Most GTM teams are using AI now.
That part is no longer interesting.
The real question is whether AI is helping teams make better decisions, or just helping them produce more stuff faster with weaker thinking behind it.
That was the core of the discussion Mark Stouse and I had during our Causal GTM Leader chat on LinkedIn last week (formerly The Causal CMO).
We renamed this series because GTM is a system. Marketing alone was too narrow a lens. Sales, CS, Product, Finance, and the C-suite all belong in the conversation.
Here’s the recap.
When pressure rises, cognitive load rises. When cognitive load rises, people look for the easier path.
That’s where AI adoption gets dangerous.
We are starting to see a lot of evidence... about people surrendering cognition. They’re basically saying, “That’s what AI said, and I’m just going to accept it, believe it, and hope that it’s true.”
Microsoft Research surveyed 319 knowledge workers and found that higher confidence in Gen AI is directly associated with less critical thinking. The more people trust the output, the less they question it.
There is a second problem underneath that one.
People also resist AI that challenges their assumptions. Teams complain about sycophantic AI, but every time developers try to stiffen the spine of these tools, users push back.
We say we want to be challenged. We usually don’t.
The old leadership rule applies: delegation is not abdication. You still own the output. You’re still on the hook for what you’re accepting.
You can’t say the software made me do it.
Gen AI is commonly used for asking things like, What should we do? What’s the best path? That is exactly what it cannot answer reliably. The algorithms inside Gen AI tools fundamentally can’t do that.
Why? Because success is not patterned.
Our outside environment controls 70 to 80% of whether it’s successful or not, and that is constantly changing. Full stop.
Failure, however, is heavily patterned. That is where Gen AI earns its place. Feed it a strategy document and you can punch holes in the logic, surface weak assumptions, and de-risk the plan before you execute.
In a recent example, Mark stress-tested a new strategy for a CMO and CRO. The findings made the boardroom uncomfortable and created pushback. But because the logic was legit, the CEO and CFO were okay with it.
De-risk first. Then execute.
Where Gen AI pattern-matches the past, Causal AI tracks what is actually driving outcomes now.
Mark uses a compass rose as an analogy:
Gen AI operates roughly 100 degrees off true north because it cannot model the external environment. Causal AI gets to around 5 degrees off, and keeps updating. It’s perpetual. Like a GPS. You still have to stay on top of it. You can't use either one as a static snapshot.
We went into the decision logic behind this previously in The Decision Layer.
A lot of AI adoption still rides on a cost-cutting premise: replace people, produce more, spend less.
The narrative around Gen AI has gone way off track.
This whole idea of efficiency and low cost and replacement of people... is just crap.
Why? Because the price end users pay today is heavily subsidized.
The fact that we can do whatever we do with ChatGPT for 20 bucks or even 200 bucks a month is astounding, but it is not real.
Reuters reported that OpenAI expects to spend $50 billion on computing power this year and is targeting roughly $600 billion through 2030. When that cost reaches users, the question changes. Not “how much can we automate?” but “which AI use cases are worth paying for?”
The answer is anything that is provably an improvement in effectiveness. Not output volume. Effective outcomes.
There is another cost in the headcount math.
When you cut the people who carry customer context and market judgment, and that knowledge was never captured, you do not get a leaner team. You get a team running AI on stale inputs with nobody left to question the output.
When the board says “do more,” GTM teams often hear: more activity, more channels, more volume.
That is not what the board had in mind.
The board means: I want more sales opportunities, a higher average selling price, a faster sales motion. I want those things for less money. They’re not talking about activity. And that difference is huge.
Activity metrics do not connect to the three things a CFO tracks: more deals, bigger deals, faster close. If your reporting cannot make that connection, you are speaking a different language.
More on this in GTM Reality Gap and The Causal Bridge.
If there was ever one thing every go-to-market leader needs to think about and take to next week, this is it:
Stop trying to make it all about channel optimization or delivery of the message. Start making it about THE message.
Markets are moving faster than GTM teams can adjust tactics. If you try to follow every shift, volatility turn times will defeat you. You end up fighting the last war.
The answer is evergreen customer strategy. Deep knowledge of what keeps your buyer up at night, what earns their confidence and trust over time.
FUD (Fear, Uncertainty, Doubt) has never been more prominent than now. Buyers want a reason to believe in you before they commit.
And THAT is a brand problem, not a demand problem.
The brand is demand.
They are converging fast. If you are cutting brand investment to fund more lead generation, that trade is working against you.
Write down and confirm what the board actually means by “do more”. More opportunities, higher ACV, faster close, lower CAC. Ask them.
Then check your current reporting against those outcomes.
If the connection is not clear, that is the conversation to have before the next planning cycle.
Missed the session? Watch it here.
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Cheers!
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