Future-Proofing
Your First AI Integration: How IT Teams Should Evaluate Tools
Your First AI Integration: How IT Teams Should Evaluate Tools by Todd Moss
As someone who's been in IT for over two decades, I've seen cycles of hype come and go. But AI isn't just another wave. It's a shift in how tools interact with people. The question isn't if AI can help your team—it's how, where, and why it should.
But that doesn't mean jumping in blind. Too many companies adopt AI tools because "everyone else is." They end up with subscriptions nobody uses, or worse, automations that confuse teams more than they help. If you're here wondering how to get your first AI integration right, you're already ahead of the curve.
Let me walk you through how we approach it at 24HourTek.
Start With a Pain Point, Not a Product
The best AI projects don’t start with demos. They start with frustration.
A nonprofit ops director tells me their team is drowning in donor database updates. A startup COO mentions how their Slack is clogged with repetitive IT questions. These are signals. Friction points. Opportunities to bring in smart automation—but only after clearly defining the problem.
Ask yourself:
Where are people burning time on repeatable, rule-based tasks?
What delays cause frustration for staff or clients?
Which pain points show up in every quarterly review, but never get resolved?
Once we identify that "itch," then we talk tools.
Align It With the Humans Using It
Here’s the part a lot of vendors skip: your team has to trust the tool.
If AI quietly replaces judgment without explanation, people will reject it—or worse, silently work around it. Good tools build confidence.
That means:
Explaining clearly what the tool does and doesn’t do
Starting with "recommendation mode" instead of full autopilot
Putting humans in the approval loop until trust is earned
AI should feel like a helpful assistant, not an off-brand manager making decisions from behind a curtain.
Once we know the pain point and align the team, we move into the mechanics. This part isn't glamorous, but it's where success is made or lost.
Don't Cut Corners on Security
AI tools often need access to sensitive data: user behavior, emails, financials, internal systems. That means you can't treat them like just another Chrome plugin.
Before we greenlight any integration at 24HourTek, we go through a checklist:
What data does this tool touch, and where does it store it?
Are there clear user permissions and logging mechanisms?
Is the vendor compliant with SOC 2, HIPAA, or other relevant standards?
Do we have a rollback plan if something goes sideways?
It’s not about being paranoid. It’s about treating AI like any other critical system: with discipline and foresight.
Prepare the Ground With Change Management
The best tech in the world won't work if people don't understand it, or worse, feel threatened by it. A little empathy goes a long way.
When we launch new AI tools for clients, we do three things:
We explain the "why" in plain English. Not: "This uses GPT to classify entries." Instead: "This tool will help us close tickets faster by drafting first responses."
We involve end-users early. Small pilot groups. Feedback loops. Build together.
We share small wins fast. "This saved our team 3 hours last week" is more powerful than any slide deck.
A tool that feels collaborative will get used. A tool that feels imposed will collect dust.
Start Small, But Start Right
Some of the most effective AI tools we've implemented didn't overhaul entire systems. They automated one painful step. A quick summary generator. A helpdesk pre-fill. A Slack bot that routes questions to the right person.
These small wins are low-risk, measurable, and trust-building. And they teach your team how to think with AI, not just react to it.
Once the tool is live and your team is onboard, the real work begins: making sure it keeps working.
Measure What Matters
Too many AI integrations fade because no one defines success. Set clear, human-centered goals from day one:
Are we saving time?
Are users less frustrated?
Are we getting better data, faster responses, or fewer errors?
Review these monthly. It doesn’t have to be complex—just consistent. That’s how you catch issues early and make sure the tool stays useful.
Expect AI to Drift—And Plan For It
AI tools can "learn" the wrong things over time if left unchecked. We've seen systems that slowly start tagging tickets incorrectly because someone kept overriding them manually. Feedback loops matter.
Build in checkpoints:
Quarterly audits
Training refreshers
Manual spot-checks
Your AI should be treated like a junior hire: smart, fast, but still needs mentorship.
Know When to Retire a Tool
Sometimes, an integration outlives its usefulness. That's okay. Tech changes. Needs evolve. You might replace a third-party tool with something custom. Or maybe the original pain point is gone.
Don’t force tools to stick around for emotional reasons. Have a clean exit plan, just like you would for any other vendor or app.
About 24hourtek
24hourtek, Inc is a forward thinking managed service provider that offers ongoing IT support and strategic guidance to businesses. We meet with our clients at least once a month to review strategy, security posture, and provide guidance on future-proofing your IT.
If this sounds familiar, we’re happy to help. We’ll walk you through an assessment, help prioritize based on risk and budget, and build a refresh strategy that makes sense—no upselling, just honest advice.