There are conferences you attend for the sessions, and there are conferences you attend for the community. The Women's Leadership Council virtual event, hosted by Channel Focus, is one of the rare ones that manages to be both.

I want to start with the community part, because it's the thing that doesn't fit inside a screenshot.

Thirteen years ago, when the WLC was founded, roughly a quarter of the attendees at Channel Focus were women, and fewer than one in ten speakers were. By 2022, half the speakers on stage were women. That kind of change does not happen by accident. It happens because a small group of people (Rod Baptie, Theresa Caragol, and a growing chorus of leaders who followed) decided to build something and keep building it.

I was especially glad to see Meg Brennan step in as the new chair, and to catch Joanna Hauck on the panels. Both are former bosses of mine, and both are people whose fingerprints are on more of this industry than most people realize. Watching them lead conversations at an event like this is the kind of full-circle moment that reminds you why you stay in the channel.

Now to what I actually took away.

The Question That Kept Coming Back

The opening frame for the day was simple. As AI becomes more capable, what becomes more valuable about being human?

That question is what I keep returning to a day later. Because the honest answer, based on everything I heard, is that the human parts of channel work are not receding into the background. They are moving toward the center.

What Real Practitioners Are Actually Doing With AI

I've been in a lot of AI panels this year. Most of them stay abstract. This one did not.

People are using AI to interview themselves in their cars before high-stakes conversations, prompting the model to interrupt them when they start rambling and help them find a cleaner answer. People are using it to synthesize twenty-seven-slide decks down to ten. People are training their tools on their own writing so their weekly team updates sound like them, not like a chatbot in a hurry.

And people were honest about the limits. "Hallucination" came up more than once. So did "garbage in, garbage out." The strongest line I heard on data readiness was simply this: AI is not magic. If your underlying data infrastructure is a mess, no tool is going to fix it for you.

I also appreciated how skeptical the room was of the "AI is why we had to cut roles" narrative. The more common view was that AI is often being used as convenient cover for decisions that were already being made. Most organizations, even sophisticated ones, are still in the early innings of figuring out where AI actually creates leverage.

What This Looks Like for Me

The event pushed me to actually name my own practice out loud, so here it is.

The heaviest lift AI takes off my plate is analysis and competitive comparison. When I need to understand how another vendor structures their program, or how five companies are approaching the same category, I can get to a working comparison in an afternoon instead of a week. That does not mean the output is finished. It means the raw synthesis is done, and I can spend my time on the judgment layer, which is where the actual value lives.

Deck creation and talk track drafts are the second big one. I do not use AI to produce the final version of anything I present. Starting from a rough draft that already has a structure and a first pass at the language is a completely different lift than starting from a blank slide.

The third is the least glamorous and honestly the highest leverage. I have been writing small Apps Scripts and lightweight web apps to make my day-to-day tools work together the way I actually need them to. Getting one Google Sheet to talk to another. Building a small internal app that turns a repetitive workflow into a button click. Pulling data out of one system in a format I can use somewhere else. None of it is production engineering. All of it saves hours.

The most important use, though, is not tactical. In my current role I own partner experience, which means the question I sit down with every morning is the same one. How can we make the experience better today, not just for our company, but for the partners who work with us? AI has become the tool I think through that question with. It helps me pressure-test a program change before I ship it. It helps me see a decision from the partner side, not just from the vendor side. It helps me stress-test assumptions that would otherwise get baked into a program update that lands with every partner at once. That is not productivity. That is strategic decision-making.

The thread across all of these is what the panels kept coming back to. AI is not doing my thinking for me. It is compressing the distance between an idea and an action, and pushing me to think harder about the decisions that matter most.

New Roles, Not Fewer Roles

Something that surprised me, in a good way, was how much of the day focused on the roles emerging rather than the ones disappearing.

Partner experience managers. Prompt engineers on partner portal teams. Content engineers. AI strategists at the organizational level. Digital experience teams replacing what used to be called "the portal team." Enablement pivots where tech writers become on-demand training designers.

The pattern is consistent. The mundane, repetitive work is going to software. The higher-order thinking (the judgment, the synthesis, the design of the actual experience) is becoming the job.

The Invisible Workload

The session I think I'll be quoting back to friends the longest was the one on personal AI use cases. Not because the tools were novel, but because the framing was.

The pitch was simple. Women in this room are already carrying an invisible workload. Family schedules, meal planning, aging parents, PTA receipts, vacation planning, the mental load nobody sees and everybody expects. The point of AI in your personal life is not to get more done. It's to reclaim time to reinvest in things you care about.

The example that made me laugh out loud was a PTA president friend with a year of receipts sitting in a box. Take screenshots. Upload to your favorite tool. Ask it to build the spreadsheet. Get it off your list.

The reframe of AI as the tool that gives women their evenings back is going to age better than most of what gets said about AI at work.

Human Skills Are the Differentiator

The through line across every panel was that the so-called soft skills are becoming the actual differentiators. Empathy. Discernment. Reading a room. Asking better questions. Building relationships that hold when the systems fail.

One of the sharper reframes came in the leadership discussion. The old model of leadership was having the answer first. The new model is knowing which question to ask. AI is very good at generating answers. It is much less good at knowing which question deserves the answer in the first place.

Vulnerability as a Tool, Not a Weakness

The final session was on obstacles and resilience, and it was the one that grounded the day. A long career in this industry means eventually being on the wrong end of a layoff, a reorg, a rumor you didn't start, or a moment where you have to rebuild your confidence one small win at a time.

Two things from that panel I'll carry.

The first was the idea of a personal board of directors. Not mentors in a formal program sense. A specific set of people you can go to with the messy stuff, the strategic stuff, the "I think I really messed this up" stuff. Different people for different questions. And the discipline of maintaining those relationships before you need them.

The second was permission to normalize therapy and coaching as part of professional development, not as evidence that something is wrong. Sometimes small wins rebuild confidence. Sometimes a bigger investment does the same work. Going back for the MBA. Earning a new certification you can carry with you into the next role, whether that is an AI credential, a leadership program, or a technical qualification. And a really important reminder that personal accomplishments outside of work count just as much. A yoga class you actually keep going to. Training a puppy. Learning to bake bread. Picking up something with your hands that has nothing to do with your career. All of it does real work on your mental health and your confidence, and the professional pieces travel with you into whatever comes next.

What I'm Taking Back

I walked away with three things.

A reminder that the AI conversation in our industry is more sophisticated when it's grounded in real practitioner examples than when it's driven by keynote hype. That was the whole tone of this event.

A reminder that the human skills, the ones that get called "soft," are the ones that become non-negotiable when the technology takes more of the execution off our plates.

And a reminder that the community that shows up for events like this one is the actual asset. The frameworks are useful. The prompts are useful. The list of people you can call when the hard week comes is what makes any of it work.

Grateful for the day. Grateful for the WLC. And especially grateful to see two of my former bosses speaking at a wonderful women's event, where we're thinking forward in the AI era and remembering to support each other through whatever comes next in this industry.

Have thoughts on this? Connect with me on LinkedIn.