By Matt Gilchrist, Account Executive, Ondaro
LinkedIn: Matt Gilchrist
LinkedIn: Ondaro
HR leaders are getting pulled in two directions. Employees want the kind of self-service experience they use everywhere else where they can type a question in plain language, get a clear answer quickly, and move on with their day. That expectation is already changing workplace behavior. Microsoft’s 2025 Work Trend Index found employees choose AI over a colleague because of 24/7 availability (42%) and speed and quality (30%).
But many HR organizations are still operating with knowledge bases shaped by years of growth, urgent workarounds, and systems that do not always line up cleanly. The result is a gap between expectation and reality that creates more than frustration. In a health system, it can quietly drain time away from patient care.
UCLA Health saw this play out in a practical way. Even when answers already existed in the HR portal, employees often skipped self-service and reached out to HR directly or opened a case. Leaders also reported spending time searching for HR information on behalf of their teams. In a patient-centered environment, those extra steps matter.
Stacey Titter, Senior Manager, HR Digital Transformation at UCLA Health, approached the problem with a straightforward view. If employees cannot quickly find what they need, they interrupt care teams, managers step in to interpret policy, and HR becomes a bottleneck for questions that should have been resolved in self-service.
It is tempting to treat that as a tooling issue. Add a new search feature, automate a few workflows, and hope adoption follows. UCLA Health took a different path, and it is one that more health systems are finding they cannot avoid. AI and automation can elevate self-service, but only when the knowledge underneath is consistent, governed, and trusted.
Start where most teams do not want to start
Automated workflows are often described as a technology shift, but the hardest work is operational. When you introduce AI into employee self-service, it forces decisions that are easy to postpone.
Before UCLA Health introduced an AI-enhanced search experience, HR knowledge varied widely across teams. Articles were created independently with different formats, writing styles, and levels of detail. Employees dealt with too much scanning, too much guessing, and too many dead ends. When that happens, they revert to what feels reliable, which is emailing HR or opening a case.
UCLA Health treated knowledge as the foundation of transformation. In late 2024, the HR team dedicated an entire department retreat to AI, with a clear focus on high-quality data, a prerequisite many organizations underestimate.
As Titter put it, “We knew that if we wanted AI to truly enhance the employee experience, we had to start with our knowledge as our foundation.”
That mindset shift changes what knowledge means. It is no longer a set of helpful articles that sit on the side of the business. It becomes a product that must be designed, maintained, and governed because it directly shapes what employees see and whether they trust the portal.
Standardization is change management
For HR teams, standardization can trigger fatigue. It can look like extra work that gets in the way of serving employees. In practice, it is one of the strongest levers for adoption because it reduces variation, which breaks trust.
UCLA Health aligned knowledge content to clear standards, updated articles, and put governance in place so new content follows the same rules. They also built a feedback-driven approach to monitor how the experience performs and where it needs improvement. That governance step is where many implementations stall. Without it, early gains fade. New content gets added without structure, duplicates appear, policies change and content lags, and employees stop trusting self-service.
Go-live is where trust is won or lost
Once UCLA Health went live with an AI-supported search and summarization experience in the HR portal, employees could ask questions in plain language and receive summarized responses with links to supporting knowledge. The experience felt closer to what people use outside of work. That matters because it changes behavior. When employees can find answers they trust, they are less likely to open a case for something self-service should handle.
Titter also understood that credibility is fragile when you introduce AI into a core employee experience. “We approached this launch knowing we had one opportunity to build trust in the experience, and that investing time in our data upfront would determine long-term adoption.”
That is the real implementation challenge. One confusing answer, one missing link, or one outdated policy summary can send employees back to old habits.
A sustainable path forward
In healthcare HR, knowledge naturally spreads. As policies, compliance requirements, local practices, and benefits guidance change, knowledge needs to be reflected accurately. That reality makes governance non-negotiable, and it also makes AI more valuable when it helps teams stay ahead of content revisions.
Looking forward, UCLA Health is focused on sustaining the foundation they built and using advanced capabilities to support content development and refinement. The goal is to consistently scale the maintenance work that often falls on a small group of people and is done reactively.
Titter describes the direction this way. “As AI capabilities mature, we envision an AI agent working alongside our portal content manager to monitor usage trends, flag outdated or duplicate content, and identify gaps based on unanswered employee questions.”
For health system HR leaders, the takeaway is that automated workflows are rising quickly, but success depends on the unglamorous work. Build a foundation worth automating, put governance behind it, and earn employee trust one consistent answer at a time.