September 10, 2025 • 25 mins
Join Sahar, The AI Whisperer, and her skeptical executive husband Joe in this episode of AI Café Conversations as they explore the neuroscience behind AI learning speed for executives. Discover why some executive brains adapt to AI quickly while others struggle, using brain science insights that require no technical knowledge.
Through real workplace examples and conversational dialogue, learn how cognitive flexibility, neural plasticity, and executive brain architecture affect AI adoption speed. Sahar explains the neuroscience of learning differences while Joe represents every skeptical leader wondering "Why am I so slow at this AI stuff?"
Perfect for executives, HR professionals, and business coaches seeking to understand AI learning challenges in leadership development. This episode provides practical, brain-based strategies for accelerating AI adoption without overwhelming executive teams.
Key topics include executive brain patterns, AI learning anxiety, neural rewiring for technology adoption, and organizational strategies for different learning speeds. All insights are presented in accessible, non-technical language designed for busy executives.
Ideal for leaders implementing AI coaching tools for executives, those struggling with AI integration, and anyone interested in the neuroscience of executive decision-making and technology adoption.
Subscribe to AI Café Conversations for weekly neuroscience insights that help executives master AI while maintaining human-centered leadership. No tech background required - just curiosity about how your brain works with AI.
This episode is designed for executives, HR professionals, and coaches who see the urgency of AI adoption but want it to align with human connection, not replace it.
Email me at sahar@saharconsulting.com with questions or topic suggestions for future episodes.
My book "The Coach's Brain Meets AI" is available on Amazon, and I'll send extra guides if you email me after purchasing. Follow me on LinkedIn (Sahar Andrade) and Instagram (Sahar the Reinvent Coach).
Subscribe now to start transforming your leadership with Human-Centered AI!
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Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:13):
Hello, hello, hello and welcome back to AI Cafe
Conversation on this beautifulWednesday morning.
I am Sahar, your AI Whisperer,and I'm here for those who have
been watching their colleaguesnavigate AI with very different
results.
Let me tell you, every singleday I'm seeing different
(00:35):
organizations, different leaders, different attitudes, different
results, different thoughts,different processes, thoughts,
different processes, and it'samazing because all of us are
sometimes looking at AI fromdifferent point of view, from
different approaches, because,remember, ai is still it's in
infancy and we are stillbasically scratching the surface
(00:58):
of what we can do.
But that's why I'm reallymarrying AI with neuroscience,
because I want always to base iton facts, not on maybe or maybe
, an assumption or a perception.
I really want to always kind ofbase it on neuroscience because
, maybe, because it makes senseto me.
(01:20):
So today I'm going to startthis by saying that one of my
clients told me that it wasagain like I said, everybody
looks at AI from differentpoints of view, and my client,
like I was saying, told me it'sfascinating but frustrating at
the same time.
Their business partner pickedup ChatGPT in two weeks and now
(01:45):
uses it for everything I do too,I have to confess.
Anyhow, meanwhile, their cfohas been learning it for six
months six months and stilltreats it like a fancy search
engine.
And, by the way, this isprobably 80 percent of the
people that are using um eitherchad, gpt or um or cloud or
(02:08):
perplexity or meta whatever yourheart desire as a platform for
ai.
They're using it as asophisticated google search and
this is so not what it'sdesigned for.
Okay, so we all use the same AItool and we could have the same
training, but completelydifferent outcomes.
(02:30):
And does that sound familiar tomy executive listeners?
Why?
Because it's not aboutintelligence.
For example, the CFO in thatcompany is brilliant.
He's a Harvard graduate, mba,cpa and all the abbreviations
that you want at the end of thename, and he runs a complex
financial model.
(02:51):
But put him in front of ai andhe's like a deer in a headlight,
and by again, he's not the onlyone, so there is no shame in
that.
I see it every single day.
This is one of the most commonquestions I get from executives
why do some of my people get AIimmediately, while others
struggle for months?
And the answer here is, again,pure neuroscience.
(03:14):
So it's not about being techsavvy and it's not about being
young, a Z generation or an Xgeneration or a Y generation?
All the alphabet letters, right?
It's not about that.
Those factors are important,especially for the younger
generation that grew upbasically as native digital,
(03:35):
that internet and all that ispart of of their dna.
It's like an appendix to them,but they are quite factors, but
they're not the primary drivers,though.
Your brain's learningarchitecture, how your neural
pathways are structures fromdecades of experience,
determines how quickly you adaptfor ai.
(03:57):
So some brains are just betterat learning AI.
Some brains are structured inways that make AI learning feel
natural.
Others have neural patternsthat create resistance, and
that's what we see a lot,especially within the teams.
But here is the key Both can bechanged and, like you do and I
(04:23):
think again I'm going to keepbringing that up whenever we are
introducing ai and aiadaptation or integration, we
need to treat it as a changemanagement where 80 percent
factors is human and only 20percent processes, and not go
with the wrong assumptions ofchange management that 80
percent processes and 20 humanand that's when it fails, okay.
(04:45):
So both mentalities canactually be changed.
Today's we are diving into theneuroscience of AI learning
speed and how to accelerate it.
So, for example, something thatI observed in executives that
pick up AI quickly.
(05:05):
They seem kind of playful withit.
They go with an open mind.
It's like they're not afraid toexperiment.
They will try weird prompts,try different approaches, laugh
when it gives them weird results.
And these are like actually wesee it, and they are the perfect
observations that we have beenseeing between the different
(05:26):
executives, because thoseexecutives have what
neuroscience call high cognitiveflexibility.
Their brains easily switchbetween different mental
frameworks.
So what does actually that mean?
Their prefrontal cortex, againin the front of the brain, like
around our forehead, or thebrain's executive center, has
(05:49):
strong connections betweencreative and analytical regions.
They can shift from structuredthinking to experimental
thinking without stress.
So the question is are theymore naturally adaptable?
The brain architecture supportswhat we call divergent,
convergent thinking cycles.
(06:11):
They can brainstorm widely withAI, then organize the results
logically.
This is how the brain works.
It's like having mental gearsthat shift smoothly, like if you
ever drove a stick shift car.
That's how I started driving.
On a stick shift car you candownshift or upshift, you know,
(06:31):
depending on how fast, how slowand how much control you want to
have on driving a stick shiftcar.
So why do some executives havethis and others don't?
It usually comes from careerexperiences that require
constant adaptationEntrepreneurs, consultants,
people who have worked acrossindustries.
(06:54):
Their brains build flexibilityneural pathways naturally in
their brain Remember it'sneuroplasticity Neurons that
fire together, work together.
They created pathways thatconnect together by repetition.
And that's what we say when youdo something for at least six
weeks, like habits, they becomeautomatic.
(07:18):
Some of the people that areexecutive and using the AI, I
can see them that through theircareer they moved from one level
to the other or even throughdifferent industries.
Their brain learned thatchanging approaches leads to
better outcomes and when theyencounter AI, those same neural
(07:40):
pathways activate.
Experimentation feels familiar,not threatening.
So people sometimes ask meweird questions like is it a
personality thing?
Are extroverts better than AI,which I find really interesting
questions.
When it comes to AI, becauseagain, it's a kind of
intelligence, it's less aboutextroversion and more about what
(08:02):
psychologists call openness toexperience.
They're open to experience.
Some introverts are incrediblyopen to new ideas and learn AI
fast.
They just don't show it outside.
Okay, there are even peoplethat are introvert extrovert.
You know there is a lot ofvariations, variations of
between that.
So it's not about being open oroutgoing.
(08:29):
It's not really about that, butopenness correlates with
neuroplasticity how easily yourbrain forms new connections.
High openness, executive CAI isas interesting, not intimidating
.
It depends how you look at it,and that's what I always say.
When we approach something newthrough our curiosity, what it
(08:55):
does, it opens the door to ourproblem-solving center in the
brain.
Because two things cannot go atthe same time.
I cannot be fearful ofsomething and curious at the
same time.
Okay, one of them will takeover.
So if I have fear, I havecortisol in my brain, I'm
(09:16):
stressed, I cannot thinkstraight and I cannot learn
anything.
But when I approach it for like, hmm, let's see what, where
that can go, do I win?
Do they win?
If we come from a curiositypoint of view, right away,
analytical thinking and problemsolving centers will open.
So it becomes more, like I said, interesting and not
(09:37):
intimidating.
I don't know if you can measureit, but there are indicators.
For example, fast AI learnerstypically ask what if questions?
They enjoy puzzles, they havehobbies outside work and view
failures just as data ratherthan defeats.
It's like when I fail intosomething, I laugh and I'm like,
(09:59):
haha, now I know what not to dookay, and I would avoid that
next time I say it's like oh mygod, I I failed, I'm not good,
like I'm not worthy, blah, blah,blah, I don't do that, okay.
It's all about how we look atfailures.
So let's talk about executiveswho struggle with AI.
What patterns do we see in them?
They seem careful, almostparalyzed.
(10:20):
They want to understand exactlyhow it works before they will
use it.
They have their conditions,like they want to be in control,
right?
They ask lots and lots ofquestions about reliability and
accuracy.
I don't blame them, but stillclassic science of what we call
analytical dominant brainarchitecture.
These executives haveincredibly strong systematic
(10:44):
thinking pathways, but theydon't know weaker exploratory
connections.
They are too logical for AI.
Not really, they're not toological, but their brains are
wired for sequential,predictable processes.
Again, it's about control.
Ai learning requires iterative,experimental processes that feel
(11:06):
chaotic to systematic thinkers.
They need to understand themethodology before trusting any
tool.
Their brain excel at structuredanalysis but struggles with
ambiguous inputs.
Ai responses vary.
Sometimes they even hallucinateOkay, not perfect and they
(11:31):
require interpretation.
This triggers their brain errordetection systems.
Remember we never takeeverything AI takes up for
granted.
We are the human brain here weneed to look at it, think about
it, think about our experience,the pros and cons, and maybe add
(11:52):
and push back, and this is theonly way we can get accurate
results that we want to have.
So sometimes the strength is theweakness actually, of the
person that just wants to seewhatever AI is doing only
through the error detectionsystem.
Their analytical rigor, whichmakes them brilliant at
(12:16):
financial modeling, for example,creates resistance to AI's
probable nature.
Their brain interpretsinconsistency as being
unreliable.
I'm not saying this is likewrong way of thinking or this is
being stupid, but because theseexecutives run very complex
(12:38):
organizations.
They are extremely, extremelysuccessful, but their cognitive
architecture is perfectlydesigned for traditional
executive tasks strategicplanning, risk analysis,
systematic decision making.
Ai just requires differentneural pathways.
And what makes them struggle?
(12:58):
Several factors perfectionistneural patterns that resist
trial and error learning, riskaversion circuits that interpret
AI uncertainty as danger, andexpertise bias that makes new
learning feel threatening toidentity.
And you might tell me what?
(13:21):
Expertise bias?
What is that?
When you are an expert intraditional methods, your brain
resists tools that might revealknowledge gaps.
Remember control Learning AImeans admitting there are better
ways to do things you havemastered, so it can be, or can
(13:47):
seem threatening to someone whobuilt their career on specific
expertise, because their brain'sidentity protection system
fights against adoption toolsthat might take their
hard-earned knowledge.
That can make them obsolete.
But here is the encouragingnews Neuroplasticity means slow
(14:13):
learners can become fastlearners with the right approach
, which means that we canactually rewire a brain for AI
learning.
The brain builds new neuralpathways throughout life.
It just requires intentionalpractice that works with your
(14:33):
existing architecture instead ofagainst it.
Work with it, not against it.
Less resistance.
And how does that workpractically For systematic
thinkers like the CFO I wasdiscussing in the beginning of
the podcast?
Start with structured AIexperiments Instead of play
around with chat, gpt.
(14:54):
Give them specific prompts totest with measurable outcomes,
and that can help make AIlearning feel like a controlled
experiment.
Where they feel still they havecontrol, their analytical brain
needs frameworks.
(15:14):
So create AI protocols thatthey can follow systemically.
Once they see consistentpatterns, their trust circuits
will activate.
And you might ask but whatabout the perfectionist
executive who hate makingmistakes?
We can reframe mistakes as datacollection Instead of I got a
(15:36):
bad AI response.
Maybe try to start.
Make them think I collecteduseful information about prompt
effectiveness.
Change the language to changethe brain response.
Remember words have power.
Okay, change your words, youchange your word.
Languages shape neural pathways.
(15:58):
Experiment feels lessthreatening than trial and
errors.
Iteration sounds moreprofessional than playing around
than playing around.
So there are something specificexercises to build AI learning
speed so we can start with whatwe call micro experiments five
(16:20):
minutes AI tasks with clearsuccess metrics.
This builds confidence pathwayswithout triggering overwhelmed
circuits like baby steps for thebrain.
Perfect analogy is that eachsuccessful micro experiment
releases dopamine, reinforcingAI engagement, and over time
(16:43):
these small wins build largerconfidence neural networks.
You might ask how long doesrewiring take?
It varies actually byindividual, but neuroplasticity
research suggests thatsignificant pathway changes in
30 to 60 days with consistentpractice.
The key is daily engagement,even if brief.
(17:06):
That's basically creating newhabits.
Remember, and if you add anextra layer on the consistent
practice and have triggers likeput yourself a stick on notes on
uh on your desk or have ascreensaver or put an alarm on
your phone at certain times toremind you of something like
quick proko, like a trigger thatwill let you go and do that
(17:29):
five minute or micro experiment.
So 15 minutes daily beats threehours weekly for neural pathway
development.
Repetition is better thanduration.
Consistency builds strongerconnection than intensity.
So let's get practical, okay.
(17:49):
How can executives speed up AIadoption across their teams,
especially when they have amixed bag of facts, adopters and
holdouts?
Number one assess your team'slearning architectures.
Don't use one-size-fits-alltraining, which basically
everybody has been doing.
That's wrong.
(18:10):
Match AI introduction methodsto individual neural preferences
.
What does that mean?
Analytical thinkers needstructured framework and
measurable outcomes.
Creative thinkers needopen-ended exploration time.
Risk aversion personalitiesneed safety nets and supervision
(18:30):
.
Different approaches fordifferent brain types.
Your systematic, for example,cfo, like we discussed in the
beginning.
They need AI standard operatingprocedures.
The creative marketing directorneeds AI playground time with
no specific objectives, hope itmakes sense and how to build
(18:51):
confidence in slow adopter.
Create AI wins quickly.
Give them simple, low-risktasks where AI obviously saves
time, like email summarization,data organization, routine
analysis, reading report, excelsheets.
Routine analysis, readingreport, excel sheets.
(19:12):
So, building success beforecomplexity.
Each small success releasesdopamine and builds positive AI
associations.
Start with tasks thatcomplement their existing
strength, not challenge them,and I know that some executives
(19:33):
have some fear factor.
They worry that AI will replacetheir jobs.
We need to address thisdirectly with neuroscience.
Explain or explaining that AIaugments executive capabilities
like strategic thinking,relationship building, creative
problem solving that AI can'treplicate.
This is human skills that AIcannot replicate.
(19:56):
That no matter what executivewill have those very unique
skills.
So position AI as a power tool,not competitor.
We are complemented by AI.
We collaborate with AI and wedon't compete with AI.
Frame it as AI helps you domore of what only humans can do
(20:20):
by handling what machines dowell.
This reduces threat responseand activate curiosity circuits.
So some of the specificorganization strategies that I
use is I use peer learning.
Accelerates adoption.
Pair fast learners with slowlearners, not as teachers, but
(20:41):
as learning partners.
Remember, like mentoring andreverse mentoring, social
learning activates differentneural pathways than individual
studies.
Body systems for AI learninganyone but structured body
systems give pairs specificchallenges to solve together.
Collaboration reducesindividual performance, anxiety
(21:02):
while building collectivecapability.
And how to measure progress?
And how do we know if therewiring is working?
We track behavioral indicatorsfrequency of AI tool usage,
complexity of tasks, attemptedcomfort with imperfect output
(21:23):
and willingness to experimentwith new prompts.
Practical metrics instead ofjust surveys, because the neural
pathway changes show up inbehavior before people
consciously recognize them.
Usage patterns reveal brainrewiring better than
(21:44):
self-reporting.
So let's create a simpleprotocol executives can use to
speed up their own AI learning.
So let me give you somethingthat can actually be implemented
.
Week one and two daily 10minutes structured experiments
(22:08):
same ai tool, same type of task,different approaches.
Build familiarity, neuralpathways, consistency and
repetition first.
Week three and four introducecomplexity gradually.
Add one new variable per week.
Different prompts, differenttasks or different tools.
(22:30):
Build flexibility circuitsslowly.
Do not overwhelm the system.
Week five and six integrationchallenges Use AI for actual
work problems, not practiceexercises.
This builds confidence andrelevance neural connections.
(22:51):
So now we move from practice toreal application.
Week seven and eight teachingothers Remember to real
application.
Week seven and eight teachingothers remember the best way to
learn something is to teach it.
Explaining ai approaches tocolleagues activates deeper
understanding pathways andreinforce learning.
And the final step basically,like I just explained, is
(23:12):
becoming a teacher yourself asan executive.
Teaching forces your brain toorganize AI knowledge into
transferable patterns.
It's the ultimate neuralconsolidation exercise.
So let me ask you this, guyswhat was your takeaway for
executive?
Wondering why AI learningspeeds vary so much?
(23:34):
And the answer is simple it'snot about intelligence or age.
It's about brain architecturebuilt from career experiences.
Fast learners have flexibleneural pathways.
Slow learners have systematicpathways.
Nothing, no one, is better thanthe other.
Okay, both can be changed withthe right approach.
(23:56):
Executive, remember yourlearning speed is not fixed.
Neuroplasticity means you canbuild ai fluency at any career
stage with intentional practice.
So don't judge everybodybecause they're being systematic
or about everything right.
(24:17):
The systematic brain isactually an asset, just needs ai
compatible frameworks.
Next week we are diving into aiproductivity paradox why more
ai tools can feel like lesscontrol.
Subscribe if you want tounderstand why some brains love
(24:37):
AI and others fight.
Show me some love Like.
Share this with someone else.
Subscribe to our podcast so youdon't miss any of the new
episodes.
This is Sahar, your AIwhisperer, signing off from AI
Cafe Conversations.
Your brain is more adaptablethan you think.
Any questions, questions, anycomments?
(24:58):
Please email me at sahar atsahar consultingcom Website,
sahar consultingcom.
My book the coaches brain meatAI is still On top new releases
on Amazon and is doing reallywell, is on the top 30 of three
different categories and I'mvery proud of it it and I hope
(25:22):
you like it.
I hope you get to read it andtell me what you think about it,
but for now I'm over and out.
See you next time.
One, two, three, four.
Hello, hello, hello and welcome back to AI Cafe
Conversation on this beautifulWednesday morning.
I am Sahar, your AI Whisperer,and I'm here for those who have
been watching their colleaguesnavigate AI with very different
results.
Let me tell you, every singleday I'm seeing different
(00:35):
organizations, different leaders, different attitudes, different
results, different thoughts,different processes, thoughts,
different processes, and it'samazing because all of us are
sometimes looking at AI fromdifferent point of view, from
different approaches, because,remember, ai is still it's in
infancy and we are stillbasically scratching the surface
(00:58):
of what we can do.
But that's why I'm reallymarrying AI with neuroscience,
because I want always to base iton facts, not on maybe or maybe
, an assumption or a perception.
I really want to always kind ofbase it on neuroscience because
, maybe, because it makes senseto me.
(01:20):
So today I'm going to startthis by saying that one of my
clients told me that it wasagain like I said, everybody
looks at AI from differentpoints of view, and my client,
like I was saying, told me it'sfascinating but frustrating at
the same time.
Their business partner pickedup ChatGPT in two weeks and now
(01:45):
uses it for everything I do too,I have to confess.
Anyhow, meanwhile, their cfohas been learning it for six
months six months and stilltreats it like a fancy search
engine.
And, by the way, this isprobably 80 percent of the
people that are using um eitherchad, gpt or um or cloud or
(02:08):
perplexity or meta whatever yourheart desire as a platform for
ai.
They're using it as asophisticated google search and
this is so not what it'sdesigned for.
Okay, so we all use the same AItool and we could have the same
training, but completelydifferent outcomes.
(02:30):
And does that sound familiar tomy executive listeners?
Why?
Because it's not aboutintelligence.
For example, the CFO in thatcompany is brilliant.
He's a Harvard graduate, mba,cpa and all the abbreviations
that you want at the end of thename, and he runs a complex
financial model.
(02:51):
But put him in front of ai andhe's like a deer in a headlight,
and by again, he's not the onlyone, so there is no shame in
that.
I see it every single day.
This is one of the most commonquestions I get from executives
why do some of my people get AIimmediately, while others
struggle for months?
And the answer here is, again,pure neuroscience.
(03:14):
So it's not about being techsavvy and it's not about being
young, a Z generation or an Xgeneration or a Y generation?
All the alphabet letters, right?
It's not about that.
Those factors are important,especially for the younger
generation that grew upbasically as native digital,
(03:35):
that internet and all that ispart of of their dna.
It's like an appendix to them,but they are quite factors, but
they're not the primary drivers,though.
Your brain's learningarchitecture, how your neural
pathways are structures fromdecades of experience,
determines how quickly you adaptfor ai.
(03:57):
So some brains are just betterat learning AI.
Some brains are structured inways that make AI learning feel
natural.
Others have neural patternsthat create resistance, and
that's what we see a lot,especially within the teams.
But here is the key Both can bechanged and, like you do and I
(04:23):
think again I'm going to keepbringing that up whenever we are
introducing ai and aiadaptation or integration, we
need to treat it as a changemanagement where 80 percent
factors is human and only 20percent processes, and not go
with the wrong assumptions ofchange management that 80
percent processes and 20 humanand that's when it fails, okay.
(04:45):
So both mentalities canactually be changed.
Today's we are diving into theneuroscience of AI learning
speed and how to accelerate it.
So, for example, something thatI observed in executives that
pick up AI quickly.
(05:05):
They seem kind of playful withit.
They go with an open mind.
It's like they're not afraid toexperiment.
They will try weird prompts,try different approaches, laugh
when it gives them weird results.
And these are like actually wesee it, and they are the perfect
observations that we have beenseeing between the different
(05:26):
executives, because thoseexecutives have what
neuroscience call high cognitiveflexibility.
Their brains easily switchbetween different mental
frameworks.
So what does actually that mean?
Their prefrontal cortex, againin the front of the brain, like
around our forehead, or thebrain's executive center, has
(05:49):
strong connections betweencreative and analytical regions.
They can shift from structuredthinking to experimental
thinking without stress.
So the question is are theymore naturally adaptable?
The brain architecture supportswhat we call divergent,
convergent thinking cycles.
(06:11):
They can brainstorm widely withAI, then organize the results
logically.
This is how the brain works.
It's like having mental gearsthat shift smoothly, like if you
ever drove a stick shift car.
That's how I started driving.
On a stick shift car you candownshift or upshift, you know,
(06:31):
depending on how fast, how slowand how much control you want to
have on driving a stick shiftcar.
So why do some executives havethis and others don't?
It usually comes from careerexperiences that require
constant adaptationEntrepreneurs, consultants,
people who have worked acrossindustries.
(06:54):
Their brains build flexibilityneural pathways naturally in
their brain Remember it'sneuroplasticity Neurons that
fire together, work together.
They created pathways thatconnect together by repetition.
And that's what we say when youdo something for at least six
weeks, like habits, they becomeautomatic.
(07:18):
Some of the people that areexecutive and using the AI, I
can see them that through theircareer they moved from one level
to the other or even throughdifferent industries.
Their brain learned thatchanging approaches leads to
better outcomes and when theyencounter AI, those same neural
(07:40):
pathways activate.
Experimentation feels familiar,not threatening.
So people sometimes ask meweird questions like is it a
personality thing?
Are extroverts better than AI,which I find really interesting
questions.
When it comes to AI, becauseagain, it's a kind of
intelligence, it's less aboutextroversion and more about what
(08:02):
psychologists call openness toexperience.
They're open to experience.
Some introverts are incrediblyopen to new ideas and learn AI
fast.
They just don't show it outside.
Okay, there are even peoplethat are introvert extrovert.
You know there is a lot ofvariations, variations of
between that.
So it's not about being open oroutgoing.
(08:29):
It's not really about that, butopenness correlates with
neuroplasticity how easily yourbrain forms new connections.
High openness, executive CAI isas interesting, not intimidating
.
It depends how you look at it,and that's what I always say.
When we approach something newthrough our curiosity, what it
(08:55):
does, it opens the door to ourproblem-solving center in the
brain.
Because two things cannot go atthe same time.
I cannot be fearful ofsomething and curious at the
same time.
Okay, one of them will takeover.
So if I have fear, I havecortisol in my brain, I'm
(09:16):
stressed, I cannot thinkstraight and I cannot learn
anything.
But when I approach it for like, hmm, let's see what, where
that can go, do I win?
Do they win?
If we come from a curiositypoint of view, right away,
analytical thinking and problemsolving centers will open.
So it becomes more, like I said, interesting and not
(09:37):
intimidating.
I don't know if you can measureit, but there are indicators.
For example, fast AI learnerstypically ask what if questions?
They enjoy puzzles, they havehobbies outside work and view
failures just as data ratherthan defeats.
It's like when I fail intosomething, I laugh and I'm like,
(09:59):
haha, now I know what not to dookay, and I would avoid that
next time I say it's like oh mygod, I I failed, I'm not good,
like I'm not worthy, blah, blah,blah, I don't do that, okay.
It's all about how we look atfailures.
So let's talk about executiveswho struggle with AI.
What patterns do we see in them?
They seem careful, almostparalyzed.
(10:20):
They want to understand exactlyhow it works before they will
use it.
They have their conditions,like they want to be in control,
right?
They ask lots and lots ofquestions about reliability and
accuracy.
I don't blame them, but stillclassic science of what we call
analytical dominant brainarchitecture.
These executives haveincredibly strong systematic
(10:44):
thinking pathways, but theydon't know weaker exploratory
connections.
They are too logical for AI.
Not really, they're not toological, but their brains are
wired for sequential,predictable processes.
Again, it's about control.
Ai learning requires iterative,experimental processes that feel
(11:06):
chaotic to systematic thinkers.
They need to understand themethodology before trusting any
tool.
Their brain excel at structuredanalysis but struggles with
ambiguous inputs.
Ai responses vary.
Sometimes they even hallucinateOkay, not perfect and they
(11:31):
require interpretation.
This triggers their brain errordetection systems.
Remember we never takeeverything AI takes up for
granted.
We are the human brain here weneed to look at it, think about
it, think about our experience,the pros and cons, and maybe add
(11:52):
and push back, and this is theonly way we can get accurate
results that we want to have.
So sometimes the strength is theweakness actually, of the
person that just wants to seewhatever AI is doing only
through the error detectionsystem.
Their analytical rigor, whichmakes them brilliant at
(12:16):
financial modeling, for example,creates resistance to AI's
probable nature.
Their brain interpretsinconsistency as being
unreliable.
I'm not saying this is likewrong way of thinking or this is
being stupid, but because theseexecutives run very complex
(12:38):
organizations.
They are extremely, extremelysuccessful, but their cognitive
architecture is perfectlydesigned for traditional
executive tasks strategicplanning, risk analysis,
systematic decision making.
Ai just requires differentneural pathways.
And what makes them struggle?
(12:58):
Several factors perfectionistneural patterns that resist
trial and error learning, riskaversion circuits that interpret
AI uncertainty as danger, andexpertise bias that makes new
learning feel threatening toidentity.
And you might tell me what?
(13:21):
Expertise bias?
What is that?
When you are an expert intraditional methods, your brain
resists tools that might revealknowledge gaps.
Remember control Learning AImeans admitting there are better
ways to do things you havemastered, so it can be, or can
(13:47):
seem threatening to someone whobuilt their career on specific
expertise, because their brain'sidentity protection system
fights against adoption toolsthat might take their
hard-earned knowledge.
That can make them obsolete.
But here is the encouragingnews Neuroplasticity means slow
(14:13):
learners can become fastlearners with the right approach
, which means that we canactually rewire a brain for AI
learning.
The brain builds new neuralpathways throughout life.
It just requires intentionalpractice that works with your
(14:33):
existing architecture instead ofagainst it.
Work with it, not against it.
Less resistance.
And how does that workpractically For systematic
thinkers like the CFO I wasdiscussing in the beginning of
the podcast?
Start with structured AIexperiments Instead of play
around with chat, gpt.
(14:54):
Give them specific prompts totest with measurable outcomes,
and that can help make AIlearning feel like a controlled
experiment.
Where they feel still they havecontrol, their analytical brain
needs frameworks.
(15:14):
So create AI protocols thatthey can follow systemically.
Once they see consistentpatterns, their trust circuits
will activate.
And you might ask but whatabout the perfectionist
executive who hate makingmistakes?
We can reframe mistakes as datacollection Instead of I got a
(15:36):
bad AI response.
Maybe try to start.
Make them think I collecteduseful information about prompt
effectiveness.
Change the language to changethe brain response.
Remember words have power.
Okay, change your words, youchange your word.
Languages shape neural pathways.
(15:58):
Experiment feels lessthreatening than trial and
errors.
Iteration sounds moreprofessional than playing around
than playing around.
So there are something specificexercises to build AI learning
speed so we can start with whatwe call micro experiments five
(16:20):
minutes AI tasks with clearsuccess metrics.
This builds confidence pathwayswithout triggering overwhelmed
circuits like baby steps for thebrain.
Perfect analogy is that eachsuccessful micro experiment
releases dopamine, reinforcingAI engagement, and over time
(16:43):
these small wins build largerconfidence neural networks.
You might ask how long doesrewiring take?
It varies actually byindividual, but neuroplasticity
research suggests thatsignificant pathway changes in
30 to 60 days with consistentpractice.
The key is daily engagement,even if brief.
(17:06):
That's basically creating newhabits.
Remember, and if you add anextra layer on the consistent
practice and have triggers likeput yourself a stick on notes on
uh on your desk or have ascreensaver or put an alarm on
your phone at certain times toremind you of something like
quick proko, like a trigger thatwill let you go and do that
(17:29):
five minute or micro experiment.
So 15 minutes daily beats threehours weekly for neural pathway
development.
Repetition is better thanduration.
Consistency builds strongerconnection than intensity.
So let's get practical, okay.
(17:49):
How can executives speed up AIadoption across their teams,
especially when they have amixed bag of facts, adopters and
holdouts?
Number one assess your team'slearning architectures.
Don't use one-size-fits-alltraining, which basically
everybody has been doing.
That's wrong.
(18:10):
Match AI introduction methodsto individual neural preferences
.
What does that mean?
Analytical thinkers needstructured framework and
measurable outcomes.
Creative thinkers needopen-ended exploration time.
Risk aversion personalitiesneed safety nets and supervision
(18:30):
.
Different approaches fordifferent brain types.
Your systematic, for example,cfo, like we discussed in the
beginning.
They need AI standard operatingprocedures.
The creative marketing directorneeds AI playground time with
no specific objectives, hope itmakes sense and how to build
(18:51):
confidence in slow adopter.
Create AI wins quickly.
Give them simple, low-risktasks where AI obviously saves
time, like email summarization,data organization, routine
analysis, reading report, excelsheets.
Routine analysis, readingreport, excel sheets.
(19:12):
So, building success beforecomplexity.
Each small success releasesdopamine and builds positive AI
associations.
Start with tasks thatcomplement their existing
strength, not challenge them,and I know that some executives
(19:33):
have some fear factor.
They worry that AI will replacetheir jobs.
We need to address thisdirectly with neuroscience.
Explain or explaining that AIaugments executive capabilities
like strategic thinking,relationship building, creative
problem solving that AI can'treplicate.
This is human skills that AIcannot replicate.
(19:56):
That no matter what executivewill have those very unique
skills.
So position AI as a power tool,not competitor.
We are complemented by AI.
We collaborate with AI and wedon't compete with AI.
Frame it as AI helps you domore of what only humans can do
(20:20):
by handling what machines dowell.
This reduces threat responseand activate curiosity circuits.
So some of the specificorganization strategies that I
use is I use peer learning.
Accelerates adoption.
Pair fast learners with slowlearners, not as teachers, but
(20:41):
as learning partners.
Remember, like mentoring andreverse mentoring, social
learning activates differentneural pathways than individual
studies.
Body systems for AI learninganyone but structured body
systems give pairs specificchallenges to solve together.
Collaboration reducesindividual performance, anxiety
(21:02):
while building collectivecapability.
And how to measure progress?
And how do we know if therewiring is working?
We track behavioral indicatorsfrequency of AI tool usage,
complexity of tasks, attemptedcomfort with imperfect output
(21:23):
and willingness to experimentwith new prompts.
Practical metrics instead ofjust surveys, because the neural
pathway changes show up inbehavior before people
consciously recognize them.
Usage patterns reveal brainrewiring better than
(21:44):
self-reporting.
So let's create a simpleprotocol executives can use to
speed up their own AI learning.
So let me give you somethingthat can actually be implemented
.
Week one and two daily 10minutes structured experiments
(22:08):
same ai tool, same type of task,different approaches.
Build familiarity, neuralpathways, consistency and
repetition first.
Week three and four introducecomplexity gradually.
Add one new variable per week.
Different prompts, differenttasks or different tools.
(22:30):
Build flexibility circuitsslowly.
Do not overwhelm the system.
Week five and six integrationchallenges Use AI for actual
work problems, not practiceexercises.
This builds confidence andrelevance neural connections.
(22:51):
So now we move from practice toreal application.
Week seven and eight teachingothers Remember to real
application.
Week seven and eight teachingothers remember the best way to
learn something is to teach it.
Explaining ai approaches tocolleagues activates deeper
understanding pathways andreinforce learning.
And the final step basically,like I just explained, is
(23:12):
becoming a teacher yourself asan executive.
Teaching forces your brain toorganize AI knowledge into
transferable patterns.
It's the ultimate neuralconsolidation exercise.
So let me ask you this, guyswhat was your takeaway for
executive?
Wondering why AI learningspeeds vary so much?
(23:34):
And the answer is simple it'snot about intelligence or age.
It's about brain architecturebuilt from career experiences.
Fast learners have flexibleneural pathways.
Slow learners have systematicpathways.
Nothing, no one, is better thanthe other.
Okay, both can be changed withthe right approach.
(23:56):
Executive, remember yourlearning speed is not fixed.
Neuroplasticity means you canbuild ai fluency at any career
stage with intentional practice.
So don't judge everybodybecause they're being systematic
or about everything right.
(24:17):
The systematic brain isactually an asset, just needs ai
compatible frameworks.
Next week we are diving into aiproductivity paradox why more
ai tools can feel like lesscontrol.
Subscribe if you want tounderstand why some brains love
(24:37):
AI and others fight.
Show me some love Like.
Share this with someone else.
Subscribe to our podcast so youdon't miss any of the new
episodes.
This is Sahar, your AIwhisperer, signing off from AI
Cafe Conversations.
Your brain is more adaptablethan you think.
Any questions, questions, anycomments?
(24:58):
Please email me at sahar atsahar consultingcom Website,
sahar consultingcom.
My book the coaches brain meatAI is still On top new releases
on Amazon and is doing reallywell, is on the top 30 of three
different categories and I'mvery proud of it it and I hope
(25:22):
you like it.
I hope you get to read it andtell me what you think about it,
but for now I'm over and out.
See you next time.
One, two, three, four.
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