A Plan Is Not an AI Strategy: Smart Cookies with Julie Averill
At our September Smart Cookies live panel in Seattle, we explored a pressing challenge: AI ambition is outrunning execution. Leaders from Tableau, PitchBook, the Gates Foundation, and Nordstrom shared what it really takes to move AI from promise to practice.
In this episode, we continue that conversation with Julie Averill, former CIO of Lululemon and author of Chief Impact Officer. Drawing on decades of leading technology transformation, Julie challenges the idea of “AI wishing” and explores why strategy, culture, trust, and the people closest to the work are essential to turning AI ambition into real business impact.
Key Takeaways
- AI wishing is not an implementation strategy. You cannot wave a magic wand, sprinkle pixie dust, and skip the hard work of putting AI into practice. Enthusiasm alone does not create results.
- A plan drives efficiency. A strategy creates new opportunities. Improving existing operations is valuable, but real AI transformation means asking what your business can do today that was never possible before.
- A great demo is not the same as enterprise readiness. Demos can work beautifully on clean data. Real enterprises often operate across disparate systems that handle data differently. Making that data usable is still hard work.
- Culture is not a soft topic. It makes innovation possible. The teams closest to the business often see opportunities leadership cannot. But those ideas only emerge when people have the freedom to experiment, speak honestly, and fail without punishment.
- Honesty builds trust faster than any pitch. Founders do not need to pretend their products are enterprise grade before they are. Being transparent about limitations creates the foundation for stronger partnerships.
- Technology has accelerated. People have not. AI may move faster than previous technology waves, but transformation still depends on earning trust, changing how people work, and bringing teams along on the journey.
If you’re working through these decisions in your organization, we’d be glad to continue the conversation with you. Connect with KG Digital
Full transcript
Bryon: Well, welcome to Smart Cookies, Julie. For our listeners, I’m Bryon Scharenberg, and I’m sitting down with Julie Averill today. A quick introduction: Julie, you’ve spent the last 30 years bringing new technology into organizations. Eight of those years you were the CIO at Lululemon, with time at Nordstrom and REI along the way, here in the greater Seattle area.
This summer, many of you may have read the guest essay Julie wrote for The New York Times telling companies to stop kidding themselves about AI. It has traveled well beyond the tech world and picked up a lot of steam. We’ll talk about that today.
A lot of your professional time now, Julie, you spend advising leaders and boards, and most recently you published a book called Chief Impact Officer, which I’ve been reading and find very interesting. One of the things that stuck with me is how you talk about your parents: your dad Earl, and how he built trust with people, and your mom Pat, who inspired the name of your current advisory company. Gold Thread was a bit of a nod to her being a seamstress. Is that right?
Julie: Right. It’s called Gold Thread, so it’s really… I got it ’cause there’s threads on the thread of a baseball. My mom was a seamstress, so really a nod to both of them.
Bryon: Love that. Along with your professional career, you also document your personal life throughout the book: you and your wife Cindy, and your three kids along the way, and how that has intertwined with your professional journey. I’m very thankful you’re here today, Julie, and excited to learn from your experience. So thank you for being here.
Julie: Yeah, happy to be here, Bryon.
Bryon: One of the things I love asking guests on our show is thinking back to when you were a kid and thought about your future. What did you wanna be when you grew up?
Julie: The only thing I can remember is that I wanted to be president. It was mostly because there had never been a girl president, and I didn’t understand why. That was kind of the childhood goal. But then as I got a little older, I really got into computers: early, early days. But I still never… Even when I went to college and got a degree in computer science, I didn’t think it was for my career. I just loved computers, but I had no female role models that I could see who had great careers in technology. So it was just my destiny. I knew it was my destiny, but I wasn’t sure how it was all gonna work out.
Bryon: I heard you say recently your dad, who had a number of years as a professional baseball player, was a catcher, very interesting to learn about, and later went on to work for RadioShack. You talked about how he brought home a TRS-80, and you kind of became an expert at it. And as a late teenager you started doing some training on Lotus 1-2-3. I’m curious: you said it wasn’t where you thought your career was gonna go, you just enjoyed technology. Is there anything you learned during those early years of wonder with technology that you still carry forward today?
Julie: Yeah. A couple things come to mind. My dad had a small consulting business and he was always absorbing the latest rounds of tech: started with TRS-80s, then evolved into desktop computing. He would sell computers to local businesses, and I would go in and help them learn how to use them. Before Word, it was WordPerfect. Before Excel, it was Lotus 1-2-3. What I took away from that was really that I had to understand the business before I knew how to help them use the technology. That stuck with me throughout my career: start with the problem you’re trying to solve before finding the right technology to put into place.
And then the other thing was just grit and hustle. From an early age I took that job. I pitched myself as an expert in Lotus 1-2-3 at probably 17 years old, got a job at a training center, and started doing classroom training to local teams. Yeah, just grit and hustle.
Bryon: I love that. Even as a dad to a teenage girl, I think about what a cool example that is: this 17-year-old brimming with confidence, going into a business and saying, “Help me understand your challenges and I’m gonna train you on these tools.”
Julie: Yeah, I don’t know if it was confidence. It was all scary. But I think I get this from my dad: I like to do hard things and push myself. If it’s uncomfortable for me, I’m probably gonna do it, ’cause I know that’s where I’m gonna grow, and it won’t be as uncomfortable the next time.
Bryon: Kudos to your dad for being willing to bring his teenage daughter into the family business and give her a shot. Was the op-ed you wrote for The New York Times a hard piece to write for you? Tell us a little bit about where that came from.
Julie: It started with the fact that I left Lululemon and I’m talking to all my CIO peers, and these common themes of frustration kept coming up: CIOs who had been in their jobs for long periods of time, being successful, and all of a sudden a new technology came in a different way. On November 22nd, 2023, when ChatGPT came to everyone’s mobile, all of a sudden everyone became an expert. My sister-in-law was able to take a picture of the inside of her refrigerator and ask what was for dinner. It solved problems that she never knew she had.
And everyone had ideas about how powerful this technology was. So there was a frenzy that started from every executive. The marketing executive was getting pitched by all these startups with platforms that were gonna transform marketing. Same thing in supply chain. And then boards heard about it too, and boards wanted an AI strategy. So these CIOs were sitting there thinking, “I don’t know what to do: just a week ago I was trying to get the business involved in technology, and now everyone’s an expert.”
That was really the impetus for the piece: trying to call out this hysteria, this AI wishing, this belief that you can wave the magic wand and sprinkle the pixie dust and skip the hard work of actually implementing AI. It took me about five months to write. I pitched The New York Times, and I have so much respect for them throughout this process and their high standards. There were many times where I thought, “I don’t think this is gonna get published. Maybe I should just pitch it to another magazine.” But we finally got to a place where I knew they were interested, and then they pushed every single sentence and challenged everything. It was an incredible process. I think I’m a better writer as a result of it. It was not an easy process, but I’m super proud of it. It got put in print, which was really cool. And yeah, it started a conversation.
Bryon: Love that. For those who don’t know, The New York Times is still a print newspaper: we’re so used to reading articles online. Why do you think it had such a reception? It really resonated with a lot of people. What do you think struck a chord, maybe even compared to what you expected the reaction to be?
Julie: I think it just said the thing out loud that everyone was thinking. Everyone was feeling it, and I put words to it. With that, people were able to take the conversation forward. I hear from so many people, “Thank you for saying the quiet part out loud. This is what I’ve been thinking. I’m gonna share this with my leadership. This is exactly what we needed to be able to talk about what’s happening in my company today.”
Bryon: Yeah. I think there was the point where you shared about how when ChatGPT was introduced, the board said to executives, “Hey, what’s our AI strategy?” And then the executive goes to their team with the same question, and it trickles down throughout the organization: everyone asking that question, and the result being a punch list of everybody’s ideas. Those early AI strategies were just, “Here’s what everyone is saying and this is what we need to do.” Sitting a couple of years removed from that, when somebody asks you what an AI strategy should really look like, where would you start with them?
Julie: I see it happening in two forms. One, there’s a huge draw to look at efficiencies, look at the bottom line, put it throughout operations, start small. The ones that are succeeding are starting small, solving a specific problem, and then growing from there. But to me, that’s not really a strategy: that is a plan. A strategy creates new opportunities. The real interesting conversations are those companies saying, “What can we do today that we’ve never been able to do? Where is there a lane we can get into before our competitors get there? How can we reach our customers differently? How can we redefine what our company does because of AI?” That’s harder because it requires operating in a very creative space, and for companies that have been successful for many years, the hardest thing is to reinvent yourself. But if I was gonna define an AI strategy, I challenge teams to think differently, get outside the box, and think about what might be possible.
Bryon: I’m curious why it seems like, and I think you’re right in that distinction, there’s a quote I wrote down from your book: “Leaders today are failing when they’re framing AI as an efficiency play when it’s actually a transformation play.” It’s about unlocking opportunity. But I’m curious why that’s still such an easy trap to fall into: just thinking about how AI can make what we’re already doing better, faster, cheaper.
Julie: Especially in the economy we’re in today, where top-line growth is hard and everyone is looking for efficiencies to support the strategies they have in place. There are some stats that differentiate companies’ efforts into different buckets. That top bucket, the companies really looking at transformation, represents about 5% of companies, and these are the ones seeing outsized returns. But it’s really difficult to get there because it requires a lot of things. One is the safety to fail. You’re not gonna get it right the first time. If this was easy and the road were already paved, we’d all be on it already. This requires invention and thinking, and to do that you gotta be able to say dumb ideas. You gotta be able to try things that haven’t been tried before, and not punish those who fail: you celebrate those who tried.
Bryon: A lot of what you write about in your book, and I’ll say honestly, Julie, I didn’t know when I picked it up that Chief Impact Officer would spend so much time on culture, which was a refreshing surprise. The freedom to fail, the freedom to offer new ideas: how have you seen this play out? A lot of our listeners are technology executives trying to answer how to roll out AI effectively. It’s easy to go straight to strategy, frameworks, planning, tools. And yet some of the things you talk about, like having the honesty to trust your team, are actually the foundation. How do you even begin to identify that it might be the culture that needs work first?
Julie: Yeah. This is my fundamental belief. I helped Lululemon grow from 2 billion to 10 billion over eight years, and so much of that was technology. The company strategy was highly dependent on the technology strategy, and I had to create a team that could move really fast in many directions at one time. I changed my beliefs about how I lead and what’s important through this experience. Innovation at scale does not come from the CEO and their direct reports defining what the rainbow looks like: it comes from the teams closest to the business saying, “Let’s try this.” They get excited, they come forward: “We tried this thing. It’s really exciting. We’d like to do it.” “Okay, here’s some money. Go figure the rest of it out.” And seeing that happen at scale, where you have a business leader and a technology team partnered together, someone deeply knowledgeable about finance, someone deeply knowledgeable about the customer experience in stores, about supply chain, about opening in new markets: those are the people able to say, “Here’s how we should do things differently.”
That is like a snowball effect. The success, the try without getting punished, is magnetic. I don’t know how to describe it, but I’ve seen it, and that’s why I believe culture is so important. If you’re prescriptive and you’re holding people back because they’re not able to express what they really think or be who they really are, you’re living in a constrained environment. Culture can free that. Culture can create a space where people can really bring all of their ideas forward and create incredible things.
Bryon: One of the words that’s coming to mind as I hear you say that, which I think is crucial within that culture, is honesty. I think this connects to the AI washing theme in your essay: pretending what AI is doing for us or the outcomes it’s driving rather than being truthful about the current state. That seems to be a theme for you in a few different ways, both in your professional journey and personally. One takeaway from that idea of honesty is actually quite a challenging one, particularly for founders with an AI startup or a company they’re bringing to market. I heard you say recently at an event that it’s okay to talk honestly about the gaps in your product or what you can’t yet do. That feels counterintuitive: why have you seen that be something worth championing?
Julie: I just give people credit for being smart. If you’re not taking the honest route: first of all, I’m super intuitive, so if somebody’s trying to hide something, I’m gonna sort it out. And I have much more respect for someone who will be honest with me, because that builds trust. With trust we can have a relationship, with a relationship we can have a partnership, and with a partnership we’re interested in mutual wins. But if I’m asking around something and I know there’s a hole in the product and they’re disguising it, there’s no trust. They’re acting suspicious. And I’m probably not gonna wanna do business with someone who doesn’t start from that foundation.
Sitting in a CIO seat, when you’re talking to a founder, you get it: this is a person with an idea who is working to bring something to market and may not have a ton of experience behind what that really looks like in a business. You know who you’re talking to. So for founders to try to pretend they’re enterprise grade is just not helpful to anyone.
And in my own life too: I’ve tried to live a life that I thought everyone wanted me to be instead of the person I really was. It was exhausting and limiting. I didn’t let people see my real self. I didn’t build the relationships that really mattered. Once I got over all of that, I just have clarity. In my role now, integrity and honesty are so important to me and the people I work with. I just don’t wanna spend time anywhere else.
Bryon: There’s wisdom in that both for us as individuals and professionally. Companies being honest about where their gaps are with AI, as well as what is still aspirational, builds trust with stakeholders and partners. And someone who is authentic is much more enjoyable to do business with than someone you need to call out on things.
Julie: Yeah. Yeah.
Bryon: I’d like to pivot to something you’ve mentioned: the idea that there’s nothing new about AI in the sense of the transformation work it requires compared to prior innovation cycles. Looking back at when cloud and the internet came around, what are some of the early lessons learned from those prior cycles that apply to AI today? And what’s maybe different?
Julie: I’ll start with what’s different. The speed. Technology used to be, as we said at REI, the long pole in the tent. An initiative would take nine months, a year, two or three years. That’s not what happens anymore. The speed has changed tremendously.
But where the speed has not changed is with people. People are still the hardest part of the job: understanding how they do their work, getting their trust to do a transformation, bringing people on the journey. All the things that have always been hard are maybe harder now because the technology is faster. And then the other part that’s still hard is data, especially in enterprises. It’s easy to show a demo that works quickly and perfectly on clean data, but enterprises aren’t sitting on clean data, especially in retail. There are myriad disparate systems that each manipulate their part of the data puzzle differently. Untangling that and understanding how to get the truth out of the data is still hard work.
Bryon: Are there other similar learnings from prior innovation cycles that would benefit us to pause and remember right now?
Julie: The omnichannel journey. I had the good fortune of being at Nordstrom when we were really inventing omnichannel. It seems so easy now when we look at it, but the thought of converting stores into fulfillment centers, opening the inventory in a store to the online shopper: that was novel, and we had no idea how it was gonna work.
The technology took a long time to implement. We were integrating inventory systems, replacing the order management system. And then about six weeks before we went live, we realized we were building a pipe from the website into stores just for beauty items. And what if we didn’t filter it down and did it for all items? I went to the leaders and said, “Do you wanna sell all the products in the stores online?” And that was maybe the stupidest question of my career, because they looked at me like, “What’s the matter with you?” And I said, “Well, here’s the problem. We haven’t had time to estimate what the change is gonna be to the stores. We haven’t had time to hire people to fulfill these orders. We haven’t had time to train people on the process or work with the mail rooms to understand their capacity.” And they said, “Do it. We’re gonna figure it out.”
So we did, and we burst the seams of the company. It was crazy. Jamie Nordstrom was in the Chicago store and called me that day. I was in the Seattle store, and we were printing orders on register tape because we hadn’t bought printers. We thought this was just gonna be an exception for beauty items. So there the registers are, ringing off the hook with orders, and he said, “Julie, I have 21 feet of orders here. What should I do?” I said, “Start fulfilling orders.” That’s what we all had to do.
That six-week timeline is probably more like what we’re in right now, where enterprise change can happen quickly but you have to plan for it, or you’ll wreak havoc on a company. This was good havoc: everyone was excited because the sales were through the roof. We eventually built filters to eliminate things like the three-dollar pair of socks that was on sale in a single pair, those sorts of things.
Bryon: I imagine that’s a fun story to tell in hindsight. I’d like to move toward some closing reflections: but before we do that, Julie, you’re continuing to advise teams. What are the common problems or challenges that leaders and boards are bringing to you day to day?
Julie: I see a lot of companies still trying to figure out what their AI strategy is. How are they taking advantage of this new technology that they know has potential but maybe don’t know how it applies to their business? Where should they start? How do they prioritize it? I talk to companies about the reality of how to get started and also where to dream: looking at readiness across people, data, and technology. Where are the real returns gonna be? Where are the advocates? There are a lot of variables that make AI either more or less successful, and it’s a lot of fun for me to go in and have those conversations, help companies sort through the sandstorm that came with all the promises of AI, and get clear on where the opportunities are and where they wanna begin.
Bryon: Are you enjoying it now that you’re more in an external advisory seat than earlier in your career?
Julie: Yeah, it’s so much fun. What I really love is meeting the teams, going into different companies, having these conversations, learning different industries and the challenges of each. I’m having a great time.
Bryon: In a closing reflection, for those who are feeling a little disillusioned or overwhelmed with the speed at which things are moving, or who feel like they’ve missed the boat on some things: what would you say to that leader?
Julie: Lean in, get started, educate yourself. But remember, you’re the person who understands the business. This is about solving your problems in a different way, not going out and finding a technology to fix something that you know best about. There’s so much to learn, and there’s so much more possible now than there ever was before: but there’s still a lot of hard work to do it.
Bryon: I like that encouragement of leaning into the expertise you already have, understanding the business. That’s not something that’s changing. Add onto it, enhance it, make it smarter.
Julie: The people who built the businesses are the ones in the best position to lead these exciting transformations. They created it in the first place, so they understand the business side and where the opportunities are. I’m looking for those folks to lean in and lead us to what’s next.
Bryon: Awesome. One last question: listeners can see the Averill paddle behind you. Is that a pro model?
Julie: This was a departing gift from my Lululemon team. I’m a little bit of a pickleball fanatic, but I think this one’s more for show.
Bryon: Not your main paddle then. Maybe another career launching: pro pickler?
Julie: I wish I had those skills, ’cause that’s definitely what I would be doing.
Bryon: That’s fun. Well Julie, it’s been really great to have you here today. Thank you for sharing your journey and experience. For listeners who want to get in touch, julieaverill.com is the place to go for more information on her book, her op-ed, and her advisory work. Is that right?
Julie: Yeah. Thank you, Bryon.
Bryon: Good deal. Thanks, Julie.