The Trust Gap Leaders Accidentally Create

Here's something that doesn't come up much in AI adoption conversations: the biggest risk isn't that your team resists the tools. It's that they stop caring whether the tools stick.

Those are different problems. And they need completely different solutions.

So I've been watching this pattern unfold a lot lately: a leader gets genuinely excited about AI (fair, the possibilities are real), ideas start coming faster than systems can catch up, and before long a new tool gets introduced before the last one got a real shot. A workflow gets rebuilt before anyone figured out the first version. And at some point, the team stops asking "is this useful?" and starts asking "is this still going to matter in six weeks?"

That question is the signal. Once it's in the room it's hard to undo.

What this actually looks like

It's not dramatic. Teams don't stage a revolt or send a memo. They just recalibrate.

Rollouts get less energy. Fewer people raise their hands to own something new. Announcements land flat. There's more "I'll wait and see" and less "let me start building." None of that is resistance; it's adaptation. The team has learned that effort doesn't always compound, so they're protecting themselves accordingly.

That distinction matters more than most leaders realize, because the solution to resistance and the solution to disengagement look nothing alike. If you're treating one like the other, you're solving the wrong problem entirely.

The thing that's actually exhausting

Every partially built system becomes something your team has to carry around in their head. Is this permanent? Should I learn it deeply? Will it still exist next quarter? Am I wasting my time right now?

That overhead adds up fast. And it doesn't show up on any dashboard.

Basically, when I get brought into teams that are technically well-resourced but operationally scattered, there's almost always a version of this underneath it. Something got built halfway, the next thing arrived before it matured, and now there are four half-built systems nobody fully trusts. The team isn't failing to execute. They're failing to attach - because attachment feels risky when the ground keeps moving under them.

The part nobody really says

Hear me out, because this one can land wrong if I'm not careful.

Sometimes the urgency around AI adoption isn't really about the AI. It's about the hope that a new tool might take the edge off pressure that was already there; unclear processes, communication that's broken down, decision-making that's gotten murky, teams scaling faster than the infrastructure supporting them. AI feels like forward motion. And forward motion feels good when the operational foundation underneath is heavy and unresolved.

That's not a character flaw. It's a completely human response to strain. But if you don't name it, you keep layering tools on top of problems the tools weren't built to solve and your team will notice before you do.

What trust actually needs from you

Credibility doesn't collapse in one moment. It erodes through a pattern of smaller ones. That's exactly how the trust gap opens. Not a blowup, just a slow accumulation of "I'll wait and see."

Ownership requires a belief that effort compounds. When people repeatedly watch systems get abandoned before they have a chance to mature, they stop investing deeply in the next one; not out of cynicism, but out of experience. They've learned to protect their energy. That's rational.

The goal isn't to move slowly. It's to create enough continuity that your team can move forward without bracing for the next pivot.

In practice: finish core systems before replacing them. Be explicit about what's a pilot versus a permanent shift. Give people enough stability to actually build confidence before you ask them to start over. Make "we're experimenting with this" and "this is how we operate now" mean different things.

None of that is anti-AI. It's just the difference between chasing the technology and actually deploying it in a way that sticks.

What I keep landing on

People do better work when they trust the ground won't shift mid-process. That's not a soft concept. It's a pretty operational one.

You can have great tools, a thoughtful rollout, and a team that genuinely wants to get this right, and still lose momentum if the pace of change outpaces the pace of trust.

So the question worth sitting with isn't "are we moving fast enough?"

It's "do our people believe that what they're building today will still matter tomorrow?"

If the answer is uncertain that's the real thing to fix. The good news is, it is fixable.

The Internet Belonged to Everyone Once. It Could Again.

I’ve been online long enough to remember Myspace. Like, actually remember it... the custom layouts, the top eight drama, spending forty-five minutes (at least) clicking through your favorite bands' pages while picking your profile song. Nobody was “building a personal brand.” We were just out here with our feelings and a dial-up connection, and somehow it felt like the internet belonged to us.

That feeling didn’t last, obviously. But I’ve been thinking about it a lot lately because - and I want to be careful about how I say this - I haven’t felt this excited about being online since then. Maybe more excited.

And the reason is AI.

I know. I know how that sounds.

So before I get into why I’m genuinely lit up about this moment in our lives, I want to talk about the part that’s harder, because I think it actually deserves more than a disclaimer.

AI data centers use a significant amount of water to keep their systems cool. That’s not speculation - it’s documented. And in some regions, that water draw is happening in communities that are already dealing with drought, already watching their aquifers drop. The people absorbing the biggest impact are often not the people seeing the biggest benefit. That’s a real harm. The displacement of creative workers through AI-generated content is also real. These aren’t things I’m interested in tucking into a footnote.

So where does that leave someone like me - someone who works in AI strategy and genuinely believes in what these tools can do?

It's a difficult question to debate with myself, but here’s where I keep landing: it leaves me with a responsibility, not a contradiction.

The solution to AI’s environmental footprint isn’t individual opt-out. Honestly, my personal decision to stop using (insert your own favorite LLM here) tomorrow would have essentially zero impact on a data center’s water consumption. That’s just the math. What actually moves the needle is policy, corporate accountability, pressure on the companies building this infrastructure, and real investment in better cooling technology. Those are the levers. Collective use doesn’t have to mean collective guilt, but it does mean we have to stay in the conversation, not check out of it.

What I can do - and what I think any of us operating in this space can do - is use these tools with enough intention that they actually earn their footprint. Not treating AI like a novelty. Not generating content just to generate content. Using it in ways that close gaps rather than widen them, especially for people who don’t have teams of consultants or agencies behind them.

And okay, here comes the part I get genuinely excited about.

What I’m watching happen right now reminds me of those early internet days, except the stakes are higher and (I really do believe this) the potential reach is bigger. The gap between what a well-resourced business can do and what a solo operator or small team can do is narrowing in ways that I did not even dream of seeing in my career. A blue-collar contractor who’s excellent at their trade but has never had a marketing team can now get real support building their proposals, their follow-ups, their whole client communication process. A first-generation entrepreneur who’s always had the ideas but never had the infrastructure can now actually build something that works.

Most people I talk to don’t realize yet what’s actually available to them. That genuinely surprises me every time.

I’m not naive about who captures these tools first - we’ve seen how tech rollouts go, and it’s not usually the people who need them most. But I’m not willing to hand the whole conversation over to the cynics, or to the people who’ve already figured out how to consolidate the gains for themselves. There’s real work to be done helping everyday people understand what’s available and how to use it in ways that serve their actual lives.

That’s the work I’m in.

That’s why I’m paying attention to the ethics - not because I want to perform accountability, but because the tools only live up to their potential if we’re honest about what they cost and intentional about how we use them. I’m excited about this moment. I also think it asks something of us. Honestly? I think that’s part of what makes it worth showing up for.

What An AI Consultant Got Right About Strategy on Big Brother (Even If the Twist Got Him)

This one’s for an audience that’s probably about three people wide, but here we are. I feel very moved to talk about how seeing an AI Consultant on Big Brother hit me in a specific way.

I’ve watched the show for more than a decade. I once threw myself a full Big Brother birthday weekend: competitions, secret meetings, a makeshift memory wall (fine, that was this year, when the premiere landed on my birthday, but whatever). I have a BB tattoo. I met one of my closest friends after bringing up a BB podcast at a music festival. I once sat next to Cory Wurtenberger’s brother in an Uber and spent the entire ride pretending to be so chill.

Ten years ago I watched Da’Vonne Rogers and Jason Roy on the live feeds. Their friendship was so easy it made me feel like I was in the room. I haven’t had that kind of parasocial hit since.

Every summer my schedule tilts around the show - episodes, podcasts, feeds. I’ll talk for hours about the reality of the season versus the edit. I’ll spend the warmer months debating best and worst moments like it’s an actual sport. I have strong opinions about production choices, season themes, and casting “flops” who deserve a second chance.

All of that to say, I really love Big Brother. But let’s get to the point.

Last year I added AI consulting to my work. The tools help, sure, but most of it’s just paying attention. You hear what people say they want, you watch what they actually do, and you notice the gap between the two. Then you figure out how to close it without breaking the rest of the system.

So when Jimmy introduced himself in the BB27 preseason as an AI Consultant, I flinched. Not because I doubted him, but it’s weird seeing your relatively new job title on TV. Hearing my favorite podcasters speculate what it actually means, knowing in the back of my mind that day-to-day his job is basically training for this game. Read the room, track patterns, act at the right time. I wanted to cheer but mostly I just sank lower into the couch cushions.

Then I watched him play.

Week two the house went dark - literally. Jimmy won the Black Box HOH, a pitch-black maze where most players stayed locked on their own puzzle task. He not only navigated it cleanly, he clocked Kelley pocketing a power in the dark. That’s high-level awareness: catching the quiet move while you’re still in motion.

With power in hand he targeted the solid early threat in Keanu. Spotting comp potential and momentum was a good read, even as the week was swallowed by extra powers. When Keanu and Kelley both saved themselves, the week turned into a minefield. Twist powers forced two renoms, meaning Jimmy ultimately put five different people up for eviction during his HOH reign. He pivoted to a safer choice of nominating Amy and Will - a decision that frustrated some of his alliance but kept him in line with broader house consensus. It wasn’t the biggest move, but it was one that kept his threat level low in a week where overreach could have blown up his game.

Good consultants read the flow of information before acting on it. From the start, Jimmy positioned himself where those currents moved. In week one, he linked up with Mickey and Morgan to form Triple Threat - the first named alliance of the season - and built lines into a larger voting group. He also built a genuine connection with Rachel, giving him a personal link outside the core that could feed intel and offer cover if the main alliance fractured. That’s network design, not noise, and it’s the kind of foundation that can carry you deep.

By week three, the house was still wobbling from the early-game chaos. Triple Threat was showing cracks: Mickey wasn’t fully looping Jimmy in, Morgan was exploring side channels, and the larger voting bloc he’d tapped in week one hadn’t solidified. Bonds like his with Rachel were genuine but untested under real vote pressure. And players were already floating aggressive moves before jury, chasing short-term momentum in ways that risked alienating multiple factions. In that climate it was easy for the wrong read to take hold.

Mickey gained control via the last twist on the board, mistook Jimmy’s visibility for disloyalty, and cut him - the kind of misread that tanks a strategy before it has a chance to pay off. He was evicted this past Thursday. The irony: he was one of her most loyal allies, and removing him was a short-term win for her but likely a long-term loss.

Jimmy left with the right reads, the right allies, and the ability to spot a hidden power in the dark. You can make the right read and still lose to timing, twists, and feelings. That’s not an excuse; it’s the job. Strategy lives in the gap between what should happen and what people actually do.

Seeing “AI Consultant” in a house built on chaos didn’t make the work feel loud. It made it feel accurate. The edge isn’t the tools; it’s knowing when to speak, when to wait, and spotting the one thing no one else in the dark is paying attention to.

I started the preseason wary, but from his intro package on night one I was in Jimmy’s corner. He had the reads, the measured play, and the network instincts that could have carried him deep. It’s such a loss to see him cut so early. Not because of bad reads but because of timing, paranoia, and a twist-heavy board. The season is a little less sharp (and a lot less fun) without him in it. I’ll be watching for the next time an AI Consultant ends up on a social strategy reality show. I don’t think I’ll have to wait long.

Jimmy didn’t get the ending he wanted. But the way he played - steady, directional, and early to structure - looked a lot like real life to me.

Maybe we’re all just trying to read the room a little better.