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- UCI HR uses generative AI to streamline routine tasks, freeing staff for strategic work while respecting higher ed’s unique culture and values.
- Adoption is cautious, with careful tool selection, training, and ethical oversight to prevent bias and maintain trust in AI use.
- AI aims to help UCI manage growth and budget pressures by boosting efficiency without expanding headcount, supporting a strategic HR future.
At the University of California, Irvine, the Human Resources office sits at the intersection of tradition and transformation. Ramona Agrela, Vice President, UCI Health, and Vice Chancellor, Human Resources, UC Irvine, is steering the HR team that supports this 34,000-employee institution through the early phases of generative AI (Gen AI) adoption with both pragmatism and hope.
As she reflects on UC Irvine HR’s (UCI HR) journey in her interview with me, a clear picture emerges of how higher education’s distinct culture, constraints, and commitments are shaping its path forward.
Balancing Innovation With Infrastructure
Unlike nimble tech startups or resource-rich corporations, universities operate in layered bureaucracies. At UCI, this complexity is amplified by its unique structure: a main academic campus, a College of Health Sciences, and the sprawling UCI Health clinical enterprise.
While many organizations are sprinting ahead with AI adoption, higher education often has to walk before it can run.
Agrela describes UCI HR’s Gen AI initiative as being in its foundational stage, focused on improving operational efficiency.
“It’s a lot of looking at self-service functions,” she explains. “How to take the mundane tasks — those routine, repetitive ones — and use Gen AI to support them, freeing up time and energy for more strategic HR work.”
These ambitions are measured not by traditional AI success metrics, but by UCI HR’s own “North Star” framework: employee engagement, talent destination positioning, and process effectiveness.
Rather than viewing AI as an isolated project, it is woven into the university’s broader goals. If AI helps move the needle on these benchmarks, it’s considered a success.
Time and Training: The True Costs of AI
Despite the promise, Agrela is clear-eyed about the hurdles.
Chief among them is time, which is an increasingly scarce commodity in a post-merger HR landscape now responsible for an additional 4,200 employees.
“You don’t want to just throw in a tool and hope that it’s working,” she says. “It takes training, patience, and knowledge, and that’s a tough ask when everyone is already stretched thin.”
This perspective highlights a critical distinction between higher education and private sector AI adoption: the speed of execution. At UCI, just choosing the right tool is a slow, deliberative process, involving not only usability evaluations but cultural and strategic alignment assessments.
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For Agrela, deploying Gen AI is akin to onboarding a new employee; it must be oriented, trained, and integrated into the team. That metaphor, offered by a colleague, speaks volumes about the human-centric ethos of academic institutions.
Cost is another constraint. While some existing HR systems include AI functionalities as bolt-ons, budgetary limits often restrict experimentation with newer, standalone tools.
As Agrela notes, “A lot of the things we just don’t have a budget for.”
Cultural Resistance and Ethical Guardrails
Resistance to Gen AI is logistical as well as cultural. In higher education, where faculty and staff value personal connection and intellectual rigor, the notion of outsourcing interactions to a machine often sparks discomfort.
“People are used to picking up a phone and calling a person,” Agrela observes. “Talking to a computer isn’t something our long-term employees are necessarily comfortable with.”
This cautious approach extends to applicant screening, where AI tools capable of parsing resumes have been intentionally sidelined.
“We’re not using AI in applicant screening right now because we haven’t had the time to ensure it won’t cause some form of discrimination,” she says.
That decision speaks to a deeper concern about fairness, bias, and trust — issues that loom especially large in academic settings where equity is a guiding principle.
To navigate these ethical waters, UCI leans on a multi-tiered governance structure. A compliance and privacy committee vets every new technology to ensure it meets legal and institutional standards. A separate data governance committee ensures that AI tools integrate responsibly with existing systems.
While some universities might form a single AI oversight body, UCI’s segmented approach reflects its caution and commitment to layered accountability.
Shifting From Transactional to Strategic
Despite the early stage of adoption and the many hurdles ahead, Agrela is optimistic about Gen AI’s long-term impact. Her vision is not just about doing more with less, but about elevating the role of HR professionals.
“I envision my teams becoming smaller over time,” she says. “AI can take over the transactional work — writing memos, processing leave paperwork, managing routine correspondence — so we can focus on workforce planning, employee development, and organizational strategy.”
In this way, Gen AI is not a threat but a tool for resilience. With universities like UCI facing ongoing financial pressures, AI offers a path to maintain service levels without expanding headcount. But this transformation will only be successful if handled thoughtfully.
“You need deep, helpful thought partners to do this work,” Agrela insists.
And if AI can help free up those human minds to think more deeply and act more strategically, then it will have truly earned its place on campus.
A Measured, Mission-Driven Evolution
UCI HR’s approach to Gen AI adoption is not one of explosive innovation, but of careful evolution. It’s a case study in how large, complex, and values-driven organizations can begin to integrate new technologies without losing sight of their mission.
In higher education, change is often incremental and always contextual. Gen AI, for all its power, must adapt to that reality.
As Agrela puts it, “Higher ed is a unique animal.” In this ecosystem, the success of Gen AI won’t be measured by how fast it spreads, but by how well it supports the people and principles that define the institution. And in that respect, UCI is setting a thoughtful, responsible pace for others to follow.
