How Do You AI?

A new campaign from Baseline ITC. Because "We Need AI" isn't a strategy—and the real answer is different for every company.

AI is the new "dot-com."

Remember the late '90s when every company rushed to slap ".com" on their business card without understanding what the internet actually did? Or the 2010s when "moving to the cloud" became the answer to every IT question, whether it made sense or not? We're watching it happen again. But this time, it's AI.

CEOs come back from conferences with stars in their eyes. Boards demand "AI strategies" by Q2. Vendors promise that their AI tool will revolutionize everything. And somewhere in the middle of all this hype, the actual question gets lost: What problem are we trying to solve?

"AI" has become a buzzword so overused that it's lost all meaning. It's automation. It's security. It's analytics. It's chatbots. It's everything and nothing at once.

Business leaders throw the term around with no true definition. They know they're supposed to want it—but they don't know what they're actually asking for or what this powerful technology can truly do.

That's why we're launching a new campaign at Baseline. We're asking: "How Do You AI?" Not "Do you AI?" or "Should you AI?" But how. Because the real answer isn't one-size-fits-all. It's different for every company, every industry, every business problem.

The Problem: AI Without Context

Marc Devoe, our VP of Strategic Accounts, sees it constantly: "CEOs come back after seeing a new AI tool and say, 'hey, I want to do this. I want to integrate it into our organization, and I want us to be more profitable because of it.' But the challenge is they're putting the cart before the horse."

The most common complaint he hears from executives? "Where do I start with all this AI stuff?" Not exactly a complaint—more like confusion. Overwhelm. Decision paralysis.

"There are too many tools," Marc explains. "They don't know where to start. It's too big of a beast and too broad of a term."

Our founder and CEO, Ian Fasack, puts it even more directly: "The initial question I always have is: what do you do in AI? What's your take? What's your capability? When I ask people this, oftentimes their definition of AI is really automation. Sometimes it's security. Sometimes it's agentic code development."

Translation: Nobody actually knows what they mean when they say "AI." And if you don't know what you're asking for, how can a vendor possibly give you what you need?

The "How Do You AI?" Framework

This campaign isn't about selling you tools. It's about asking the right questions before you buy anything.

Because here's what we've learned after 25+ years in IT consulting: AI doesn't fail because the technology is bad. It fails because companies skip the foundation.

Andrew Gristina, our other VP of Strategic Accounts, breaks it down: "This is why we structured our AI assessments the way we did. We begin by identifying three things that have real value. You've got to be able to tie back an ROI or a business value or a time value to the AI tools."

Not "this tool has AI in it, so we need it." But: "What does it actually do for us? What's the ROI? Is this going to make our business more efficient or more profitable?" If you can't answer those questions, you're not ready to implement AI. You're ready to waste money on AI.

What "How Do You AI?" Actually Means

When we ask companies "How do you AI?", we're really asking:

1. What business problem are you trying to solve? "We need AI" isn't a strategy. "We need to reduce customer churn by 15%" is a strategy. AI might be the how—but it's never the why.

2. Do you know what data you have—and is it ready? Marc's assessment is blunt: "I haven't seen one client yet with mature data practices where data scientists know where everything is, have it all clean. Everybody has this challenge right now." You can't feed AI what you can't find. And if your data is messy, your AI outputs will be messier.

3. Do you have governance in place? Marc again: "If you have to prove you have good governance practices, you probably don't have good governance practices." AI governance, data governance, and cyber governance must work together. Build the frameworks first, or you're building a house on sand.

4. What's the ROI timeline—really? Most AI implementations take 9-18 months to show meaningful ROI. Not the 3 months vendors promise in their glossy demos. Set realistic expectations. Budget for the actual timeline. Don't treat AI like a light switch you flip on and magic happens.

5. Can your team actually maintain this long-term? AI isn't "set it and forget it." You need ongoing model training, data pipeline maintenance, and integration support. Budget for it now, or pay for it later when everything breaks.

The Real Answer: It Depends

Here's the truth that no vendor wants to admit: There's no universal "right way" to do AI.

A manufacturing company using AI for predictive maintenance looks nothing like a law firm using AI for contract analysis. A healthcare provider implementing diagnostic support AI has completely different needs than a retail company optimizing inventory with machine learning.

Ian Fasack built Baseline around this reality: "I want to be known for really specific, niche business cases. I don't want to be a GPT provider. I don't want to sell you Nvidia chips. I want to take business processes and workflows and turn them into an automated framework using artificial intelligence."

That's the difference between a vendor and a consultant. Vendors sell products. Consultants solve problems. And the first step to solving a problem? Understanding what the problem actually is.

The Bottom Line

AI is powerful. AI is transformative. AI can absolutely deliver ROI and competitive advantage.

But only if you do the boring foundational work first.

Stop building the plane while flying it. Your competitors rushing into AI without foundations? They're the 95% that fail.

Be the 5% that succeeds.

Build your foundation first. Then ask: How do YOU AI?

Ready to answer that question for your business? Baseline ITC offers vendor-agnostic AI readiness assessments. We diagnose before we prescribe. We listen before we sell. And we help you implement AI that actually solves business problems—not just AI for AI's sake.

Let's make 2026 the year your AI investments deliver real, measurable ROI.