Why Do People Quit Bosses, Not Jobs? | Neuroscience in AI| AI For Executives - AI Cafe Conversations | Neuroscience, Neuroleadership, and Human-Centered AI for Executives

Episode Transcript
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SPEAKER_00 (00:12):
People don't just quit buses.
Sometimes buses get pushed outby their own organization.
After trusting an AI-generatedrecommendation that turned out
wrong.
They followed the confident,fluid answer the tool gave them,
made the call, and when itbackfired, the organization

(00:32):
blamed the human.
Not the process that put anunverified AI answer in front of
a decision maker in the firstplace.
The reason this cuts so deep isnot political, it's
neurological.
Betrayal by your ownorganization activates the same

(00:53):
brain regions as physical pain.
And once that circuit fires, anapology does not reverse it.
This episode is for twoaudiences at once.
If you are the manager livingthis right now, you will get
language for what happened toyou and a real starting point.
And if you are the one decidinghow your organization treats

(01:16):
leaders who trust in a tool theorganization itself rolled out,
you will get a clearer pictureof what the decision actually
costs you long term.
So why the old saying needs anAI era update?
You have heard it a hundredtimes.
People quit buses, not jobs.

(01:36):
It's usually told fromunderneath.
The employee who finally hadenough of a manager who never
listened, never protected them,never had their back.
Before I go further, my name isSahar Andradi.
I am a neuroleadership coachwith a medical background.
This is AI Cafe ConversationsSeason 5.

(01:58):
We are the only podcast where weintegrate AI, neuroleadership,
or neuroscience, and leadership.
Thank you for being here.
Thank you for your support, andthank you for making us one of
the top 2% global podcasts.
I appreciate you.
So, again, going back to the oldsaying that needs an AI era

(02:20):
update, there is a version ofthis happening right now that
the old saying doesn't cover atall.
A manager using an AI tool, thecompany itself told him to use,
gets a confident, verywell-written recommendation.
He trusts this, he acts on it.
It's wrong.
And when it comes out, he is notjust wrong, he is scapegoated,

(02:44):
treated as if he personallyfailed, when the actual failure
was a process that handed him afluent, confident answer, and
never taught him or anyone elseto question it.
This is the conversation almostnobody has outlined.
Because admitting you trustedthe tool that turned out wrong

(03:07):
feels like admitting you werenot careful enough.
But the neuroscience herematters more than the shame
does.
So let's get into it.
There is a well-known findingworth knowing here.
Research on AI-assisted decisionmaking has found that people
accept incorrect AI-generatedanswers more than 80% of the

(03:32):
time.
I see it every day, by the way.
And rate themselves as moreconfident when they did not
less.
That's not a character flow inthe people it happens to.
That's what fluent, fast,confident sounding output does
to the part of your brain that'ssupposed to stay skeptical.

(03:56):
It goes quiet because fluencyreads as truth to a brain that's
tired, busy, or under pressureto move fast.
Remember, I always say this AIsuggests human design.
No matter how much I like myAIs, no matter what I use Claude
or Chat or whatever, I nevertake the first answer.

(04:19):
I never take it for granted.
I keep pushing, dig at leastfive levels down to get the
proper answer.
It's not about just acceptingwhat is different.
So why trust ruptures hit thebrain like an injury?
Here is what most leadershipadvice skips entirely.

(04:40):
Trust isn't a relationshipconcept, it's a nervous system
event.
When you are betrayed by peopleor systems you counted on,
including a tool your owncompany rolled out and told you
to rely on, the brain processesthat experience through the same
circuitry involved in physicalpain.

(05:01):
This is not a metaphor.
Social pain and physical painshare overlapping neural
pathways.
That's why betrayal doesn't justfeel bad emotionally, it
registers in the body as anactual injury.
The same way a sprained ankleregisters as an injury.

(05:23):
Complete with the instant toprotect the injured part and
avoid putting weight on it againtoo soon.
This matters because it explainssomething leaders get wrong
constantly.
They expect trust to reset theway a disagreement resets with

(05:43):
an apology, a meeting, maybe apolicy update about how to use
the tool going forward.
But an injury doesn't healbecause someone said sorry.
It heals through repeated,consistent evidence that the
environment is safe again.

(06:04):
That takes time, yourorganization usually isn't
willing to give a manager who'salready been quietly labeled as
the person who trusted the tooland got it wrong.
There is a reason this specifickind of wound is so hard to talk
about openly too.

(06:24):
Admitting you were betrayed by aprocess, your own organization
built and endorsed meansadmitting you trust a system
that lets you down.
And for a lot of leaders, thatadmission feels more exposing
than admitting a straightforwardmistake would.

(06:49):
A mistake is something you canfix next time, but a betrayal is
something that changes how safethe entire environment feels
going forward, tool included,and that's much harder thing to
sit with in a performancereview.

(07:12):
Let's discuss the manager whogets scapegoated because they
pay the same price.
This is where the quid bosses,not jobs, conversation needs to
widen for right now.
Managers are being toldconstantly to use AI tools to
move faster and decide faster.
When a decision made with thattool's help goes wrong, the

(07:37):
organization needs somewhere toput the discomfort.
Often, that somewhere is themanager who trusted the tool,
not the leadership team thatrolled it out without ever
teaching anyone how to questionit.
Trust with leadership erodes,goes away.

(08:00):
Reputation takes a hit thatoutlasts the actual incidents by
a long distance.
And here is the detail thatmatters most.
This is not a one-time cost,it's the kind of thing that
costs someone four years.
That's not an exaggeration.
That's the nervous system doingexactly what it's built to do.

(08:24):
Once a threat has been logged ina specific context, in this
case, this organization, thistool, this leadership team, the
brain stays on alert in thatcontext far longer than the
original event would seem tojustify.

(08:45):
This is not weakness, it'sprotection.
The circuitry that's supposed tokeep you safe doesn't know the
difference between vigilancethat helps you, and vigilance
that's now costing you youreffectiveness.
Quitely making you slower totrust the next AI

(09:07):
recommendation, slower to make aconfident call at all, slower to
do the exact kind of decisivework that made you a good
manager in the first place.
And here is what makes thisparticular betrayer so corrosive
compared to other workplaceconfidence.

(09:30):
It doesn't come from a peer or acompetitor, it comes from the
very structure that told you totrust the tool in the first
place and then blamed you fordoing exactly that, what you
were asked to do.
When the threat comes frominside the system you were
relying on for safety, thenervous system doesn't have a

(09:52):
clean outside enemy to organizearound.
It has to hold the unsettlingreality that the instruction and
the punishment came from thesame place, a place that we
stopped, that we trusted.
So, how to tell if this ishappening to you right now?

(10:14):
If you are not sure this is yoursituation, here are the signals
worth paying attention to.
You notice you're being left outof meetings, you used to be
automatically included in.
Colleagues who used to loop youin decisions start looping you
in after the fact instead or notat all.

(10:35):
Your instance start telling youto document everything, every AI
output, every email, everyconversation, in a way that
feels less like diligence andmore like self-protection.
And underneath all of it, younotice a specific kind of

(10:56):
exhaustion that doesn't comefrom workload, it comes from
constantly, quietly scanning theroom to see who's still actually
on your side.
None of these signals aloneproves anything.
Organizations are messy and notevery exclusion is a message.

(11:21):
But when several of these showup together following a specific
incident where you made adefensible call using a tool
your organization endorsed, thatpattern is worth naming honestly
rather than explaining away.

(11:41):
So what actually protectsagainst this?
The deeper problem underneathall of this isn't one bad AI
assisted call.
It's an organization that rollsout AI tools without building a
real process for verifyingoutput and without a real
process for fairness when adecision made with that tool

(12:04):
goes wrong.
Without that, every manager istrusting the tool alone, under
pressure, with the full weightof the consequences lending on
them personally if it goessideways.
This is exactly the terrain mybrain, B-R-E-I-N framework was

(12:28):
built to address, giving leadersa way to make these calls from
regulation instead of blindtrust.
And now you know what the R isregulation instead of blind
trust in a confident soundingoutput and giving organizations
language for accountability thatdoesn't default to finding one

(12:49):
person to blame for a systematicgap.
If you are the manager who gotburned this way, here is the
practical starting point.
Name what happened plainly toyourself first.
Not I was careless, if that'snot actually true, but I used a
tool exactly the way I was toldto.

(13:13):
The tool was wrong, and theorganization needed someone to
hold that outcome, and it landedon me.
The distinction matters becauseyour nervous system needs
accuracy to stop treating everyfuture decision, AI assisted or
not, as equally dangerous.

(13:36):
Then rebuild trust deliberatelyrather than waiting for it to
happen on its own because itwon't.
Pick one or two people whosetrust actually matters to you
professionally and create smallrepeated moments of consistency
with them.
Trust rebuilds through pattern,not through explanation.

(13:59):
A single well-wordedconversation will not undo a
month of quiet suspicion.
Ten small, reliable moments over10 weeks will do more than any
single meeting ever could do.
Because the nervous systemtrusts repetition far more than
it trusts a good speech.

(14:21):
And give yourself permission togrieve the version of the
relationship you had with thatorganization before this
happened.
That sounds dramatic, I know,for a workplace issue, but it
isn't.
You trusted a structure to holdyou if you used its own tool the
way you were told to, and itdidn't.

(14:42):
Naming that loss honestlyinstead of pretending it didn't
matter is often what actuallyallows the vigilance to soften
over time.
If you are the one further upthe chain, watching a manager go
through this, there is a directrole for you too.
A single private conversationacknowledging that the call was

(15:05):
defensible given the tool andthe instructions provided, even
if the outcome was bad, doesmore to interrupt this pattern
than any policy document everwill.
Managers who feel unfairlyblamed rarely say so out loud.

(15:25):
They simply become morecautious, less willing to trust
the next rule, and eventuallyless willing to stay.
If you want managers who makegood judgment calls under
pressure, including judgmentabout the question and AI
recommendation, you have to bewilling to defend those calls
publicly when they don't goperfectly, not just when they

(15:48):
succeed.
So the pushback beat, now someof you are thinking, isn't this
just accountability?
If a manager trusts a toolwithout verifying it, shouldn't
there be consequences?
Yes, there should beconsequences when a decision is
generally negligent.
When someone had a clear, easyway to check the output and

(16:09):
simply didn't bother.
But that's not what most ofthese stories describe.
Most describe a manager doingexactly what the organization
told them to do.
Using a tool the organizationrolled out and endorsed with no
training on when to double-checkit and no process for catching a

(16:30):
wrong answer before it causeddamage.
The distinction matter becauseorganizations that can tell the
difference between negligenceand a defensible call made with
company-endorsed tools end uptraining every manager in the
building to stop trusting any AIassisted process at all.

(16:56):
Or worse, to stop makingconfident calls at all.
That's not accountability,that's a slow erosion of the
exact judgment leaders need toexercise under pressure.
And it teaches an entire layerof management that the safest
move is never to advocate for adecision, which is precisely the

(17:21):
opposite of what mostorganizations say they want from
their leaders in an AI adoptionmoment.
There is a version of thispushback aimed at the manager
too, not just the organization.
If this is you, you might betelling yourself that you should
have known better, that youshould have double-checked the

(17:42):
AI output, that a moreexperienced leader wouldn't have
made that call.
Be careful with that story.
Hindsight makes every defensibledecision look obvious in
retrospect.
The information you had in themoment, including the
organization's own instructionto use and trust the tool, is

(18:05):
the only fair measure of thedecision.
Not the information that becameavailable after everything
unfolded.
If you have been the manager whogot burned for trusting AI
recommendation the organizationitself endorsed, or the one
still carrying the afterstate orthe aftertaste of a trust

(18:29):
structure that never gotproperly repaired, you are not
imagining the cause.
It's real, it's neurological,it's fixable with the right
approach even years after theoriginal incident.
This is also worth sayingplainly for anyone building or
running a leadership team rightnow.
The old saying tells you thatpeople quit buses, not jobs.

(18:51):
The AI era version is that trustbreaks in both directions.
And an organization that throllsout AI tools without a real
process, both verification andfairness, is quietly training
its best manager to stoptrusting anything, including

(19:12):
their own judgment.
Not sure where you stand.
Have a leadership clarity callwith me.
It's free, 30 minutes, no pitch,just clarity.
I will leave the link in thenotes of description of this
episode.
And as I always say, before weleave, show me some love,

(19:35):
comment, share, subscribe, rateour podcast.
Appreciate your support.
Thank you so much for alwayssupporting me and being here and
listening to this.
If you have any ideas, email meat sohar at soharconsulting.com.
Till I see you on our regularlong podcast on Wednesday next

(19:59):
week.
Peace out.

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