Brian Gibbs

04/03/2026

You know something I’ve been seeing more and more lately?

AI is already showing up inside businesses, and most owners don’t even realize it’s happening.

It usually starts pretty innocently. Someone on the team is buried, trying to keep up, finds a free tool, and uses it to move a little faster. Nothing dramatic. Just trying to get through the day.

But over time, it shifts things.

Those tools are not just helping with speed. They start shaping how information gets filtered and what gets attention. That means they are quietly influencing decisions.

I’ve seen situations where everything looked fine on the surface, but something important slipped through because the system didn’t understand the context the way a person would.

Most people’s first instinct is to shut it down, but that rarely works. People will keep using whatever helps them do their job better.

What tends to work better is just bringing it into the open. Have the conversation, see what’s already being used, and then decide where AI makes sense and where you want a human making the final call.

04/02/2026

𝗔𝗜 𝗶𝘀 𝗻𝗼𝘁 𝗮 𝘁𝗼𝗼𝗹 𝘆𝗼𝘂 𝗶𝗻𝘀𝘁𝗮𝗹𝗹. 𝗜𝘁 𝗶𝘀 𝗮 𝘀𝘆𝘀𝘁𝗲𝗺 𝘁𝗵𝗮𝘁 𝗺𝗮𝗸𝗲𝘀 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀.

That shift changes everything.

Ray almost let AI approve 6,000+ safety clearances in an hour. Fast, cheap, tempting. One wrong approval could have put someone in danger and put his business on the hook for it.

He stopped. Thought it through. Rebuilt the process.

AI handled the document review and prep work. Humans made the final call.

Three weeks of work turned into three days. Speed went up. Risk stayed controlled.

That is the move.

Use AI to remove effort. Keep human judgment where consequences matter.

03/25/2026

Here's a rule I give every business owner I work with, and I want you to write it somewhere you'll actually see it.

Automate the hunt. Not the judgment.

Let me tell you what I mean.

I worked with a sales team that was drowning. Each rep spent two and a half hours a day just finding information: researching prospects, pulling news, reading earnings calls, tracking down the right contact name. By the time they sat down to write a message, they were already exhausted.
They brought in AI to help. But here's where they didn't take the easy road.

They didn't let the AI write the emails. They let the AI do the hunting. It pulled the prospect's recent news. It flagged relevant initiatives. It surfaced the names of the budget owners most likely to care. Then a human sat down with that intelligence and wrote a message that proved they'd done their homework.

Their reply rate went from 3% to 22%.

Not because they automated the output. Because they automated the prep work and kept the judgment human.

The hunt is finding, sorting, flagging, gathering, and organizing. That's where AI thrives. The judgment is deciding what it means, what to promise, and how to say it in a way only your company can.

When you confuse those two layers, you don't just create operational risk. You chip away at the thing that makes clients choose you over the cheaper option down the street.

Hunt with the machine. Judge with the human. That's the whole game.

I wrote an entire book on how to draw that line inside your business. If you want to go deeper: https://vist.ly/4w3rp

03/23/2026

𝗘𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆 𝗶𝘀 𝗼𝗻𝗹𝘆 𝘃𝗮𝗹𝘂𝗮𝗯𝗹𝗲 𝗶𝗳 𝗶𝘁 𝗳𝘂𝗻𝗱𝘀 𝘀𝗼𝗺𝗲𝘁𝗵𝗶𝗻𝗴 𝗯𝗲𝘁𝘁𝗲𝗿.

I want to leave you with the one question I ask every business owner after they tell me about their AI wins.

"What did you do with the time you saved?"

Most people pause.

They automated a workflow. It worked. They saved ten hours a week across the team. The dashboard looks better. The process is cleaner. And they're already looking for the next thing to automate.

But those ten hours? They kind of just... disappeared. Nobody's quite sure where they went.

Here's the thing about efficiency. It's only valuable if it funds something better.

Better client conversations that used to get cut short. A more careful review process for work that actually matters. Time to train the junior person who has potential but keeps getting deprioritized. The call you've been meaning to make to the client who's been quieter than usual.
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If automation doesn't buy you something better, it just bought you a slightly less frantic week. And a slightly less frantic week is not a competitive advantage.

The consulting firm that used AI to cut their research phase by 70% didn't pocket the savings. They used the new capacity to serve a client segment they'd been turning away for years. First year: $3.2 million in new revenue.

They didn't just get efficient. They got strategic.

Efficiency is the input. What you build with it is the business.

So before you automate the next thing, decide where the gain is going. Name it. Assign it. Make it real.

Because if you don't redirect the time on purpose, the calendar will fill it with something. And that something is almost never the thing that actually moves the business forward.

I wrote the full playbook for getting this right. If you're ready to go deeper: https://vist.ly/4vvf8

03/23/2026

I love WA, but it's so hard to justify going back right now.

The new mayor of Seattle has a proposal that is so insane it could destroy what little the city has left. Instead of cleaning up the streets, the mayor wants...

03/20/2026

Small businesses are bleeding thousands of dollars every single month — not because AI doesn't work, but because they're using it wrong.

Sound familiar? You've probably tried AI tools. Maybe they felt overwhelming. Maybe the results were "meh." Maybe you're still not sure what you should or shouldn't be handing off to a machine.

That's exactly the gap Brian Gibbs' "What NOT to Automate" was written to close.

This isn't another hype book about how AI will save your business. It's the playbook for business owners who want to get it right — the honest, strategic guide to knowing where AI helps, where it hurts, and how to stop leaving money on the table either way.

✅ Avoid the costly mistakes your competitors are already making
✅ Know exactly which tasks to automate (and which ones to NEVER touch)
✅ Walk away with a clear AI strategy built for YOUR business

The article will be tomorrow's fish wrap. This book will save you thousands.

👇 Get your copy today - https://www.amazon.com/What-NOT-Automate-Strategy-Playbook/dp/B0GPDQ17MY

03/11/2026

The most dangerous thing in your business right now isn't your worst employee.

It's the AI nobody is supervising.

Most companies think adoption is a software problem. It isn't. It's an operating system problem.

AI doesn't just automate tasks. It rewires how decisions get made, how risk spreads, and who's actually in control.

Most owners don't figure that out until something breaks.

The companies winning with AI aren't deploying more tools. They're building systems that control how those tools make decisions.

Skip that step and you get decision drift — machines quietly making choices nobody intended to delegate.

New episode is live here - https://vist.ly/4ujh6

03/11/2026

𝗠𝗼𝘀𝘁 𝗽𝗲𝗼𝗽𝗹𝗲 𝘁𝗵𝗶𝗻𝗸 𝘁𝗵𝗲 𝗿𝗶𝘀𝗸 𝘄𝗶𝘁𝗵 𝗔𝗜 𝗶𝘀 𝘁𝗵𝗮𝘁 𝗶𝘁 𝘄𝗶𝗹𝗹 𝗺𝗮𝗸𝗲 𝗺𝗶𝘀𝘁𝗮𝗸𝗲𝘀.

𝗧𝗵𝗮𝘁 𝗶𝘀 𝙣𝙤𝙩 𝘁𝗵𝗲 𝗿𝗲𝗮𝗹 𝗿𝗶𝘀𝗸.

The real risk is that AI slowly begins making decisions that no one intentionally delegated to it.

It usually starts with something harmless.

A company installs a bot to answer parking questions. Another tool routes customer support tickets. A system summarizes incoming emails.

All of that seems reasonable.

But tools tend to drift.

The bot that answered parking questions eventually gets asked about lease renewals. The support system starts deciding which complaints deserve escalation. The email assistant begins drafting responses to sensitive clients.

No one sat down and decided these decisions should be automated.

They simply happened over time.

Not because the AI demanded it.

Because nobody stopped to ask a basic question:

What kind of work is this?

Some work is ex*****on. Ex*****on follows patterns, rules, and repeatable steps. AI is extremely good at that.

Other work is judgment. Judgment comes from years of conversations, mistakes, context, and relationships.

When owners tell me they are automating everything, I usually ask them two questions.

What happens if the AI gets this wrong?

Does this decision depend on experience someone earned over time?

Those two questions usually reveal the entire situation.

Once you see it this way, most workflows fall into four clear zones.

When you map work across two dimensions—𝗿𝗶𝘀𝗸 and 𝗰𝗼𝗻𝘁𝗲𝘅𝘁—four zones appear.

𝗙𝗮𝗰𝘁𝗼𝗿𝘆 𝗙𝗹𝗼𝗼𝗿 — Low risk and low context. Automate aggressively.

𝗢𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀 — Moderate risk. AI assists, humans verify.

𝗔𝗱𝘃𝗶𝘀𝗼𝗿𝘆 𝗟𝗮𝘆𝗲𝗿 — High context. AI can recommend, but people decide.

𝗕𝗼𝗮𝗿𝗱𝗿𝗼𝗼𝗺 — High risk and high context. Judgment stays human.

Most companies adopting AI have never mapped their work this way.

Which means they do not actually have an automation strategy.

They have 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻 𝗱𝗿𝗶𝗳𝘁.

Automate the work that follows patterns.

𝗣𝗿𝗼𝘁𝗲𝗰𝘁 𝘁𝗵𝗲 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀 𝘁𝗵𝗮𝘁 𝘁𝗼𝗼𝗸 𝘆𝗲𝗮𝗿𝘀 𝘁𝗼 𝗹𝗲𝗮𝗿𝗻.

If you are not sure where your own workflows fall, send me “𝗔𝗨𝗗𝗜𝗧.” We will figure it out together.

03/10/2026

Most leaders think AI is just better software.

It isn’t.

Software follows instructions.
AI suggests answers.

That sounds like a small difference.

But it quietly moves AI out of the 𝙩𝙤𝙤𝙡 𝙘𝙖𝙩𝙚𝙜𝙤𝙧𝙮 and into the 𝙙𝙚𝙘𝙞𝙨𝙞𝙤𝙣 𝙘𝙖𝙩𝙚𝙜𝙤𝙧𝙮.

A calculator waits.
AI proposes.

And once a system starts proposing answers, people slowly begin trusting it to decide.

That’s the moment leaders lose control without noticing.

Smart companies use a simple operating rule:

𝗔𝗜 𝘀𝗰𝗮𝗻𝘀. 𝗛𝘂𝗺𝗮𝗻𝘀 𝘀𝗶𝗴𝗻.

Let the machine accelerate information.
Keep the final decision attached to a human name.

What decision in your company should never be handed to AI?

01/29/2026

https://vist.ly/4pmt6

01/29/2026

At some point in the meeting, someone suggests asking AI. It usually happens after the discussion has gone long enough to feel repetitive but not long enough to surface what is actually wrong. Growth is off, yet every explanation sounds reasonable until the next one replaces it. Priorities keep shifting, and everyone can feel the gap, even if no one can quite name it.

Opening a laptop and typing a prompt feels like forward motion. The question is framed broadly enough to sound strategic and loosely enough to avoid committing to a real position. When the response comes back, it is clean and well structured. The language sounds familiar. The ideas are ordered into phases, priorities, and next steps. It reads like something that could plausibly work, which is often enough for the room to relax.

What that moment provides is not clarity. It is relief. Relief from having to sit with a problem that has not yet been fully understood, and from the discomfort of admitting that the underlying issue is still unresolved.

When unfinished thinking is handed to AI, it comes back smoother than it deserves to be. Assumptions gain shape without being tested. Decisions feel coherent without having been fully made. Because the output looks polished, it feels trustworthy. Because it feels trustworthy, it is easy to mistake it for progress, even when the logic underneath has not improved.

The cost of that mistake rarely shows up immediately. It appears later as priorities drifting apart, teams interpreting the plan differently, and leaders making expensive adjustments to something that once felt solid. By then, the frustration is usually framed as an ex*****on problem or change fatigue, even though the instability was present from the beginning.

The issue is not adopting AI too slowly. It is using AI to move faster through decisions that were never clear in the first place. Compressing decision time without improving decision quality only hides the problem temporarily.

The teams that seem steadier with AI tend to approach it differently. They stay with uncertainty long enough to name constraints, surface trade-offs, and accept what is not yet resolved. Only after that work is done does AI become useful, not as a substitute for judgment, but as a way to challenge it.

If this feels uncomfortably familiar, it may be a sign the decision needs more framing, not better tools. That kind of clarity is rarely created alone. If you want to talk through where AI is genuinely helping your thinking and where it might be masking uncertainty, I am open to that conversation.