“Great news, Joseph, you qualify for one of our programs. We’re going to transfer you now. Thanks, and have a great day.”
Jourdan Hathaway is playing the voice agent for me, the way she once heard it through a pair of headphones in a room full of colleagues who had been listening to calls for hours. Then she stops and asks the question the room eventually asked itself. “What do you do when you hear thanks and have a great day?”
Hang up.
The agent sits at the front of an admissions contact center. It qualifies a prospective student, then hands the call to a live specialist. Getting it there took the better part of three quarters: the business case, the build, the unglamorous change management that decides whether an AI initiative works at all. It dialed. It connected. It asked the right questions in the right order, and people answered them.
Then came the number nobody wanted to see. The warm-transfer rate, the metric that mattered most because it is the start of the revenue funnel, was well below the benchmark. Every instinct on the team said technology or data. “If I were only looking at the dashboards, the dashboards would tell a story of it being non-performant,” Hathaway says. So they formed a tiger team and listened to the calls.
“If nobody did the human thing of discernment, we would all be looking at each other and say, It failed. AI is broken.”
It took, in her telling, about thirty seconds. After qualifying a caller, the agent said the polite thing. To the software, the sign-off was a few seconds of scaffolding while the handoff processed. To the human on the line, it was what decades of phone etiquette had trained every one of us to hear: goodbye. Not a compliance failure, not bad data, not governance. “It was literally just Psychology 101.” The fix was one line: we’re transferring you now, please hang on.
Hathaway, the company’s Chief Business Officer, is not entirely comfortable telling this story. She tells it anyway: “If we are too afraid to talk about some experiences that we have during AI transformation, then failures happen under the radar.” She also can’t let go of the irony. “One day I can’t wait to do a presentation on what an ill-timed thank-you taught me about AI transformation.”
The part she loves is who found it. A contact-center manager with no technical AI background heard it in a second, because coaching calls was already the job. That person went on to coach the agent instead, an emerging role Hathaway calls digital agent workflow manager. Her rule, in four words: “I observe before I prescribe.”
She has reason to trust that rule. General Assembly has spent the past two years transforming to meet the moment: consumer operations ceased, and the organization reinvented itself around AI skills training for teams, enterprises, and governments. Roles changed with it. “Every employee needs to provide value,” she says, and when the ground moves under a role there are two choices. “You either take your ball and go home or you reinvent yourself.”
She learned to say the hard parts out loud the hard way. After a career in marketing, “one day I found myself the COO,” and the title did not come with the language. “I did not wake up and go, oh, now I speak EBITDA, CapEx, OpEx.” So she wrote herself a plan called Project FLAT, for financial literacy, and published it as she went — the botched meeting, the investment case that didn’t land. Now she does it for other people. The plan with the failures in it, she says, “has done more help to my mentoring than any of the polished blogs or polished speeches that I used to give.” The mentoring is not all business, either. The question she asks most often is the one she had to learn to ask herself: what’s fun to you?
Which brings us to the hour. Before a single email, before a single Slack message, she now spends the first hour of the day on herself.
“Untethered from accomplishments, achievements, who I think I’m supposed to become.”
She spent decades climbing, “looking for that next success ring,” wearing what she calls the veneer of a professional until she felt she had made it. Then the AI narrative began dragging everyone she knows through “this grief arc and fear arc,” and she noticed it “doesn’t really do me on an individual basis on a Tuesday morning any good.” So she drew the line where she could hold it: “Just for Jourdan on a Tuesday morning, what does it take for me to feel satiated and a sense of purpose and a sense of joy — because maybe that’s the part that I can control.”
In practice, that means a botanical garden and tai chi she is genuinely bad at. Being good at it is not the point. “I have solved some really thorny business problems when I’m out in a botanical garden trying tai chi that I’m terrible at.”
The fear underneath isn’t about robots. “I’ve never truly escaped fully what it means to grow up in poverty. You always have this feeling that you can’t take your eye off the ball, because at any point in time you might go backwards.” That, she says, is the real reason for the hour — “to let go of the scarcity mindset.”
At the end she gave me homework. Try something new in my own town, something out of the norm, and report back: either why did I do that, or that’s pretty freaking cool. Either way, she’ll want the specific. She always does.