In celebration of International Women’s Day, this episode of Analytics Power Hour features an all-female crew discussing the challenges and opportunities in AI projects. Moe Kiss, Julie Hoyer and Val Kroll, dive into this AI topic with guest expert, Kathleen Walch, who co-developed the CPMAI methodology and the seven patterns of AI (super helpful for your AI use cases!). Kathleen has helpful frameworks and colorful examples to illustrate the importance of setting expectations upfront with all stakeholders and clearly defining what problem you are trying to solve. Her stories are born from the painful experiences of AI projects being run like application development projects instead of the data projects that they are! Tune in to hear her advice for getting your organization to adopt a data-centric methodology for running your AI projects—you’ll be happier than a camera spotting wolves in the snow!

Links to Resources Mentioned in the Show

• Canva Create April 10, 2025 – Hollywood Park, Los Angeles


• Build a gem


• Thinking in Maximums: Escaping the tyranny of incrementalism in product building


• The Secrets of Instacart’s AI: What’s Next for Personalized Shopping? with CPO Daniel Danker

Photo by Caleb Woods on Unsplash

Episode Transcript

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0:00:05 .8 Announcer: Welcome to the Analytics Power Hour. Analytics topics covered conversationally and sometimes with explicit language.

0:00:13 .8 Moe Kiss: Hi, everyone. Welcome to the Analytics Power Hour. This is episode 266. I’m Moe Kiss from Canva. And I’m sitting here in the host chairs today because we’re continuing our great tradition of recognizing International Women’s Day and all of the amazing women in our industry. So it’s coming up this Saturday, March 8th, and we’re going entirely gents free today. So of course that means I’m joined by the wonderful Julie Hoyer from Further.

0:00:44 .1 Julie Hoyer: Hey, everyone.

0:00:45 .1 MK: And Val Kroll from Facts and Feelings as my co hosts. Hey, Val.

0:00:49 .1 Val Kroll: Hello. Hello.

0:00:50 .0 MK: Are you ladies excited to know that Tim won’t be slipping into some of his quintessential soapboxing?

0:00:56 .8 JH: Save some for the rest of us.

0:00:58 .3 VK: I don’t think he’d be able to help himself on this one.

0:01:01 .5 MK: I know, I know. He’s pretty gutted to miss it. So, as we’re planning the show today, I fired up ChatGPT, which, to be fair, I’m a power user and I asked it to compare our topics from the last 50 shows to the topics data folks are most talking about these days and basically identify the gaps in our content. So, unsurprisingly, the response it came back with was that we should definitely talk more about AI, and it was in caps, so maybe there’s some bias in that model. Who knows? Weird. But it’s got a good point. And we’ve definitely talked about AI on multiple episodes on the show, but we probably haven’t talked about it nearly as much as we could or as much as it’s getting talked about in the industry right now. So it seems like everyone is just so excited about the possibilities. But lots of organizations are also struggling to figure out how to actually identify, scope, and roll out AI projects in a clear and deliberate manner.

0:01:58 .9 MK: I think it’s really about that shift from the tactical day to day things to the real transformation that everyone’s seeking. And that’s why for today’s episode, we’re joined by Kathleen Walch. Kathleen is a director of AI Engagement Learning at the Project Management Institute, where she’s been instrumental in developing the CPMAI methodology for AI project management. She is the co host of the AI Today podcast, which I highly recommend checking out, and she’s also a regular contributor to both Forbes and Techtarget. She’s a highly regarded expert in AI, specializing in helping organizations effectively adopt and implement AI technologies. And today she’s our guest welcome to the show, Kathleen. We’re so pumped to have you here.

0:02:43 .6 Kathleen Walch: Hi and welcome. I’m so excited to be here today. I obviously love podcasts, so I love being guests on them as well. It’s a different seat for me today.

0:02:52 .1 MK: It is definitely a different seat when you’re a guest. Hopefully a little lighter on the load. So just to kick us off, I think one of the things that’s really interesting about your professional history is that you don’t seem to be one of those people that just stumbled into AI in the last year or so and have gone full fledged on it. It really seems to be an area that you’ve been working in deeply for an incredibly long period of time. Maybe you could talk a little bit about your own experience and the journey you’ve taken to get here.

0:03:23 .2 KW: Yeah, I like that you bring that up. I always say that I’ve been in the AI space since before gen AI made it popular. I feel like the past two years or so, everybody feels like they’re an AI expert and everybody is so excited about the possibilities. But it’s important to understand that we always say AI feels like the oldest, newest technology because the term is officially coined in 1956, so it’s 70 plus years old. But we just feel like we’re now getting to understand AI. And there’s a lot of reasons for this, which we talk about quite often. But one big reason is that there’s been two previous AI winters, which is a period of decline in investment, decline in popularity. People choose other technologies, other ways of doing things, and a big overarching reason for that is over promising and under delivering on what the technology can do. So it’s really important to understand that AI is a tool, and that there’s use cases for it, and it’s not a tool that’s one size fits all approach, especially when it comes to generative AI. So my background and what got me here is actually I started off in marketing and then moved…

0:04:29 .7 KW: Yeah, I know. And then back when I was first coming out of college, my husband’s a software developer. I feel like the technology world and marketing or creative world or anything else, they really were very separate. And over the years they’ve merged closer together to the point now that I think technology is infused in many different roles and not as disparate as it used to be. Then I moved more into a data analytics role. Learned all about the pains of big data, how data is messy and not clean and all of that. And then I moved into more of a technology events role where my husband and I had a startup. It failed, but met a lot of great people from that community. Ended up going with my business partner from Cognilytica for a company called TechBreakfast, where we did morning demo events throughout the United States. And we were in about 12 different cities. So from Boston, Massachusetts to the Baltimore DC Region, North Carolina, Austin, Texas, really all over, a little bit in Silicon Valley. But that’s a unique space. And around 2016 we started to see a lot of demos around AI and in particular voice assistants and how we could be incorporating that.

0:05:48 .4 KW: That was when all of the big players in voice assistants started to come out. So we had Amazon Alexa and Google Home and Microsoft Cortana, when that was still a thing. So from that we said, there’s something here. And we started an analyst firm actually focused o