFs. Most critically, there was no formal change management program. Changes to production systems were happening without governance or structured risk assessment.
These aren’t outlier situations; they describe the starting point for a significant share of state and local IT organizations today. The challenge isn’t motivation or talent. It’s the absence of a structured foundation. And without it, every technology investment that follows, including AI, is building on sand.
WHY ITSM MODERNIZATION COMES FIRST
There’s a temptation to treat IT Service Management (ITSM) modernization as a housekeeping task, something to get to eventually after the more exciting projects. That framing gets the sequence exactly backward.
AI tools need clean, structured inputs to deliver value. To be successful, most tools require a knowledge base that’s current and organized around how people actually ask questions. Workflow automation requires documented processes before anything can be automated. Predictive analytics require historical ticket data that’s been consistently categorized over time. Without this mature ITSM infrastructure, AI produces unreliable outputs at best and erodes user trust at worst.
Many government CIOs now rank AI as the No. 1 technology priority, but the pressure isn’t just to adopt it: It’s to show measurable outcomes. That’s only possible when the underlying data is clean and reliable enough to measure against. ITSM maturity isn’t a detour from digital transformation. It is step one.
HOW TWO GOVERNMENTS IMPROVED ITSM MATURITY
San Joaquin and Worcester took different tactical paths to improving ITSM maturity but followed consistent principles.
1. Start with the highest-risk gap
When Sendrowski assessed where to begin in Worcester, the answer wasn’t the quickest fix. It was the one representing the greatest operational risk.
“We started with change management since it was the least mature and we felt that there was the greatest risk not having it,” Sendrowski explained.
San Joaquin took a different but equally deliberate approach. Before touching any technology, Thomas convened a structured conversation across IT teams to surface shared pain points and build the organizational buy-in needed for meaningful change.
The principle was the same: Understand the problem clearly before selecting the solution.
“It was a call to arms, really, and we brainstormed together, trying to identify where we had similar problems and challenges, and how we could solve them,” Thomas said.
2. Build the data layer before you use it
Both organizations were operating without meaningful data before modernization, not because data didn’t exist, but because it wasn’t being captured, structured or made accessible in a useful way within their legacy ITSM platforms.
To remedy this, both governments went to market for new ITSM tools and landed on TeamDynamix.
San Joaquin’s transformation centered on consolidating fragmented systems onto a single platform, giving county leadership visibility into workloads across 25 departments for the first time, and enabling informed resource decisions that hadn’t been possible before.
“We saw, with TeamDynamix, that we could support the platform without a lot of dedicated resources,” Thomas said. “By bringing everything together in a single tool, we can get a comprehensive view of everyone’s workloads and better manage the resources we have. Having that single-pane-of-glass view has been really, really helpful.”
With TeamDynamix in place, Worcester used early help desk data to identify which service requests drove the most ticket volume, directly shaping their self-service strategy.
“Now that we can see our service desk data better, we can see that the scope of services we offer has increased, but not necessarily our head count,” Sendrowski said. “To address this, we use the data we now have to better allocate our resources and offset some of it with self-service.”
Small, data-driven decisions like this compound over time into meaningful ticket deflection.
3. Think enterprise from day 1
Neither organization treated ITSM modernization as an IT-only exercise.
San Joaquin extended the platform to HR and the Public Defender’s Office early, replacing email-and-spreadsheet workflows with structured, trackable processes.
As a result, employees could see the status of their requests and leadership could track progress without chasing people down.
The Parks Department is now queued to use Enterprise Service Management capabilities for public issue reporting, asset management and preventative maintenance.
Worcester is actively rolling out ESM to its Law Department and HR, building directly on the foundation established in IT.
The intent in both cases is explicit: IT is an enabler of organizationwide efficiency, not just a service desk.
WHAT MATURE ITSM UNLOCKS
San Joaquin’s entire platform, serving 10,000 employees across 25 departments, is managed by just half an FTE, freeing the rest of the team for strategic work.
Worcester has used improved visibility to reallocate resources and grow the scope of services delivered without growing head count.
In state and local government, where hiring is slow and budgets are constrained, a platform that scales without proportionally increasing administrative burden isn’t a luxury. It’s a requirement.
The automation payoff is equally concrete.
San Joaquin’s IT department must track and bill every hour of work back to the departments it serves. Before modernization, staff coded hours manually. After integrating TeamDynamix with Workday, labor is captured and billed automatically every month.
The most significant long-term return from both implementations isn’t what happened inside IT. It’s what happened when the same platform extended to HR, legal, facilities and citizen-facing services.
And here is the direct line to AI readiness: Structured ticket data, a mature knowledge base, documented workflows and clean integrations are the exact inputs AI needs to be successful. Neither San Joaquin nor Worcester had this infrastructure before.
Both have it now, and both have a foundation that can actually support the next level of service management modernization.
WHAT STATE AND LOCAL IT LEADERS SHOULD DO NEXT
The journeys of San Joaquin County and Worcester aren’t exceptional. They’re instructive. Both started from a place most government IT organizations will recognize, and both followed a path that any IT director can adapt to their organization.
Start by auditing your ITSM maturity honestly before evaluating AI tools. Where are your biggest visibility gaps? Do you have structured, categorized ticket data going back at least a year? Is your knowledge base actually used by employees? Do you have formal change management in place?
The answers determine where you start, and whether an AI investment will have the data it needs to perform.
Then start with the highest-risk process, not the most interesting use case. Stabilizing the highest-risk gaps first builds the organizational trust, process consistency and data quality that advanced tools like AI require.
Finally, look at the tools you have in place to support your foundation and determine whether they can help you scale to the next level. You may find, as both San Joaquin and Worcester did, that a new ITSM tool is needed.
If evaluating ITSM platforms, prioritize low administrative overhead. State and local IT teams are stretched thin. A platform that requires dedicated developer resources to configure, maintain or adapt becomes a liability when staffing changes or priorities shift.
Both San Joaquin and Worcester specifically cited the no-code, low-lift nature of TeamDynamix as a critical factor in their ability to sustain and expand what they’ve built.
Finally, think enterprise from day 1, even when deploying incrementally. If you’re selecting an ITSM platform today, ask whether it can extend to HR, legal, facilities and citizen services without a separate procurement and implementation cycle.
THE FOUNDATION IS THE STRATEGY
State and local IT leaders are being asked to accomplish things simultaneously that are, in practice, sequential. You can’t show AI ROI without clean data. You can’t automate workflows that haven’t been documented. You can’t expand digital services without a platform that’s proven it can scale.
San Joaquin County moved from prefoundational chaos to a mature, enterprisewide operation in three years. Worcester built the change management discipline, self-service infrastructure and data foundation to support continued expansion in a similar time frame. Now, both have a solid foundation for further modernization and AI adoption.
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