HRTech Interview with Kelli Rico, Chief Product Officer, isolved
Kelli Rico, Chief Product Officer, isolved chats about the benefits of embedding an AI layer to global payroll processing workflows in this catch up with HRTech Series:
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Hi Kelli, what’s the most exciting aspect of being part of the HRTech ecosystem today?
I have enjoyed seeing the evolution of technology that actually makes someone’s job easier. Everyone’s focused on AI right now, but I don’t think success is about being first to market or being able to say you have AI everywhere in your platform. If you can’t quickly answer how your AI system is improving your work experience or alleviating previous pain points, what’s the point of implementing it at all?
What excites me most is the combination of humans and AI working together. With AI involved, my team can move away from repetitive admin tasks to the strategic work where human judgment and perspective really matter. That doesn’t mean I don’t believe functions like timekeeping, payroll, and onboarding aren’t important. They absolutely are. Tasks like these are so important that sometimes AI can make them even stronger by helping catch errors that humans often miss. We’re already seeing how quickly the industry is moving in that direction. In fact, isolved found that 69% of HR leaders say their teams are leveraging AI today, with payroll and recruitment among the top use cases.
Briefly take us through isolved’s latest AI agent (The Guardian) and how the feature is useful to the tool’s end users?
The Guardian is isolved’s first autonomous AI agent that was built to help HR teams manage payroll functions more proactively and accurately. Instead of a software tool that simply flags an issue for an administrator to investigate, The Guardian acts as a teammate that analyzes every payroll run before close, identifies and ranks potential errors, and helps move those issues toward resolution without requiring a human to intervene.
The Guardian also learns an organization’s normal payroll patterns over time, so that it can distinguish between actual anomalies and normal behavior. This includes things like seasonal hiring, overtime, recurring bonuses, and shift premiums. Because every organization is at a different pace on its AI adoption journey, customers can establish guardrails and determine the autonomy level that they’re comfortable with. As their confidence grows, they can allow The Guardian to take over more responsibilities.
What are some of the common global payroll processing problems that finance and payroll teams often struggle with?
Payroll is one of the most critical and highly complex processes in an organization, but it can also be highly manual, time-consuming, and prone to error. Payroll teams are managing enormous volumes of data across employees, and at that scale, even experienced professionals can struggle to catch every anomaly before payroll closes.
A few common errors include missing direct deposit information, overtime rate miscalculations, incorrect tax withholding, multi-state reciprocity mismatch, and missed minimum wage updates. Even a one-character typo in an employee’s bank account or routing number can mean they won’t receive their paycheck at all. Another example would be for individuals who live in one state and work in another, and reciprocity rules aren’t applied correctly. If they’re taxed in both states, they will have more withheld from their paycheck than they should.
Receiving an accurate and on-time paycheck is one of the most important ways employers build trust with their employees, and when that trust is broken, employees aren’t afraid to pick up and leave. Our research found that 63% of employees have experienced a payroll issue, and 53% say they would look for a new job after encountering one.
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How is AI enabling solutions in this area?
Embedding AI into payroll processes has multiple benefits, especially the ability to move payroll teams from reacting to errors to proactively identifying and resolving errors on behalf of payroll teams.
The challenge is that while many areas of HR have been significantly modernized, payroll has been left behind. That’s where AI can be incredibly valuable. Payroll specialists need technology that can analyze information at scale and proactively identify issues such as tax-jurisdiction errors, overtime inconsistencies, missed deductions, and unusual pay patterns.
This allows HR teams to move away from the tedious, data-intensive work and redirect their focus to workforce planning, developing talent, improving the employee experience, and helping your business navigate change.
AI can identify persistent problems, not just one-off mistakes. For example, if the same employee repeatedly receives incorrect paychecks that are missing overtime hours, AI can recognize that pattern across multiple payroll runs and flag the issue to the broader team to investigate. It gives payroll teams greater visibility into issues that might otherwise become normalized or overlooked.
Ultimately, AI gives payroll teams more confidence in the accuracy of each payroll run and ensures that employees are consistently paid accurately and on time.
For teams reviewing how new age AI powered HRtech and payroll systems can benefit them, what best practices should they follow when adopting these technologies?
Not every organization is ready to adopt AI as quickly as another, and that’s okay. Each organization has different needs, workflows, and pain points. Simply adding more technology into the mix isn’t going to fix the problem if you haven’t identified the problem in the first place. Start by looking at where your teams are spending significant time on administrative or repetitive tasks. Maybe there’s a consistent pattern of correcting payroll errors or manually entering information that AI can easily step in to take over.
Second, communicate with each other. If a tool isn’t improving the experience for one department, it might create significant value for another. Test the technology in your everyday work, ask teams what’s working and what isn’t, and be willing to make adjustments before rolling it out more broadly. Think about your personal life: would you ever buy a car without test driving it first? Most people would say no. Organizations should take a similar approach with AI.
Lastly, go beyond treating AI adoption as another onboarding module. Don’t expect your employees to understand how to use it. Humans are naturally curious people and often don’t like change, so it’s important to explain how to use the technology and what it means for their own role. If AI takes a task off someone’s plate, help them understand what they now have more time to accomplish. Adoption becomes much easier when employees see the technology as something that enables them rather than something happening to them.
How do you feel the HR Tech ecosystem will shift in the future as AI redefines the landscape?
AI is changing how we do everything. That means HR needs to change how they define “qualified.” In a market that demands adaptability and team collaboration, organizations that are still hiring those who check off a static list of qualifications are already behind. I’ve seen that in my own career. I haven’t followed the traditional, linear path. In fact, it’s been the opposite. I’ve had the opportunity to move across roles like university and training manager to leading product management, not because I had the perfect background for every opportunity, but because I was trusted to learn, adapt, and grow into new challenges.
That same mindset should shape how companies hire in an AI-driven workplace. If I’m interviewing a candidate who might not meet every traditional qualification but is curious, willing to learn, and eager to get started, I’d choose that potential over a perfect resume without the same passion. Technical skills can be taught and developed on the job. It’s qualities like coachability, resilience, collaboration, and the ability to elevate a team are much harder to teach later on. And in an AI-shaped workplace where hard skills evolve very quickly, those human traits are becoming the real differentiator.
A few thoughts on the future scope of the typical HR department in light of HRTech revising the evolution of these roles?
I’ve been in the industry for over a decade, and throughout that time there has always been a prediction that the next wave of technology will eliminate HR jobs. What we’re seeing with agentic AI, however, is the potential to expand our roles and make them more important than ever.
Organizations will increasingly need to treat their AI agents like workers, not software. When this occurs, HR will begin working alongside IT to redesign a way of working where humans and agents work in tandem. Like employees, agents need clearly defined roles, onboarding, oversight, and training to do their jobs effectively. Organizations need visibility into agent ownership, outcomes, and costs alongside traditional workforce data.
Rather than creating an entirely new function to manage the emerging agentic workforce, HR is well positioned to set expectations, establish accountability, manage performance and support agents throughout their lifecycle, from onboarding to offboarding. So, while I don’t believe HR is going away, I do think what people traditionally picture when they hear “HR” is about to change dramatically, and I’m excited for what’s to come.
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[To share your insights with us, please write to psen@itechseries.com ]
isolved is a Workforce Capital Management company that combines human workers and AI agents on a single lifecycle management system.
Kelli Rico, is Chief Product Officer, isolved
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