Is Anyone Actually Watching Your AI?
AI is everywhere right now: newsletters, product launches, lead generation campaigns, scheduling tools. Innovation moves fast, and the list of applications keeps growing. But speed and volume raise a question worth sitting with: are we actually reviewing what our AI tools produce, or are we letting them run unchecked?
Here's a concrete example. I received seven emails from a single representative at a company pitching appointment-booking services. The progression below tells a story.
Email 1: An initial outreach about booking more meetings through a pay-per-qualified call model.
Email 2: A follow-up asking whether I'd seen the first message.
Email 3: A third attempt referencing their MMD AI booking tool, with a note acknowledging it was the third try.
Email 4: A request to "pencil in" a quick call.
Email 5: A check-in asking whether I received the last email.
Email 6: An availability request for two specific days at noon, no time zone included.
Email 7: A longer message circling back with a 10-minute call ask and a case study from a company I'd never heard of.
No person monitoring their own outreach sends seven emails to a contact who has not responded once. This sequence has the fingerprints of automated AI: running without human review, optimizing for follow-up cadence rather than genuine engagement. The tools aren't the problem. The lack of oversight is.
I use AI regularly. I rely on it to check clarity and flow in my writing, research topics, generate campaign image concepts, and build content calendars, breaking larger themes into weekly posts. I treat it as a tool I activate intentionally, not a system I set loose.
Automation offers real advantages when used with discipline. Large-scale email sends, automatic report summaries, calendar management with smart notifications: all of these save meaningful time. But every automated system requires a human to keep track of what it's actually doing. The seven-email sequence is what happens when no one is.
The question isn't whether to use AI. It's whether you're the one in control.
So WHO is at the Wheel?
One of AI's selling points is its ability to pull potential client data. But what happens when that data is outdated or simply wrong? By doing your due diligence and verifying what the tool has pulled before you reach out, you can spare yourself from serious embarrassment.
We experienced this firsthand about ten months ago. A young man we will call "Tom" appeared on LinkedIn as an employee of Mind The Gap Services. He had never worked for our company or spoken to anyone on our team. What happened was that his personal brand name was close enough to ours that LinkedIn connected him to our business page. When I found this unexpected "new employee," our team discussed how to handle it, and I reached out to explain the situation. He unlinked his brand from our page. Problem solved, or so we thought.
Fast forward to today. One of our team members now regularly receives emails addressed to "Tom." Her name does not start with a T, and their last names share no resemblance. But during the brief window when Tom was connected to our page, AI logged him as a permanent member of our team and tied him to her email address. That association has never been corrected. It is a clear sign that no one on the sending end is verifying whether their data is current before hitting send.
Is That How You Address Your Clients?
Another instance of AI pulling incomplete data landed in my inbox recently. Opening an email with only someone's last name is not professional and should never make it past a basic review. Here is what that looks like in practice:
Spies,
If you want to lead blah blah blah blah blah…..
Regards,
Mr. “My AI sent this without me checking it” Smiley
The body of the email was professional enough, but no one who has reviewed their own outreach sends a greeting that is just a last name to a complete stranger. I heard my last name used that way plenty of times in the military, but never in a cold business email. No honorific, no first name, just "Spies." It killed any interest I had in reading further.
Maybe the system failed to capture that Sunny is my actual name. Maybe there was a data hiccup that left the field blank. Either way, a simple review before sending would have changed the entire tone of that email. Instead, it felt less like a business pitch and more like a commanding officer asking for a favor.
Who's Minding the Machine?
The examples in this article are not rare edge cases. They are the everyday result of powerful tools being used without a human in the loop, and we are seeing it every day. Seven unanswered emails. A ghost employee still tied to an active inbox. A greeting that addressed a stranger by last name like a commanding officer. Each one could have been caught with a simple review before hitting send.
AI is not the problem. Neglect is. These tools work best when a person is actively directing them, reviewing their output, and course-correcting when something is off. The moment you stop paying attention is the moment your automation starts working against you.
So, take stock of what you have running right now. Check what your tools are sending, who they are sending it to, and whether the data behind it is accurate and current. Using AI well is not about using it more. It is about using it with intention. You built your business on your reputation. Make sure the tools working on your behalf are protecting it, not undermining it.
