Why Most AI Initiatives Fail with Paul Shirer

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**Michael Hartmann** (0:25)
Hello, everyone. Welcome to another episode of Ops Cast, brought to you by marketingops.com, powered by all the MO Pros out there. I am your host, Michael Hartmann, joined by no one again. We'll get Mike and Naomi back at some point here, I'm sure. But today, I am talking with Paul Shirer, founder and CEO of Infinite Ideas AI and director of AI and go-to-market technology at Bridge Partners.
Paul spends his time helping organizations evaluate, implement and scale AI initiatives. And in earlier conversations with him, we found ourselves coming back to a theme that many ops professionals are wrestling with right now.
That is, despite massive investment in AI, many organizations are struggling to generate meaningful business impact. That is measurement. We'll explore why that is, where companies are getting AI adoption wrong, how leaders should be thinking about workflow design and decision making, and what practical steps organizations can take to move beyond experimentation and toward measurable value. So Paul, welcome to the show. Thanks for joining.

**Paul Shirer** (1:24)
Hi, Michael. Thanks so much for having me. I'm excited to talk today.

**Michael Hartmann** (1:29)
It's an all Texas affair today since you and I are, what, about 50 miles apart? Is that about right?

**Paul Shirer** (1:36)
Yeah, that's about right. You got the North side covered, I got the South side.
We got our territories, we stay in.

**Michael Hartmann** (1:43)
There we go.
Well, again, I appreciate it. So let's just dive right in. So when you've talked and what we've sort of trade messages about, you've said that many organizations are treating AI as a tooling problem when in reality, it's a workflow and adoption problem. So break that down. What does that mean in your words? And how did you get to that sort of point of view?

**Paul Shirer** (2:13)
Yeah. Well, I got to that point of view by failing, number one.
So that helped a little bit.

**Michael Hartmann** (2:20)
Payne is a good teacher, right?

**Paul Shirer** (2:21)
That's right.
Yeah. So I remember, I recall back over a couple of years ago, and maybe it's two and a half years ago now, when the ChatGP moment hit. And the first thing was like we need to get ChatGPT, right? And so we got it, everyone got a license, and then you'd go look at the usage of that tool, and it would be like very few people using it at the time. Now, I'm sure that would be different if we did it today, but at the time, it was very little.

**Michael Hartmann** (2:48)
Yeah.

**Paul Shirer** (2:49)
And so you start looking at how we're going to start transforming the way we work. And really, that was the theme from the beginning. If you were getting ahead of it from a strategic standpoint, you were thinking this is going to change. But how long is it going to take? What's it going to take to do that? And what are the baby steps along the way, right? And so a tool is just a tool. It's sort of like a hammer is just a hammer. I hear that all the time. That's what it is. But unless you have something to use it on and kind of what you're trying to build, then it's not really all that useful.
So I think that the key to this whole thing is, for most organizations is start where people are. Don't get way, way ahead of yourself.
The idea that you're going to change away all of your workflows and processes and get people to follow along and do that all at the same time. It's a very difficult thing to do. And I think a lot of folks have done that in terms of how they piloted AI. They're trying to rewire everything. And so I kind of advocate for the people where they are, how they're currently working, give them to buy in, get them to actually start to use these things and see the value and let them be your research. And one of the metaphors I use, not such a metaphor, but a sort of strategic framing I use is, we're working inside organizations, but it's not much different than if you were going to market with a new tool. And so think about your organization as the marketplace, if you will. And what are the pain points? What are the problems, the challenges that they have? And how can we have this new technology come in and help solve some of those problems? So meeting them where they're at, getting their sort of buy-in in the early stages of it, how can you help them create better content, make better decisions, look at analytics in a different way, all the things that we know AI can do, but talk to them about it. And start to begin to understand how you can support them with the tool itself. And that means obviously skilling, it obviously means onboarding and creating communities of practice, make it be their idea, so to speak, help people share those ideas.