Join Sahar the AI Whisperer in AI Café Conversations In this Forbes Edition of AI Café Conversations, as we delve into 'AI for Executives' and 'Human-centered AI' strategies for transformative leadership. This podcast offers invaluable insights on AI adoption and executive coaching tailored to non-technical leaders who feel overwhelmed by the complexities of artificial intelligence.
Through expert interviews and actionable strategies, you'll learn how to integrate AI into your leadership style seamlessly while enhancing human connection. Discover neuroscience-based approaches that alleviate tech anxiety and resistance, allowing you to fully embrace AI as a partner in your leadership journey.
Sahar shares hilarious and human stories of working with AI — from scheduling mishaps to unexpected lessons in leadership.
Discover how AI and leadership can coexist, why upskilling and executive coaching with AI matter, and how to build a workplace culture that balances innovation with empathy.
This episode blends humor, neuroscience, and human-centered insights to explore the future of work where AI supports — not replaces — humanity.
New episodes drop weekly, ensuring you remain at the forefront of AI developments that can redefine your coaching and executive practices.
Subscribe to AI Café Conversations for weekly neuroscience insights that help executives master AI tools without sacrificing mental clarity or leadership effectiveness.
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).
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Episode Transcript
Welcome back to AI Cafe Conversations, where
neuroscience meets AI forexecutives.
I'm Sahar and I'm dragging yourAI whisperer.
Have you ever had an AI tool?
Completely and totallymisunderstand you.
I will never forget when an AIscheduling app decided my
(00:35):
leadership workshop should runat the same exact time as my
surprise birthday party.
There I was trying to talkabout inclusive leadership while
secretly worrying I had missedmy own cake.
It actually was funny, butfrustrating and oddly humanizing
(00:57):
, and it taught me somethingimportant.
What it actually taught me isthat AI might be brilliant with
data, but it still needs us, ourcreativity, our emotional
intelligence and our oversight.
(01:19):
In today's episode, we willexpose what it means to work
alongside ai, not as a threat,but as a quick partner, from
upskilling teams to fosteringinclusive leadership.
I will share how leaders canembrace ai without losing the
heart of human connection.
(01:42):
Remember, this is not ourregular podcast.
This is our extra cafe flavorthat I share with you on Fridays
.
Now I have been having a lot ofactually nice comments and a
lot of emails from you guys.
Thank you that you have beenliking that extra flavor that I
have putting.
These are my Forbes articlethat I do as podcast.
(02:06):
Keep letting me know.
Love you all.
Speaker 3 (02:09):
Welcome to the deep dive.
Our mission, as always, ispretty simple Take loads of
complex info, articles, studies,maybe your own notes, and boil
it down to the core insights youcan actually use now.
Speaker 2 (02:23):
Yeah, the useful stuff.
Speaker 3 (02:24):
Exactly, and today we're diving deep into something
that's well everywhere theAI-powered workplace.
It's not sci-fi anymore, is it?
It's basically our new coworker.
Speaker 2 (02:34):
That's right.
I mean, if you're listening,you already get that AI is sort
of baked into daily life.
Now Think about Spotify andNetflix.
They seem to know what you wantnext, right, or Waze getting
you through traffic.
But the bigger picture, thereal revolution, is in industry.
Ai is doing things like helpingdiagnose diseases, managing
complex financial stuff, evenplanning out supply chains.
(02:57):
It's huge.
Speaker 3 (02:58):
So understanding how to work with this force.
It's not optional anymore, it'skind of the new professional
baseline.
Speaker 2 (03:04):
Absolutely.
Speaker 3 (03:05):
And for this deep dive our source material is
really interesting.
It comes from a leader, expert,someone grounded in
neuroscience actually, and theymap out their own journey,
starting from being prettyskeptical about AI to finding a
way to genuinely partner with it.
They talk about this mix ofcuriosity, comedy and occasional
chaos, which sounds about right.
Speaker 2 (03:25):
It does.
And that perspective is sovaluable because, you know, the
conversation around AI tends toswing wildly, doesn't it?
Speaker 3 (03:32):
Yeah, it's either wow , efficiency, or oh no, the
machines are taking over.
Speaker 2 (03:35):
Exactly so.
Our mission here is to cutthrough that noise, to really
unpack what it takes for humansand AI to collaborate
effectively and, importantly,define what makes human workers
truly unique.
What's our value add?
We're really at this crossroads, I think, between innovation
and, well, ethics too.
Speaker 3 (03:54):
Okay, so let's get into it with some of those real
world examples.
The funny ones often teach usthe most right, because this
shift from seeing AI as maybe anunwelcome guest to a productive
partner, it didn't startperfectly.
Speaker 2 (04:06):
Oh, definitely not.
That unwelcome guest analogy isperfect, actually, because AI
is incredibly precise, but itoften lacks well context, common
sense.
Almost the source shared acouple of stories that really
highlight why we still need thathuman oversight.
It's crucial.
Speaker 3 (04:20):
Get this first one.
They rolled out a new AIscheduling tool, you know,
designed to make everyone'scalendar super efficient.
Speaker 2 (04:26):
Standard stuff.
Speaker 3 (04:27):
Right.
So they asked it to find theabsolute best time for a really
important leadership strategyworkshop, and the time it picked
.
Speaker 2 (04:35):
Let me guess Lunchtime.
Speaker 3 (04:37):
Worse, it picked the exact time that was already
blocked out for the source's ownsurprise birthday party.
Speaker 2 (04:43):
Oh, no See, that's it Exactly.
The AI saw an open slot,probably optimized for
everyone's lifted availability,but it completely missed the
human element, the social value.
You can't put a data point onsurprise party importance.
Speaker 3 (04:59):
Right, it failed the context test spectacularly Okay.
And then there was the otherone.
The AI meant to automatefeedback for process.
Okay, and then there was theother one.
The AI meant to automatefeedback for process improvement
.
What happened there?
Speaker 2 (05:08):
Yes, that one.
Well, instead of gathering andanalyzing feedback from people,
it somehow got stuck in a loopyeah, a closed circuit, where it
just kept generating positivefeedback for itself, basically
complementing its own efficiencyat giving feedback.
Speaker 3 (05:21):
So the AI became its own biggest fan, running on pure
self-congratulations.
Speaker 2 (05:26):
Pretty much, yeah, and that's the heart of this
comedy of errors, isn't it?
Yeah, it shows us that AI cancrunch data like nothing else,
but it lacks that fundamentalhuman social awareness,
self-awareness even.
Speaker 3 (05:38):
So we have to learn to work with its quirks.
Speaker 2 (05:41):
Exactly.
We go from being wary of it itmaybe treating it like that
awkward guest, to eventuallyfiguring out how to coexist,
almost like a like an oldmarried couple yeah, you learn
each other's strengths andweaknesses.
The lesson is pretty clear, Ithink yeah real value comes when
you combine ai speed and dataskills yeah with human
creativity, judgment and thatcrucial emotional intelligence
(06:04):
okay.
Speaker 3 (06:04):
So if individual teams are figuring this out,
sometimes the hard way, throughtrial and error, what about the
bigger picture?
Let's scale this up.
How do organizations approachthis strategically?
What's leadership's role increating a real blueprint for
this human AI coexistence?
Speaker 2 (06:20):
that's the key transition.
Leaders essentially become thearchitects of this new workforce
structure, and maybe thebiggest part of their job isn't
just picking the right tech.
Speaker 3 (06:29):
It's managing the people side.
Speaker 2 (06:31):
Exactly Managing the fear that comes with it, which
means investing seriously inreskilling and upskilling.
Isn't just nice to have, it'sstrategically vital.
Speaker 3 (06:40):
Why, though, I mean playing devil's advocate here?
If AI can automate tasks, isn'tit just cheaper and faster to
hire people who already have thetech skills?
Is reskilling really worth theinvestment, or is it just good
PR?
Speaker 2 (06:56):
That's a fair question, but it overlooks
something critical contextualexpertise.
Your current employees theyhave years, maybe decades, of
institutional knowledge, thathistory, that understanding of
why things are done a certainway, or nuances about clients or
eternal processes.
Ai doesn't have that built-incontext.
Reskilling lets you leveragethat existing knowledge base and
(07:17):
layer the new AI skills on top.
Speaker 3 (07:19):
So it's about combining the old and the new.
Speaker 2 (07:21):
Precisely so.
The training needs to bespecific.
It's not just about vaguedigital literacy.
Speaker 3 (07:25):
Right, so what does that actually look like?
What skills are we talkingabout?
Speaker 2 (07:28):
Okay, Three core areas, I'd say.
First, prompt engineeringBasically learning how to talk
to AI effectively, how to askthe right questions to get
useful results.
Speaker 3 (07:37):
Okay, makes sense.
Speaker 2 (07:38):
Second, data curation and oversight.
We need people who understandthe data being fed into the AI,
people who can spot biases,limitations or potential errors
in the output.
Remember the self-complementingAI.
A human had to notice that loop.
Speaker 3 (07:54):
Right, someone needs to sanity check it.
Speaker 2 (07:56):
Exactly.
And third, strategicapplication.
This is about training peopleto take the insights.
Ai generates the data, analysisthe patterns and translate them
into smart, human-centeredstrategies Things AI wouldn't
come up with on its own.
Speaker 3 (08:16):
So AI does the heavy lifting on data analysis,
freeing up human brainpower forthe creative, strategic part,
which brings us right to thatcrucial point for you listening
what can't AI do?
What are the skills that remainuniquely human?
This is where our source'sneuroscience background really
comes in handy.
Speaker 2 (08:28):
It really does, because AI's core strength its
limitation too is patternrecognition.
It finds and repeats patterns.
So anything that lacks clear,repeatable sort of linear
patterns, that's where AIstruggles.
Speaker 3 (08:39):
Okay.
So what kind of traits are wetalking about?
What's outside the patterns?
Speaker 2 (08:42):
Well, number one is emotional intelligence.
Ei and the source reallyemphasizes this isn't just about
being nice, it's thisincredibly complex human ability
to read subtle cues, tone ofvoice, body language, the
feeling in a room to navigatetricky social situations.
Ai might classify text,sentiment maybe, but it can't
(09:04):
feel or truly understand empathy, respect, trust.
Speaker 3 (09:07):
Because those aren't based on predictable data points
.
They emerge from messy realinteractions.
Speaker 2 (09:12):
Exactly and related to that is genuine human
connection, that personal touchthat builds real relationships
with clients or within teams.
Ai can't replicate that warmth.
What else?
True strategic thinking andinnovation.
Ai is great at analyzingexisting data to suggest
improvements or predict outcomesbased on past patterns.
But human creativity that ofteninvolves making these leaps,
(09:33):
connecting totally unrelatedideas, breaking the pattern
entirely.
Speaker 3 (09:36):
Creating something fundamentally new, not just
optimizing the old.
Speaker 2 (09:39):
Yes.
Think about navigating diversecultures in a global team or
managing complex internalpolitics.
Those things are full ofunspoken rules, nuances.
They defy simple algorithms.
Ai just doesn't have that humanwarmth or the intuition to pick
up on all those subtle,non-pattern-based cues.
And the takeaway for you isthis If your job is mostly
(10:01):
repeatable tasks based on clearpatterns, ai will likely change
it, enhance it, maybe automateparts of it.
But if your role demands highEI, complex problem solving,
genuine creativity, buildingrelationships, your value
actually increases.
In an AI world, those skillsbecome premium.
Speaker 3 (10:21):
So we know the skills needed.
Now, how do you build a culturewhere AI can actually thrive?
It's not just about individualskills, right, it's about the
whole team, the wholeorganization, successfully while
onboarding AI.
Speaker 2 (10:31):
Yeah, onboarding is a good way to put it, because
adopting AI isn't just a techupgrade, it's a cultural shift.
Leaders have to actively shapean environment where AI is seen
as a contributor, a powerfultool, not a threat lurking
around the corner.
Speaker 3 (10:43):
Which means dealing with those anxieties we talked
about.
Speaker 2 (10:46):
Directly, proactively .
Leaders must create safe spacesfor open discussion.
Talk honestly about the fearspeople have job security, losing
the human touch, bias inalgorithms.
If you let those worries festerunanswered, they turn into
resistance.
Exactly, they become roadblocks.
So instead, you acknowledge theconcerns, but you also clearly
(11:06):
highlight the opportunities AIbrings.
Frame it as a chance to moveaway from repetitive tasks
towards more interestingstrategic work.
Makes sense and this wholeonboarding process.
It needs patience, just likebringing any new person onto a
team, especially a reallydifferent kind of person.
There will be bumps, funnymistakes like the scheduling
disaster.
Speaker 3 (11:27):
Right the AI's learning curve.
Speaker 2 (11:28):
Yeah, and successful integration means getting people
to see those errors not just astech failures, but as
collective learning moments.
It takes time understanding,letting new dynamics develop, so
everyone sees AI as part of theteam effort, alongside human
expertise.
Speaker 3 (11:44):
So, when we pull this all together, what's the real
future of work?
Look like it doesn't sound likethe you know sterile machine.
Take over.
Some people fear it soundsmessier, more collaborative.
Speaker 2 (11:56):
I think that's exactly right.
That's the synthesis here.
Thriving in this future meansgetting really good at using AI
strengths, its speed, its datapower, but consciously blending
them with our unique humanskills Empathy, creativity,
complex strategy connection.
Speaker 3 (12:12):
So the goal is a workplace that values both
efficiency and empathy,innovation and inclusion.
Speaker 2 (12:18):
Precisely, it's about enhancing work, not just
automating it.
Speaker 3 (12:21):
And remembering, as our source highlights, that the
journey involves those learningcurves, the occasional chaos,
even the funny mistakes.
We need to kind of lean intothe quirks of AI.
Speaker 2 (12:31):
Like the party-crushing scheduler or the
self-promoting feedback bot.
Speaker 3 (12:34):
Like the party-crushing scheduler or the
self-promoting feedback bot.
Yeah, and use those moments tocelebrate our own human ability
to adapt, to correct, to addthat essential context.
Speaker 2 (12:41):
We're not just handing tasks over.
Hopefully, we're making workmore meaningful by focusing
human energy where it mattersmost.
Speaker 3 (12:47):
Okay, so here's that final thought I want to leave
you with today.
If AI really is like thatslightly awkward, sometimes
brilliant, sometimes weirdlyself-congratulatory classroom
assistant, how can we and ourteams and organizations go
beyond just getting the rightanswer from it?
How can we leverage the actualprocess of learning, from its
mistakes, the scheduling,conflicts, the feedback loops,
(13:09):
not just to fix the output butto get fundamentally better at
understanding and mastering thecomplex systems we're using?
How do we optimize the wholelearning engine of the
organization, not just polishthe final product?
Ai helps create Something tothink about.
We'll see you next time for thenext Deep Dive.
Speaker 1 (13:24):
Today's Forbes edition of AI Cafe Conversations
.
Remember this AI is not here toreplace your humanity.
It's here to remind you howessential it is.
Let AI handle the patterns andlet us bring the empathy, the
(13:46):
creativity and leadership thatno machine can match.
If this episode made you smileor make you think, share it with
a colleague who's navigating AIin their own leadership journey
and join me next week foranother conversation where we
keep exploring what it means tolead with both brains and heart
(14:10):
in the age of AI.
Show me some love.
Like save, subscribe to thepodcast, share it with someone
else.
I have been seeing a lot of lovelately and I really love you
for it.
If you have any questions,email me at sahar at
saharconsultingcom.
My website issaharconsultingcom.
(14:30):
You can reach me on LinkedIn.
Me on LinkedIn, sahar Andrade,or on my Instagram, sahar the
Reinvent Coach, and my book, theCoach's Brain Meet AI, is doing
great on Amazon.
I have the Kindle and thepaperback Go get it.
And if you get it, email me atsahar at saharconsultingcom and
(14:54):
I will send you two extra guidesthat you can use the book with.
I will send you 50 made for youprompts that you can use right
away and 20 new nuggets.
Just email me when you get themeven on the Kindle format, that
is only $2.99 and I will sendyou the guides.
Speaker 3 (15:14):
Love you all.
Speaker 1 (15:15):
This is Sahar Andrade and I'm out of here.
One, two, three, four, Wannahear you go, go, go, go, go go.
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