Let’s just say it: for all the hype around AI, a lot of companies are still... well, kinda stuck.

Yes, it’s 2025. Everyone's throwing around terms like “machine learning,” “generative AI,” “automation,” and “LLMs” like they’ve cracked the code. But when you really zoom in, most teams are still using AI to write awkward emails or maybe speed up a spreadsheet or two. Not exactly world-changing.

So what’s the deal? Why is AI so hard to get right, especially in actual day-to-day company workflows?

Let’s break it down. Then we’ll get into 10 things teams can actually do to move forward (without overpaying for some “AI business transformation” workshop).

1. Everyone’s chasing the trend, not the outcome

The thing is... a lot of companies jumped into AI like it was the latest office gadget. You know, like when everyone got a label maker in the 2000s and suddenly everything was tagged.

But the point is, AI’s not a trend. It’s a tool.

Chasing the shiny stuff—like making a chatbot just because “everyone else is doing it”—isn’t the move. It’s like buying a drone before figuring out what you want to film.

Instead: Start with the problem. What slows your team down? Where’s the busywork? What do customers actually need faster or smarter?

Answer those... and AI can step in where it actually counts.

2. No one really owns the AI “thing” internally

You’d think a company investing thousands (or more) in AI tools would have a clear plan, right? Nope.

In most orgs, AI is floating around between departments. The IT team installs something, Marketing plays with ChatGPT, HR asks if it's secure, and... no one’s really leading.

Instead: Appoint an AI lead or task force. Doesn’t need to be a “Chief AI Officer” (unless you’re into titles). Just someone who can connect the dots across departments, pilot real use cases, and share learnings.

Think of them as your AI translator—someone who speaks both “tech” and “team needs.”

3. Teams are overwhelmed (and undertrained)

Let’s be real... AI tools can be intimidating. People open something like Notion AI or Claude and just sit there, blinking.

Because no one told them what to do with it. Or what it’s not meant for. Or how to avoid bad data. Or... anything, really.

Instead: Train for use, not theory. Don’t throw your team into a 4-hour webinar on “AI and the future of work.” Show them how to use it to do something they already do, but faster. Like summarizing meeting notes. Or drafting content outlines. Or turning raw survey results into something readable.

Short. Hands-on. Helpful.

4. They forget that AI is just one piece of the puzzle

AI can write reports. Sort data. Summarize PDFs. Even generate images. But it can’t magically align with your brand, your tone, or your customers... unless you teach it to.

And even then, it still needs a human touch.

Instead: Pair AI with good systems. Use SOPs (standard operating procedures), brand guidelines, and templates alongside AI tools. The AI should fit into your process, not replace it entirely.

This makes sure things don’t go off-brand or off-track.

5. They're trying to automate broken processes

Here’s a hard truth: AI won’t save a bad system. It just... speeds it up.

If your approval process is a mess, or your CRM is a tangled web of half-filled fields, adding AI to that isn’t going to fix it. It’s like putting a turbo engine in a car with no brakes.

Instead: Clean before you automate. Map your workflow first. Trim the fluff. Then (and only then) use AI to fill in gaps, not cover up problems.

6. They overestimate what AI can do right now

We get it. The AI hype machine is strong.

But even the best models mess up. They hallucinate (yes, that’s the actual term), they get dates wrong, and sometimes they make things up with total confidence. It’s not a mind reader—it’s a very advanced guesser.

Instead: Set real expectations. Use AI where speed and structure help—like drafts, research summaries, or first-pass edits. But always plan for human review, especially when accuracy matters.

(And don’t trust it to write legal disclaimers. Just... don’t.)

7. They lack guardrails for employees

You’d be surprised how many teams go from “We’re using AI!” to “Wait... can we even upload that data?”

Without clear rules, employees are left guessing—Can they use ChatGPT with client data? Is Bard okay for internal notes? Should they paste in sensitive info?

Instead: Set up basic usage guidelines. What tools are allowed? What data is off-limits? Who should review outputs before they go public?

Keep it simple. Think of it as your AI “side rails”—not to limit creativity, but to avoid disaster.

8. They ignore low-hanging fruit

Sometimes companies go straight for the big, complex AI tools—custom tools, fine-tuned models, expensive integrations.

Meanwhile, no one’s automated monthly reports. Or set up an AI-powered internal search tool. Or used AI to summarize meeting transcripts (yes, that’s a thing).

Instead: Start with the boring stuff. Look at repetitive, predictable tasks—like formatting slides, answering common emails, or rewriting website FAQs.

Small wins add up. And they build confidence to take on the bigger stuff later.

9. They don’t scale with AI

Even when a team does figure out how to make AI work for one use case, it often stays there. Tucked away in one department. One process. One team.

But AI gets better the more it spreads, because teams learn from each other.

Instead: Share use cases across the org. If customer support found a way to use AI to draft ticket replies, maybe sales can use that same tool for email follow-ups. If Marketing built an AI prompt library, HR might benefit too.

Share the wins. Cross-pollinate.

10. They treat it like a one-time “transformation”

We’ll say it again: AI isn’t a trend. It’s a capability.

Too many orgs do a one-time AI sprint, a workshop, or a pilot... then move on. But the tools are changing weekly. New features drop. Models improve. Use cases evolve.

Instead: Make AI a culture, not a campaign. That means encouraging ongoing experimentation. Regular check-ins to see what’s working. A Slack channel to swap prompt tips. Or even just 15 minutes during team meetings to share “here’s how I used AI this week.”

It’s not about becoming an “AI company.” It’s about staying curious—and staying useful.

Final Thoughts (Before You Go All-In)

Here’s the thing: AI’s not going to replace your team. But your team, with AI? That’s a serious upgrade.

But it takes more than tools. It takes planning. Alignment. A little bit of trial-and-error. And a whole lot of clarity on what you’re actually trying to solve.

So instead of asking, “How do we use AI?”—ask this:

“Where are we stuck... and how can AI help us move faster, smarter, or with less stress?”

That’s where the real value starts.