177 | Why Your AI Strategy Keeps Stalling & The One Decision Making Shift That Finally Moves It Forward | Leadership, Delegation & Systems with AI Frameworks

Are you trying to launch your AI initiatives from a messy lot instead of a launchpad?

Most companies aren’t struggling with AI integration, budgets, timelines, and activations because the technology is bad.

They’re struggling because the foundation underneath the technology is a hot mess. Their business foundation.

In this episode, Dawn Andrews breaks down the invisible reason so many AI initiatives stall out after the demos, strategy meetings, and expensive vendor calls. Spoiler alert? The problem usually isn’t the AI platform. It’s the messy systems, undocumented workflows, scattered data, and unclear decision-making hiding underneath it all.

This episode is your velvet-boot wake-up call if you’re a founder or executive thinking:

“Why are we spending all this money, and nothing is actually changing?”

Because the rockets aren’t the problem. The launchpad is. And once you understand that? Everything shifts.

Want help navigating the messy middle of AI implementation without turning your company into an exhausted science experiment?

Join the AI for Founders Community on LinkedIn, where Dawn hosts live office hours, practical conversations, and real-world AI strategy discussions for founders and executives who are building while the plane is flying.

Because nobody needs another generic AI webinar. You need clarity that actually works in real businesses.

Key Takeaways

• AI implementation is not just a technology project, it’s an operational clarity project.
• Most businesses are trying to automate workflows that only exist inside the founder’s brain.
• Your shared drives, SOPs, client notes, and process documentation matter more than another AI subscription right now.
• Fast-moving founders often mistake preparation for “not making progress.”
• The leaders who prepare their runway now will dominate later.

Resources & Links

• Join the AI for Founders Community on LinkedIn
• Download: 10 Ways AI Will Make You a Better Leader

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• 128 | How Female Founders Use AI to Stop Being December’s Bottleneck
• 122 | The 4-Stage AI Process Female Founders Use to Stop Losing 10 Hours Each Week Answering Questions Their Team Should Own

Want to increase revenue and impact? Listen to “She's That Founder” for insights on business strategy and female leadership to scale your business. Each episode offers advice on effective communication, team building, and management. Learn to master routines and systems to boost productivity and prevent burnout. Our delegation tips and business consulting will advance your executive leadership skills and presence.

Transcript

She’s That Founder
177 | Why Your AI Strategy Keeps Stalling & The One Decision Making Shift That Finally Moves It Forward

In this episode, you'll discover why integrating AI into your business isn't moving as fast as you want it to, and that it has nothing to do with AI.

Hey, hey, hey. You're listening to She's That Founder, the podcast for ambitious female founders who are ready to stop being the bottleneck in their business by using AI frameworks for faster delegation and decision-making.

I'm Dawn Andrews, and today you'll discover why the tip of the iceberg is not the whole story and what's hiding below the waterline in your AI rollout in your company. You'll learn what your foundation actually needs before your technology has anywhere to land, and the runway work that you can do right now, so you're the one who's ready when your IT team steps up.

Let's get into it

Today I'm sharing a conversation I had recently with a senior executive at a large company in the fashion industry.

She is one smart cookie, the kind of leader who does not miss a thing, and she came into our session genuinely frustrated. Not annoyed, truly frustrated, like the kind of frustrated that sets in when you've been watching something not work for long enough that it starts to feel personal. And here's what she laid out.

Her company had been investing significantly in AI integration across the whole company. There was a cross-functional working group, weekly status calls, and new tools being demonstrated just about every week.

All visible signs of momentum, but her honest assessment? Nothing has actually changed. This is the way she described it, and this image stayed with me.

She said, "It felt like everybody had the rockets, everybody was running around getting the rockets ready to launch, but nothing was going into the air."

Now, when I sat with her with that for a minute, like really sat with it, what surfaced wasn't a technology failure, and it actually wasn't a vendor failure, nor was it a leadership failure exactly.

What really surfaced is the foundation wasn't ready, and that's exactly what I wanna unpack with you today, because I'm watching this pattern play out across corporate organizations and small founder-led businesses alike.

The rockets aren't the problem, the launch pad is.

So let's talk about the iceberg that nobody shows you, that part that's underneath the water.

What I'm learning we need to understand first, and I really want you to hear this because it changes how you interpret everything that's happening inside your company right now as you start to work with AI and bring it into your workflows.

What most non-technical people see when they see AI working, like me, when they see a tool that generates a report or an agent that routes their customer emails or a workflow that used to take a person three hours and now takes twelve minutes, what we are seeing is the tip of the iceberg.

We see the finished thing, the working thing, the shiny, time-saving, life-changing, wow, that's impressive thing. But what we don't see is everything below the waterline. And because we are not IT professionals or technically oriented and never have needed to be, we don't see the data cleanup, the infrastructure work, the requirement scoping, the testing, the iteration, the versions that don't work, the versions that come after that, the conversation where someone had to admit that the requirements weren't actually clear enough yet, and we need to go backwards several steps and rebuild That work exists.

It has always existed, and AI has accelerated a lot of the development process, and it's raised the ceiling by so much on what's possible with shortened timelines. And I'm not here to tell you that AI technology and how it's going to really transform your business isn't real. It is extraordinarily real, like scary real and amazing real, but it still hasn't eliminated the steps that it takes to employ AI in your company.

And that gap between how fast AI feels because you type something into a tool and get back a full proposal in four minutes and how fast AI actually lands integrated inside your company, which moves through all the unglamorous work that doesn't make the slide deck, that gap is enormous.

And nobody in the organization is explaining that clearly to the people who are sitting in the steering committee watching the launch timeline slip and the budget get burned.

So if you're the leader who's frustrated because we bought the platform three months ago and nothing has changed, I want you to hear me. I want you to hear me when I say you are probably not reading a failure. You're reading that bottom of the iceberg, the part that was always gonna take time that nobody put in the slide deck.

The platform that's coming that will be integrated into your business is only as good as the foundation it's sitting on. And if that foundation isn't ready, then the tool and all of those developers and that big budget that you've invested to bring AI into your company is just sitting there waiting.

Which brings me to something a client said that I have not been able to stop thinking about.

If this is landing for you and you're nodding along because this is exactly what you're watching play out inside your company or your own business, come join us in the AI for Founders community on LinkedIn.

It's free. It's where we workshop the messy middle, the real-world application, and the questions that you just can't seem to find answers for, the stuff that actually matters when you're trying to build things for real with AI. So join us at the AI for Founders community on LinkedIn, and you'll find the link in the show notes. We'll be right back

So here's what my client said to me that stopped me in my tracks. We were talking about why, despite all the investment, all the activity, nothing was actually moving. And she looked at me and she said, and I'm paraphrasing here because this is a metaphor that I've started using with everyone, she said, " Dawn, it's like we're trying to make something smell better when what we actually need to do is take a shower first."

I was like, " Ooh, that's very vivid, and yeah, I get it. I, I understand, and that is the one." Because here's what actually surfaced when we dug into it. The company's data infrastructure was not ready for what they were trying to build with AI.

Files hadn't been organized, and I don't mean tidied up. I mean fifteen years of accumulated folders across different shared drives and redundant spreadsheets and outdated versions of things sitting next to current versions of things with no clear labeling.

Source data that the AI tools literally needed to run on and yet didn't exist in a usable form yet. And when you're running and making your business happen, especially when you've organically grown over time, you're not worried about that. You're just worried about what works in that current moment.

But for AI, to build these AI tools, you've gotta take it all the way down to the studs.

You can't just hand over the current version as it is and expect it to work because most AI tools are pulling on data and databases from years ago that you as a human may remember, may interpret, may have history with, but AI will not make those connections. You have to make it one hundred percent explicit.

So the steering committee was meeting every week. The demos of what was possible across their business were happening, but the technology was real, but the foundation, that messy, unglamorous, unsexy foundation of clean data and clear process had not been addressed.

So real talk, I just, I really want everybody to understand this here, is that most of us who are going through these big AI implementations, we're not technical people, and we have jobs to do.

And not only do we have the job that we're trying to do, we're trying to shepherd our teams through change management, through, you know, the difficulty and the unsettled feeling of AI coming into your workspace and the promise of what it could do really well, and the terror of potential jobs being lost or things having to be completely reorganized.

So you've spent years building these systems that work for you right now, but you may need to really take them apart before you can make them go faster. So even with the most sophisticated platform on the market and the best vendor and executive sponsorship, if your process is broken or unexplainable to a tool that is not going to understand all the nuance and your data is dirty, the technology is just gonna sit on top of the mess.

It doesn't fix it, it inherits it, and in many cases, it amplifies it because now your broken process that you've been kind of running with like chewing gum and a paperclip will run even faster and more exponentially.

So this isn't a tech problem, it's a foundation problem, and I wanna make sure that we're applying this metaphor across the board because I'm not talking just about corporate leaders right now.

I'm talking to you if you're a founder running a service-based business, because this applies to you too.

How organized is your shared drive? How clean is your client data? And if you wanted to hand a tool the raw material that it needed to run a workflow for you, your email history with clients or project notes or SOPs, is that material clean, organized, and in a usable form, preferably in markdown language?

Or is it scattered across inboxes and Google Docs and sticky notes and your own memory and some of your team's memory? The single most powerful thing you can do right now to get ready for AI is to not buy another tool. Prepare your foundation.

So simple takeaway, before you stack technology on top of this high-speed engine, clean up what the technology is going to sit on.

Don't stack digital transformation on top of chaos. And taking the time to sort out this foundation can feel interminable. But I wanna be clear that you're not waiting, you're preparing the runway.

So here's what I know about people who listen to this show, because I am a fast talker and a fast thinker and a fast doer, chances are you're either listening to me on one point five speed or you are a very action-oriented person.

You don't like sitting still, and you especially don't love being told to be patient while a process unfolds on someone else's timeline.

So I'm gonna reframe what not moving yet actually means for our fasty fast selves, because I wanna give you a completely different way to think about this moment.

Think about it this way. Imagine you've hired a contractor to renovate your bathroom. They're ready to work. They got the crew. They got the tools. They know the plan, and they show up, and the materials aren't there. The tile you ordered hasn't arrived. Permits, not pulled. Decisions about fixtures, not finalized.

So what happens? The contractor moves on to the next job. It's not on them. It's on you not being ready when they were ready.

When they are ready for you, and they will be, You wanna be the team that walks in with a box that says,

"Here's our data organized. Here's what we need the tool to do in writing. Here's what working looks like from our perspective." '

Like all of those questions, if you can sort them in advance, you will meet your AI build vendor, your, you know, Palantir or your Snowflake programmer or whomever you're using, your Deloitte contractor, you will meet them ready to go That is not waiting.

That is preparing the runway. And this is the Wild West right now. Like, I wanna be clear that nobody's doing anything wrong. This is a really chaotic, disorganized time as we move into the future with our businesses. It just really is, and it's amazing, but most of your vendors are focused on what they need to learn and do around AI to be strong developers, to create the technical outcomes that you're looking for, and they are not good at helping to bridge the gap between your non-technical self and their very technical selves.

And that's what I'm doing here in this episode for you. So those questions, I'm gonna repeat them again. So imagine you're showing up for your contractor with all of your stuff ready to go. Here's our data, clean and organized, our processes documented, preferably in markdown documents.

Here's what we need the tool to do in writing. Here's what working well looks like from our perspective, and here's potentially an example, a finished product. So that's what it means to prepare the runway Here's the specific work that I want you to think about doing right now. I know I just gave you, like, the quick questions.

I'm gonna break it down just a little bit more. First, clarify your requirements. Requirements is a piece of language, it is a word that goes from our non-technical side to their very, technical side. They are asking for your requirements, so what does that even mean?

What they're asking is: what do you actually need the tool or the workflow that we're building with AI to do? Not in theory, not AI should help us be more efficient. But what specific task with what specific input producing what specific output? Get it out of your head and into a document.

The second thing that you need to do to be really prepared is audit your data. If the workflow you wanna build depends on information that lives somewhere, like in a CRM or a shared drive or someone's inbox, go look at it. Is it clean? Is it complete? Is it in a format a system can actually read? If the answer is no, that's your work right now.

Third, document your process. I cannot say this enough. I mean, I ring this bell all the time on the podcast. Document your process. Your AI tools are going to need to understand how your workflow runs, And if you can't explain your workflow to a human in clear, sequential steps, you can't explain it to a system either because the system can't see your face, it can't read your body language, it can't make inferences. It's only going with the actual literal information. So document it first, clean it up second, and then you're ready to automate it

Most leaders in this moment are going to do one of two things. They're panicking because we're behind, or they're checking out because this is gonna take forever, and this is not my problem. Neither of those is useful in this moment. The leaders who are going to win here are the ones who look at this moment and say, " Okay, I know what's needed. I know what I can do right now. I know what I can pass off to team to do right now, and I'm gonna show up to the next status call, next meeting, not with demands about why things aren't moving faster, but with the finished runway prep. Here it is. We're ready." That's the kind of leader that changes the conversation, and that is the leader that also protects her team from the panic of feeling behind in a race that doesn't have a defined finish line yet.

The leaders who win with AI aren't the ones moving the fastest. They're the ones who did the preparation work that everyone else is skipping.

Okay, I'm just gonna bring this home. Here's what we covered today. The reason your AI initiative seems like it's taking forever, or you feel like your vendor's not giving you what you want fast enough, or you're burning through your budget, it's not the technology, it's not the vendor, it's the foundation.

That iceberg was always there under the surface. AI didn't eliminate the steps. It just made the gap between what you see and what's actually required more visible. Everybody's data is messy. Everybody's processes are not documented fully, and you can't stack transformation on top of chaos and expect the transformation to sort out the chaos.

It doesn't work that way. Your action step, and I want you to do this before your next week of work starts, pick one workflow in your business or on your team. One, and it doesn't have to be big. It doesn't have to be the one that's been on the AI roadmap for six months. Just pick one testable area and ask yourself, " If I wanted to hand this to a tool or an assistant today, is the material actually ready? Is the data clean? Are the numbers real? Is the process documented? And do I know what done looks like?"

If the answer is yes, you're ready. Start there. If the answer is no, all good. That's your work. Do not buy another platform or more time with your vendors, and don't attend another demo. That right there is the work, like preparing the foundation is the work.

Because here's what I know about you. You are not behind. You're building. And the leaders who are doing that unglamorous foundation work right now, cleaning and deleting files, clarifying requirements, documenting the things that live only in their head, those are the ones who are gonna walk into Q4, who are gonna walk into their year-end with implementations that actually run and change the business forever.

Be that leader. If you wanna keep building with a community that gets it, come find us in the AI for Founders community on LinkedIn. Every month, I run a live office hours session where we dig into exactly this kind of thing, the real application, the messy middle, the questions you actually have.

You can find us at AI for Founders on LinkedIn and in the show notes. I'll see you there. Okay. That's it for today's episode of She's That Founder. We've been talking about the foundation work nobody sees because that's the work that makes everything else possible.

So go get 'er done. I'll see you on Thursday