Christina Garvey

A Career Built on Referrals

The first turning point came in 2012, when Garvey was still working out how to move from retail leadership into talent. Through a networking group in Austin she met a man who owed her nothing and gave her his time anyway. He walked her through what the recruiting world actually looked like in Austin, what the different paths inside recruiting were, what to look for, and how to position her brand on LinkedIn. Then he went back to his life, and she went back to hers.

Four years later, he called. An opportunity had opened where he worked, and he wanted to refer her. Send me your resume, he said. That referral became her first corporate role in recruiting, a global position with McDonald's through Randstad Sourceright, and it reset the trajectory of her career. "That person saw potential and took a chance," she says. The postscript is the kind of detail no one plans: he is now her partner of almost five years.

Her second mentor is the leader who hired her into that global role, a prior leader at Visa who took one look at how varied her background was and decided he wanted her on his team. Others in the process pushed back. She did not have the years, they said, or the specific experience, or the conventional background. He argued the transferable competencies instead, line by line, and she got the offer. That same leader later recruited her to Fastly and handed her the chance to build a program from the ground up. Two people, one lesson she now carries into her own hiring: the candidate in front of you is worth more than the checklist beside them.

Turning Down the Noise

Garvey was both a speaker and an attendee at the URX conference a few weeks before this profile, where artificial intelligence dominated the agenda across every corner of early careers: industry peers, campus partners, programs, and systems. The group's ambition, as she describes it, was to turn down the noise and get honest about what everyone was actually seeing.

What they were seeing, she says, was misinformation traveling in every direction at once. Nobody is quite sure how candidates are using AI, or how they will be expected to use it at the company they are applying to. Campus tells students one thing. Students tell employers another. Employers tell students something else again. Her answer is unglamorous and effective: set realistic expectations up front, talk openly with applicants about how the company uses AI and how it wants them to use it, and treat the conversation as mutual learning rather than enforcement.

The same fragmentation shows up inside organizations. Individual recruiters build their own AI workflows and their own private processes, while the rest of the business builds something entirely different. Garvey's focus is consistency: a genuine, shared understanding of how a team and a business can use these tools effectively. As she puts it, the goal is getting everybody onto the same AI playing field.

An AI-Forward Mindset

Her advice to other talent leaders is the advice she is currently giving herself. Have an AI-forward mindset, not a restrictive one. Stay open to what working with AI can do for workflows, processes, and efficiency, and not only in your own work but across your team, in how you partner with the business, and in how you meet the candidate.

"Just being open is like the number one advice," she says. It is a notably generous position from someone whose career has been built on human judgment, and it is consistent with everything else about her. Garvey is a leader who has been on the receiving end of open minds twice, from a stranger at a networking group who gave her an hour, and from a hiring leader who defended her potential in a room full of people counting years of experience. She has spent the decade since paying it forward, in early careers programs, in a leaders group chat crowded with peers she is quick to champion, and in an annual URX gathering she recommends to anyone in the field. Her career is the argument for her method: talent is a network, and networks are built by people who make time.