Avalara's Ee Lyn Khoo isn't just leading AI transformation. She's living it inside her own function
Every morning, Ee Lyn Khoo wakes up with a sense of urgency. Not because things are going badly at Avalara, where she has served as Chief People Officer since 2022, but because she knows how fast AI is moving, and she has made it her personal mission not to let her function fall short of the pace.
“Every day I wake up asking myself: ‘Am I doing everything in my power to make my function more effective by 50%?’” she said. “That’s my north star.”
For many HR leaders, AI transformation is something they’re managing for the rest of the business. For Khoo, it starts at home.
Building an AI-native HR function
Khoo joined Avalara after 13 years at Amazon, where she rose to VP of Human Resources before becoming CPO at Redfin. Her mandate when she arrived at Avalara was to “muscle up” the people function: sharpen hiring standards, codify processes, and build a culture anchored in impact rather than good intentions. What she didn’t anticipate was how quickly AI would become the accelerant for all of it.
“I joke that Claude is my BFF at work,” she said. “It’s been such an amplifier. But it goes back again to judgment. I cannot blindly assume Claude knows everything there is to know about the context of the problem we’re solving. It requires me to be smarter and sharper in terms of talking to Claude so that Claude can help me do my job better.”
READ MORE: Why HR must lead AI adoption to make technology actually work
Khoo isn’t describing a tool she relies on passively; she’s describing a working relationship that demands more from her, not less, where the quality of the output depends entirely on the quality of the thinking she brings to the prompt.
And it’s an approach she’s applying across every part of her team.
Today, Avalara’s HR function is being rebuilt around AI from the ground up; goal setting, hiring, performance management, and employee support have all been redesigned with AI at the centre.
One of the clearest examples is goal setting. Avalara has embedded AI directly into its internal goal-setting process, where it checks whether each employee’s goals are well-written, clear, deadline-driven, and tied to a clear owner, while also suggesting AI-related goals based on prompts from the employee. The results have been striking.
“The high-quality goals have gone up from something like 50% to like 95%,” Khoo said. “And about 92% of our employees have at least one well-written AI goal.”
Every employee at Avalara is now required to have at least one goal tied to their use of AI, and not a goal about learning AI in the abstract, but a concrete goal about using it to improve a specific part of their job. She gives the example of a customer service employee using AI to improve their quality scores.
“It’s really about using AI to make some part of their job better,” she said.
When AI answers the door
The changes inside Khoo’s own team are just as significant. Avalara recently launched what it calls Grove Central, a digital front door that centralizes employee queries into a single AI-powered interface. Before it existed, employees navigating HR questions could end up in four or five different places, with most simply messaging someone they trusted on Slack to find an answer.
“How frustrating for the employee. How inefficient for us,” Khoo said. “So, we created this digital front door with an agent. Everything is centralized.”
The Grove Central agent handles discoverability, surfaces documents, and helps employees interpret what those documents mean in the context of their specific question. Complex tickets still get escalated to a human, but the volume of routine queries is already falling.
“We exist so that employees have a frustration-free experience so that they can focus on solving problems for the customer and for the business,” she said.
Hiring for the AI era
Perhaps the most ambitious initiative underway is what Khoo calls the AI Persona, a minimum bar for AI proficiency that Avalara is embedding into every stage of the hiring process. Managers are given role-specific interview questions, guidance on what strong and weak answers look like, and case studies designed to pressure-test how candidates think through problems in an AI-first environment.
“We want candidates to demonstrate a certain number of behaviors or tendencies during the interview process for us to actually hire them,” she said.
And it doesn’t stop there. More broadly, Avalara is working to embed AI proficiency expectations into performance ratings, promotion criteria, and development plans, with the aim of weaving them into the full arc of an employee’s career at the company.
READ MORE: AI to transform HR into strategic function, says Gartner
Khoo’s reasoning is grounded in a specific thesis about how AI is changing the talent equation: the technical floor, she argues, has risen, making skills more accessible to more people, but the ceiling is now determined by something harder to automate.
“The ceiling now is determined by judgment and curiosity and how well somebody can bounce back after the first attempt,” she said. “Our interview process has to get at the judgment and the curiosity and the resilience.”
Managing anxiety with the three C’s
Not everyone finds this pace comfortable, and Khoo is candid about the challenge. Headlines about companies eliminating entire HR teams or replacing functions wholesale with AI create real anxiety, and she knows it.
“Chatter like that feeds angst. People worry about ‘What does this mean to me, am I losing my job?’ That is the biggest challenge,” she said.
Her response is built around what she calls the three C’s: context, connection, and confidence.
Context means communicating openly and repeatedly about what Avalara is doing with AI and why; connection means naming the anxiety directly so people feel heard, creating learning pods, celebrating failures alongside wins, and keeping human touchpoints, like the company’s leader-led onboarding program, firmly in place. Confidence, meanwhile, means giving employees access to tools, training, and coaching, and being honest with them about the career value of building AI skills.
“We’ve been very open with employees about, gosh, listen, if I were you, I would really learn as much as I can about AI and show you can make an impact, because it is a resume booster whether you stay at Avalara or not,” she said.
She also pushes back on the assumption that employee questions about AI signal resistance. More often, she argues, they signal something quite different.
“A lot of the time their questions or their concerns is coming from a place of fear. They want to do a good job, but they don’t know how. And it’s their way of asking for help.”
Start before you’re ready
Her advice to HR leaders still finding their footing is straightforward: don’t wait for the perfect plan.
“Take the first step and the next step and the next step,” she said. “They don’t all have to be big steps. I’ve learned that over time these small steps actually snowball. And suddenly you’re looking back and it looks completely different.”
She also cautions against leading with the tool. “Start with what is the process you want, or the workflow you want, or the desired employee experience. Work backwards. And then figure out the best way to get there.”
It’s a discipline that has kept Avalara’s AI rollout both grounded and fast-moving, and for Khoo, who measures herself every morning against a 50% effectiveness target, fast is the only speed that makes sense right now.
