November 21, 2025 • 33 mins
AI is transforming how teams work, but they will be great only when the foundation is strong. As Daria Rudnik explains, high-performing teams don’t fear AI, and they don’t overestimate it either. They use it to enhance clarity, improve collaboration, and free up mental space, not replace thinking or connection.
In this episode, we explore how trust, communication, and shared purpose create the conditions for AI to actually help. When teams understand each other, make decisions well, and stay aligned, AI amplifies their strengths rather than their stress.
We dig into:
- Why clarity and communication matter more than any tool
- Core pillars of forming a strong team
- How strong teams use AI for cognitive offloading without losing judgment
- The boundary between what machines process and what humans must decide
- What future-ready, AI-supported teamwork really looks like
If you want to build a team that’s not just efficient—but resilient, connected, and ready for the future—this episode is your guide.
“You should never offload anything that needs empathy and human-to-human connection… you should never fire a person with the help of AI.” - Daria
About Daria Rudnik
Daria is a team architect, executive leadership coach, and author who has spent 15+ years helping leaders build teams that think clearly, communicate honestly, and perform sustainably. A former Chief People Officer and Deloitte consultant, she’s supported organizations across six continents through crises, rapid growth, and major transformation. As the founder of Aidra.ai, she blends human insight with hybrid-intelligence tools to help overloaded leaders create clarity without carrying the whole load themselves. At her core, Daria is a guide for teams who want to work smarter, not harder — and for leaders who want collaboration that actually feels human.
You can connect with Daria on LinkedIn LinkedIn dariarudnik and her website https://dariarudnik.com/
Mind Blend is all about real experiences and meaningful conversations—through sharing these insights, I hope to inspire and empower you as you navigate your unique journey.
I’d also love to hear from you! What resonated with you today? What topics or guests should we feature next? Let’s keep the conversation going—connect with me on LinkedIn @ karenkchong and @Mind-Blend
Follow Mind Blend to get notified when new episodes are released!
Until next time, stay curious, keep exploring, and let’s continue to blend our minds and discover what’s possible.
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:01):
Welcome to the show Mind Blend. I'm your host, Karen Chong, and
I'll be diving into the minds ofincredible people, each an
expert in their very own way. Together, we'll uncover insights
and share ideas so you can be inspired and empowered to
navigate your own unique journeyin life.
Ready to get curious and discover what's possible?
(00:22):
Let's blend. So a few episodes back, I'm mind
blended with Collette Mason about how we can make AI work
for us, not replace us. But the conversation doesn't
stop there. There's so much more we have to
explore about what happens when AI and human truly start working
(00:43):
together. So today I'm joined by Daria
Rudnick. Daria sits right at the
intersection of AI, leadership and human connection.
She's a leadership coach, team architect.
And then we'll go a little bit more into that and hybrid
intelligence strategist who helps leaders in their teams
build clarity, trust and real connection in an AI driven
(01:05):
world. Hi Daria, welcome to Vine One.
Hi, Cameron. Thanks for having me here.
It's it's yeah, I'm very excitedto have this conversation.
Yeah. So I'm sure our listeners are
intrigued by now. What do you mean by team
architects and hybrid intelligence strategies?
So tell us a little bit more about your journey and how you
(01:25):
got to where you are today. Yeah, well, my, my background is
an HR and organization development.
I started my career in Deloitte and then I moved to achieve
people officer for mostly tech and telecom companies.
And look through throughout my career, I, I, I've seen
disruptions that you said various disruptions that teams
(01:47):
face, teams face like merges andacquisitions like setting up in
other countries. And what I've noticed is when
organizations have strong teams,they are much more successful in
any organization transformation that's happening.
They are much more successful indealing with, I mean, global
disasters like financial crisis or COVID or like whatever it is.
(02:08):
But when the teams are not strong, when like the culture is
very diluted, it's, it's very hard for leaders to move their
organization forward. And I've seen examples of like
failures where the companies were just acquired and, and
dissolved. They were not existent anymore
or they, they go bankrupt. A lot of it because the teams
(02:28):
were not ready for for this change.
So since ever that time I started to study and see how to
design amazing teams, how to build those teams because they
don't just happen on the road whenever like families of the
team, universities are the team,schools on the team.
And the first time we really join a team is when we're
(02:49):
joining workforce. And now we're expected to be a
team player, like work in a teamor when manager grows into his
first managerial role, they say we need to build a team.
How do you do that? Yeah, they didn't teach it.
It's not about delegation and control.
I mean, no. So you need to design the team,
you need to build a team. And so it's a special effort,
(03:11):
it's a skill. There are certain tools and
techniques that you can use in order to practices that you that
you need to implement in order to build this this great team.
That's why I kind of call myselfA-Team architect because I
helped leaders build those kind of teams and design them.
But he also mentioned about hybrid intelligence and that's
kind of a new thing when AI is joining the workforce and
(03:32):
influencing team dynamics, organizational dynamics, how we
work together. It's and it's not just work how
we think, collaborate and make decisions.
And that's a totally used skill and kind of understanding of how
to work with the AI so that you don't delegate too much, you're
still in control, that you stillown the work that didn't have
(03:53):
intelligence to do that. So let's set the scene a little
bit for our listeners. We are at the time of this
recording close to the end of 2025, we've seen layoffs with
reasons such as we're optimizingour resources and now we don't
need nearly as many people with the help of AI.
And you also see sort of like this pressure coming up from
(04:16):
leadership or founders level C-Suite of mandates of we need
to use more AI or we need to useAI and all these projects and
things like that. Because you work with teams and
leaders directly, what have you,What sort of emerging patterns
have you noticed? It's, it's kind of from the
(04:39):
employee perspective, there's sort of fear.
There's a fear that AI will replace me.
And even more, it's not that AI will replace me, it's the
manageable thing that AI can replace me, which is not like
you mentioned layoffs. There were a lot of layoffs
labeled like AI driven lay layoffs but like to be honest
(05:01):
most of them are economically driven layoffs and AI is just a
nice cover for many of them. And we've seen, I think so too.
Yeah. And we've seen situation when
people kind of think, OK, now AIcan do that for them, we can
save some money. They have to rehire those people
back because, well, no, AI cannot do all the work for
humans. It can support you can do more
(05:24):
with the same amount of people, but doing more with less people.
Well, not. Not yet.
Yeah, I am glad you pointed out the not yet because you know,
we're actively training it. The models are getting improved.
At some point it can do more than what it can do today.
However, we need to keep the lights on.
(05:44):
And it's, I definitely believe that it's more how you can make
your people more efficient so you can do more of what's
important for the organization, not just do more.
Yeah. What about leaders like, what
are like the ones who advocate like, yes, we should just use AI
and replace half of our workforce or the ones that are
(06:06):
sort of pressured by their management of incorporating more
AI in like your team. Like what have you seen with
that layer? A lot of companies are
experimenting with AI and we areat this experimentation stage
when lots of AI projects are initiated from various parts of
organizations, sometimes from the top, sometimes from the
(06:27):
bottom, sometimes like multiple AI projects in various
functions. But together with that, we also
see that AI is not bringing regional investment as a as we
hope it will. So I mean we're still like
trying to figure out how that how that should work.
So the latest, the main questionis they will have to use AI,
(06:47):
Everyone will have to use AI. We we can understand that.
But the question is like why? Yeah, I'm not against that at
all. Yes, why and how?
Like what is the reason? What is that we want to use AI
for and what are the norms, how we're going to use it?
Because I've seen situations where kind of people just dive
in, OK, let's use AI for everything, and then that causes
(07:08):
team disengagement, loss of motivation, and eventually loss
of productivity and effectiveness.
So you you help companies build effective teams.
High performing teams. Name some characteristics of a
high performing team. Oh, I can have you 55.
Yeah, name as many as you want. I guess while while working with
(07:30):
teams and like not just the favorite, not just in practical,
but like, yeah, reading literature and scientific
literature about how like great what what does it make to be a
great team? I came up with five major
pillars of any successful team, high performing team, team that
is more self-sufficient, more autonomous, that can manage
(07:51):
themselves and they don't need leader for every decision.
So the first thing is they have they have a clear purpose and
that's pretty obvious. Yes, you need to understand why
you're together. And the tricky part here is not
every team has that. So if if you have a bunch of
people and like just being reported to one manager, that
doesn't make them a team. They become a team only when
(08:11):
they have a shared purpose, something that they can achieve
together by collaborating and and working together and not
just by combining the individualcontributions.
So that's, that's the one important part.
The second one is linking connections.
When people are connected withinthe organization, there were a
(08:32):
lot of connections manager to employee, but what about like
people employee to employee, people, team members to team
members And more importantly, what about the connections of
this team members to other, to their stakeholders.
So it's not just the manager whogoes out to the boss, to the
stakeholders, to peers presenting the results.
So it's people, team members go now to their stakeholders,
(08:55):
understanding their needs, presenting results, taking
responsibility for the mistakes that they've made.
So that's the second part, linking connections.
The third one is integrated work.
And that that's what many leaders are missing is how do we
work together as a team? What are our team norms?
What is what do we support in terms of behaviour?
(09:16):
What kind of behaviour do you want do we want to see in our on
our team and what kind of behaviour we never want to
tolerate? So what is not tolerated on our
team? So this team knows how many
meetings do we want to have? Like what are the communications
channels that we're going to use?
It creates a lot of clarity and it removes frustration from
(09:36):
people. OK, what's next?
The 4th 1 is collaborating decisions.
How do you make decisions on your team?
Because you as a manager, you don't have to make all decisions
on your own. And then finally, knowledge
sharing and feedback. How do you as a team learn and
grow together? How you learn from your
mistakes, how you give feedback to each other, how you collect
(09:57):
feedback from your stakeholders?So those five pillars, clear
purpose, linking, connections, integrated work, collaborative
decisions, and knowledge sharingis what will make your team
click. Have you seen anything that like
you, let's say you have a clientthat you help them build high
(10:18):
performing teams. Do you, have you seen any cases
where they used to be performinggreat, but recently they've
started phasing out certain things that they're doing
because of changes in technology?
Have you seen anything like that?
Well, I have AI have an example of a of a team.
I'm not sure they were like super high performing team, but
(10:39):
they were recently like they were pretty decent before AI, it
was a customer success team. They were like working with the
clients, pretty happy together, engaged, working well.
It's a good team and at some point, and they were a good
team, they were curious about new things.
So they implemented and started using AI quite a lot.
(11:01):
So they they had that conversation with clients.
The conversation was recorded. They had a transcript of this
conversation. AI generated insights from the
conversation. They uploaded it to CRM.
Some of the items went to backlog and then AI helped them
generate agenda for the next meeting with the client.
So I mean, a lot, a lot was automated.
(11:21):
Everyone was happy. They had lots of time.
They had to like pick up the projects that they didn't have
time for before they had some time to breathe and kind of OK,
relax and not behind all like the days all the time.
But here was what happened next.At some point during the, the
team meetings, they, they couldn't like recall some of the
(11:44):
things they used to know about their clients.
They used to know they're like, like, you know, but now they,
they keep forgetting they need to go to the, to the CRM to look
at their insights that they havenot generated that were created
by AI. They couldn't prioritise items
for, for the backlog because, OK, they didn't have this
understanding what's more important for their clients
(12:06):
because again, they, they were not the ones who generated those
items. It was AI and they started to
feel like they're losing connection with their work.
They became just operators, putting data from one source to
another operate, helping AI do the work for them.
But they lost the meaning. They lost meaning, they lost
engagement and like eventually they lost productivity because
they were not so much involved in everything that's happening
(12:29):
by their clients. And that's when I joined this
team and kind of helping them to, to be like, to regain their
like get the engagement back andproductivity and become more
efficient with AI and how they use AI.
And So what they did is well, they started again with, with
why with a clear purpose. Why, why are we using AI?
(12:52):
Like what are we using AI for? What's what's in it and what is
what should stay with us as a team?
What's our word value proposition for organization for
our clients? Again, this, this understanding
and feeling of what the clients need and being able to support
their needs the best way possible is what should stay
with them as humans, as teens. And some of their automated work
(13:14):
can be created by AI. And the next thing they did is,
I don't know if you've heard about it.
There's a research called Your Brain on ChatGPT that tells that
if you like ask AI to do something and then like try to
edit it, your brain is disengaged and it stays
disengaged for like the whole project.
(13:36):
But if you do something, if you initiate the draft, if you do
something 1st and then ask to edit it or get some input, your
brain stays engaged longer. So what they did is they before
generating insights from the conversation and from the
transcript at the end of each conversation, when the
conversation was over, they kindof just was speaking, speaking
(13:56):
some things that they thought ofthis conversation, their
feelings, they got the insights,the idea, and then AI generated
insights based on what manager said and they're trusting the
conversation. So they were the first one to
give this input. They still own the conversation,
they still own the result. And then, well, they had team
(14:16):
meetings when they looked at those insights, looked at the
backlog and they were like, really, really go deep into that
and analyzing what's there and saying, OK, this is relevant,
this is not relevant. So they they they became part of
the process rather than just theobservable support AI is doing
for that. Yeah, you know what?
That sort of made me think of two real life scenarios.
(14:40):
One, phone numbers. So now you just hand your phone
to whoever they put the phone number in, you call them to like
give them your own phone number.That was the transactions.
So the numbers have not even gone into your brain at all.
So it's kind of similar to that.Another one is if you are, if
(15:01):
you work in a restaurant and you're the person taking the
order and you pass it to the chef, you may remember what it
is, but that was like really just the level.
And you may not even remember ifthere's like 100 customers.
So what you pointed out about you being the first engaging
(15:21):
your brain, I think that's like a really, really good point
because there are many things that we are starting to do it
like that. If you have to go somewhere, put
the address in the GPS, you may not remember how you get there.
I know that happened to me a fewtimes.
So by them kind of taking back that ownership of the insides of
(15:41):
the idea, how have you seen themgone back on track?
Well, they started having this conversation, well, first of all
between themselves when they started, when they, they engaged
in team meetings discussing the outputs, the inside the backlog.
Well, not only they understood it better because they.
(16:02):
Understood it better. OK.
But they also had again had a chance to talk.
We love connection with people. We love working together.
We love like seeing how ideas are built on ideas that we
share. Something someone fixed it up,
what's the question? And that not only helped them
understand better their clients,but it also helped with the team
(16:24):
climb and how they feel together.
Yeah. And I feel like they may have
insights that AI will never be able to generate for them
because we understand situationsdifferently.
And you sort of have to feed allthe new ones into AI for it to
give you like a well-rounded suggestion or insights.
So I'm glad. So what you were describing like
(16:46):
it never touching their brain, is that what you call cognitive
offloading? I mean it's it's it's a, it's a
term and this term is actually what you like properly described
with phone numbers and GP and GPS.
It's deal with that for quite a while right there when we
offload some of the information from our brain to technology,
(17:06):
which is good. I mean, there's so many, like
there's so many things we need to remember.
So that's so much information. We don't need to remember it
all. So at some point, cognitive of
loading is helping us to, to live with this excessive data
that we have around us. But when you offload too much,
when you like, one thing is a floating data numbers and things
(17:28):
like that. The other thing is when you
offload decision making. And that's when things go wrong.
And that's, that's the difference between like
automation and AI, because with automation, you don't expect
anything from a machine. But with AI, we kind of think
we're talking to a human being. We kind of have a real
conversation. We kind of assume that this
(17:49):
thing is telling us the truth, that this thing knows, which is
not true. So that's why it's very
important to be mindful about how much do you want to upload
to AI and at this, you know, lose this connection with your
work. So what in your opinion?
So besides data and like everyday business scenario, what
(18:12):
else would be suitable a suitable category of information
to offload and what they people should definitely not offload
like you mentioned decision making.
Yeah, I mean, there are lots of things we can offload.
Whether we cannot and should notoffload is something that needs
empathy and and human to human connection.
And a great example is you never, should never fire a
(18:32):
person with AI, with the help ofAI.
And there was A, and it's true and it sounds ridiculous.
There was a company that was a post on LinkedIn and some CEO or
CEO or some of the company they mentioned, like a relay of lots
of people here was an AI tool you can like reach out to and
talk to make you feel bad about that.
(18:53):
Oh, that's that's, that's so bad.
This post was bleeded but Internet remembers everything so
the screenshots are there. But yeah, things like that
should never be delegated to AI.And if you work with again, high
sensitive data, obviously, and be very mindful about like who
is getting access to that data. And again, it thinks AI telling
(19:18):
us they're not true. I mean, it depends on how you
train this AI, but it's if it's generated AI, they're not true.
They have probabilities that AI predictions based on what it
knows. So and always checking,
rechecking their output that AI gives you is a critical skill.
For now, at least, we'll still need to do that.
(19:40):
Do you have any good success cases like we can step away from
just focusing on AI? How has your biggest success
been going into a team and trying to fix, quote UN quote,
fix their issues and turn them into a high performing team?
Great question. I'm a lot of indicators of of
(20:01):
high performing great team. One of them is how much revenue
they can generate, how much theycan perform.
I've been working with company that.
Increased performance 3, three or four times.
But they were really pretty goodteam to be honest.
So the transformation they they've been through was, was
successful because they're very good team.
(20:23):
But I have an example where there's a lot of conflict on the
team. It's it's a manufacturing
company and the CEO reached out to me say, hey, like I have a
lot of conflict on my team. People cannot make, make
decisions together. They think the ID is better.
So when I joined the team and westarted having those
conversations, team sessions, ithappened that that well, people,
(20:46):
all of them, they were really engaged and they're really
motivated in company success. They just saw it differently.
Some saw that they need to focuson quality, others so that the,
the, the most important thing isdistribution channels and things
like that. So one of the things we did
together is apart from like being clearly, clearly being
(21:06):
clear on the purpose of the team, we created a list of
behaviours like what are the behaviours that the team wants
to see and wants to support and want to see more of like sort of
the keep it up behaviours, behaviours that need to stay on
the team. And what are they cut it out
behaviours, behaviours that they're not going to tolerate.
(21:28):
So they had the list, they had the list of keep it up behaviors
and carried out behaviors and all.
Eventually they, they had like they started to have meaningful
conversations with each other. They learned how to work
together. They moved forward and I think
it was a success. But the most interesting thing
happened about six months after when the CEO reached out to me
(21:48):
and said, you know what, we're moving fine.
We're going in in that direction.
A lot of conversations, lots of argument, but they're not like
personality conflicts, but people really bring in some
ideas and challenging them. Yeah.
And the team decided that the sales leader needs to go.
Why? Because she didn't follow the
(22:11):
keeping up behaviors and she constantly demonstrated some of
the cut it out behaviors and theteam mentioned that several
times. She didn't change and and the
team, they decided that she needs to go.
It wasn't C the CEO, it wasn't like the divorce.
It was the teams that she's not part of our team because she's
not following what we agreed to follow altogether.
(22:34):
I think that's that's a great example of TNB more
self-sufficient brand. They don't need their leader to
make every decision. They can make decisions on their
own. If they can solve problems on
their own, they can be more autonomous and they moving
without delay because they can make those decisions and they
can, they can do that. Are the clients that you work
(22:54):
with, are they like more concentrated in certain
geographies or you work with different people in different
continents? I actually, yeah, I was
counting, OK, how many countries?
I've been working with people inIndia, in Zimbabwe, in Latin
America, US mostly it's North America and Europe, but
Australia, yeah. And it's, it's, yeah.
(23:16):
I I love this opportunity to work with any like people from
any country like due to again, due to technology.
Yeah, 'cause what I wanted to ask is, you know, like I know
one of your effort is to help teams be like, to avoid burnout,
both burnout for the leaders andburnout for the team.
(23:36):
And in the example that you gave, the team can make
decisions themselves so they don't have to go to a leader
every single time. That hierarchy sort of depends
on the culture. To some cultures, that is fine.
Some cultures you the final say,still come from the top.
So how? How do you balance the culture
(23:57):
versus the nature of a high performing team and how to keep
people from burning up? That is, I mean, that's I love
that question. And and the the the best thing
about like a high performing team and how they're formed is
that the team themselves, they people on this team, they decide
what works for them best. If they think that the manager
(24:18):
need to have a final word, they can do that.
The cultures were like company organizational cultures.
When they say you work hard, youwork 1212 hours a day, like
you're not getting promoted for five years, but you'll get in
return like rapid growth or healing skills or whatever.
(24:39):
So it's it's a very clear contract and a very clear
agreement. So you can have any type of
culture you want I guess, as long as you sit together and
agreed on your team norms and team goal.
I haven't really thought about it that way, but that is a very
good tactic to kind of frame people's mindset before they go
(25:02):
into how do we get to become a high performing team.
So there's this like cycle of you have farming, storming,
norming, performing. So that's a typical cycle of any
team. Some teams may skip some.
Some teams may be stuck in Yeah Storming, for example, and they
(25:23):
come to you. Yeah.
But again, it's not a cycle. It's it's more like a spiral
because like with with any new challenge, with any new member
coming in, coming out, you go through the same cycle again
over and over again. So and then it's important for
men to kind of catch those cycles and make sure that to
help team go through that cycle because they will repeat.
(25:46):
Yeah. Now with technology like what
would be something that any leader or team members who are
burned out, anyone listening whowants to make a change so that
they can use AI to help them better, What would be something
that you would suggest they start?
To actually depends on the on the stage of AI and like
(26:09):
wireless. Yeah yeah in the company like
personally for themselves where they are because I mean I know
there were people who are using AI daily, but companies just OK
thinking should we do it? Should we not So they are in the
different like levels. But well, first is being curious
about what's there, like how it works, being curious about like
(26:31):
not only how should I use it, but also like what's really
happening when AI produces some outcomes.
Like the thing I mentioned that it's not true, it's predictions
like how actually LLMS work and start trying it out, make
mistakes, be mindful about the outcomes again, like repeat the
(26:52):
cycle, learn something else, tryit out, share with other people,
see what they're doing. And that's how we learn.
Yeah, the theme of curiosity, what has been floating through
the whole Mind Blend series so far, is like to keep an open
mind and iterate, learn from your mistakes.
Yeah, well, that's that's the drive of the progress.
(27:13):
Yeah. What would be your worst case
study? That it's always something that
you talk about as like casual family gathering or dinner party
or something. I have AI, have an.
I have an example. I was, I was having a
conversation with the CEO when Ifound one company and well, they
said that they value, I think itwas either transparency or
(27:37):
honesty, like transparency or honesty, probably honesty was
their value and and they wanted and they want to build honest
relationships with their customers.
And he talked a lot about that. But like throughout some
conversations, trust, hey, it was trust.
So he was talking about trust and he wanted to build trustful
relationship with with the customers.
(28:00):
But like while talking to that person I found out that he's not
paying full salary for the employees.
OK. Like using some like kind of
schemes to minimize taxes as OK.You talk about trust, how people
can trust you if you're doing things like that and like the
response was OK, You don't understand how to lead a
(28:21):
business. You cannot lead a like you
cannot run a business if you don't do things like that.
I mean, what happened a few months after that?
Is that one of the suppliers so brought bad product and and some
of the customers got quizened because of that product.
Wow. OK.
And I mean, if you if you build your relationship on trust, you
(28:45):
need to make sure everyone can trust you.
But if you build, if you like, if you're trusting here and not
trusting there, make sure you control everything like very,
very thoroughly. Because the trust is one thing,
but like if you're lying on someother things, it like it
destroys your culture and finally it destroys your
(29:06):
business. So that is a great example of
how I declare values and not actually part of the company and
how it can do in a company. Yeah, like you mentioned it in
the beginning, like the pillars of high performing team, like
shared values. Yeah.
So for this last part, let's play something out of the
(29:27):
ordinary. So I have a few rapid fire
questions. Just like really quick whatever
comes to your mind, say it. What's 1 human skill you think
is underrated in the age of AI? Well, we simply talked about
curiosity. I have this curiosity in my
mind. I think like we, we
underestimate curiosity and we underutilized curiosity to be
(29:48):
more curious and open to new things.
Yeah, I am 100% with that. So you've worked with, like
many, many continents, What culture taught you the most
about teamwork? It's it's not like culture, it's
again that don't put labels frompeople based on their origin.
(30:08):
Like see the human we as a leader, you have 10-8 people on
your team. We can learn about them as human
beings without labeling them like based on their culture.
Yeah, yeah, I see this a lot. It's not intentional, but people
will be called Oh the the, the Scottish guy like the Chinese
(30:31):
guy. Yeah, know them by their name.
Call them by their name. OK, When you feel mentally
overloaded, what's your go to way to reset your mind?
I studied practice in Tai Chi was in Canada.
I love it. Tell tell me more like I'm
interested. Well, like I used to do yoga
like long, long time ago. And I went, OK, I need to get
(30:53):
back to yoga. I could get back to doing yoga,
but I couldn't do that. It's important.
My husband shared a video with me and like a lesson and I was,
I was impressed with the wisdom is that can't let go together
with with the body movement and and the wisdom for me was very
(31:15):
important. And the point is that we you
cannot achieve anything with force.
This force is just one black powder, one thing, but you need
to be able to release, and that is as powerful as force if you
do it right in the right way. And this balance between like
(31:35):
moving forward and releasing andletting go is what I'm
practicing in my business and life.
And Tai Chi is is really helpingme with that.
Interesting because I see peoplein parks sometimes doing Tai chi
in the morning and like I have amental image of the movement
(31:56):
just because like I grew up in Asia.
But interesting that helps with business too.
So complete this sentence. I wish AI could.
I wish AI could change the worldfor the better.
I'm not sure if it's possible. Well.
This is why we're having this conversation today.
(32:19):
Like, I think if we can early onadopt A healthy mindset of using
AI and how we should use it to help us, partner with us, even
not just like an operational tool.
If more people can think of things like this, then yeah, we
can change it for the butter. Like we have so much more
information. Humans.
(32:40):
Can yeah, it itself will not do anything.
I, I do want people to walk awaywith like knowing this AI
shouldn't be used on its own. We should always be the humans
in the loop. Well, thank you very much for
having this conversation with me, Daria.
I will leave your information inthe show notes so anyone who
(33:03):
would like to continue this conversation, they can get in
touch with you or you can leave us a comment and we'll keep the
conversation going. Thanks for having me.
Thanks for listening to this episode of Mind One.
Maybe you enjoyed the conversation.
Don't forget to follow and shareit with anyone who needs to hear
it. And let's keep the conversation
going. Connect with me on LinkedIn or
(33:25):
leave me a comment. Until next time, stay curious,
keep exploring, and let's continue to blend our minds and
discover what's possible.
Welcome to the show Mind Blend. I'm your host, Karen Chong, and
I'll be diving into the minds ofincredible people, each an
expert in their very own way. Together, we'll uncover insights
and share ideas so you can be inspired and empowered to
navigate your own unique journeyin life.
Ready to get curious and discover what's possible?
(00:22):
Let's blend. So a few episodes back, I'm mind
blended with Collette Mason about how we can make AI work
for us, not replace us. But the conversation doesn't
stop there. There's so much more we have to
explore about what happens when AI and human truly start working
(00:43):
together. So today I'm joined by Daria
Rudnick. Daria sits right at the
intersection of AI, leadership and human connection.
She's a leadership coach, team architect.
And then we'll go a little bit more into that and hybrid
intelligence strategist who helps leaders in their teams
build clarity, trust and real connection in an AI driven
(01:05):
world. Hi Daria, welcome to Vine One.
Hi, Cameron. Thanks for having me here.
It's it's yeah, I'm very excitedto have this conversation.
Yeah. So I'm sure our listeners are
intrigued by now. What do you mean by team
architects and hybrid intelligence strategies?
So tell us a little bit more about your journey and how you
(01:25):
got to where you are today. Yeah, well, my, my background is
an HR and organization development.
I started my career in Deloitte and then I moved to achieve
people officer for mostly tech and telecom companies.
And look through throughout my career, I, I, I've seen
disruptions that you said various disruptions that teams
(01:47):
face, teams face like merges andacquisitions like setting up in
other countries. And what I've noticed is when
organizations have strong teams,they are much more successful in
any organization transformation that's happening.
They are much more successful indealing with, I mean, global
disasters like financial crisis or COVID or like whatever it is.
(02:08):
But when the teams are not strong, when like the culture is
very diluted, it's, it's very hard for leaders to move their
organization forward. And I've seen examples of like
failures where the companies were just acquired and, and
dissolved. They were not existent anymore
or they, they go bankrupt. A lot of it because the teams
(02:28):
were not ready for for this change.
So since ever that time I started to study and see how to
design amazing teams, how to build those teams because they
don't just happen on the road whenever like families of the
team, universities are the team,schools on the team.
And the first time we really join a team is when we're
(02:49):
joining workforce. And now we're expected to be a
team player, like work in a teamor when manager grows into his
first managerial role, they say we need to build a team.
How do you do that? Yeah, they didn't teach it.
It's not about delegation and control.
I mean, no. So you need to design the team,
you need to build a team. And so it's a special effort,
(03:11):
it's a skill. There are certain tools and
techniques that you can use in order to practices that you that
you need to implement in order to build this this great team.
That's why I kind of call myselfA-Team architect because I
helped leaders build those kind of teams and design them.
But he also mentioned about hybrid intelligence and that's
kind of a new thing when AI is joining the workforce and
(03:32):
influencing team dynamics, organizational dynamics, how we
work together. It's and it's not just work how
we think, collaborate and make decisions.
And that's a totally used skill and kind of understanding of how
to work with the AI so that you don't delegate too much, you're
still in control, that you stillown the work that didn't have
(03:53):
intelligence to do that. So let's set the scene a little
bit for our listeners. We are at the time of this
recording close to the end of 2025, we've seen layoffs with
reasons such as we're optimizingour resources and now we don't
need nearly as many people with the help of AI.
And you also see sort of like this pressure coming up from
(04:16):
leadership or founders level C-Suite of mandates of we need
to use more AI or we need to useAI and all these projects and
things like that. Because you work with teams and
leaders directly, what have you,What sort of emerging patterns
have you noticed? It's, it's kind of from the
(04:39):
employee perspective, there's sort of fear.
There's a fear that AI will replace me.
And even more, it's not that AI will replace me, it's the
manageable thing that AI can replace me, which is not like
you mentioned layoffs. There were a lot of layoffs
labeled like AI driven lay layoffs but like to be honest
(05:01):
most of them are economically driven layoffs and AI is just a
nice cover for many of them. And we've seen, I think so too.
Yeah. And we've seen situation when
people kind of think, OK, now AIcan do that for them, we can
save some money. They have to rehire those people
back because, well, no, AI cannot do all the work for
humans. It can support you can do more
(05:24):
with the same amount of people, but doing more with less people.
Well, not. Not yet.
Yeah, I am glad you pointed out the not yet because you know,
we're actively training it. The models are getting improved.
At some point it can do more than what it can do today.
However, we need to keep the lights on.
(05:44):
And it's, I definitely believe that it's more how you can make
your people more efficient so you can do more of what's
important for the organization, not just do more.
Yeah. What about leaders like, what
are like the ones who advocate like, yes, we should just use AI
and replace half of our workforce or the ones that are
(06:06):
sort of pressured by their management of incorporating more
AI in like your team. Like what have you seen with
that layer? A lot of companies are
experimenting with AI and we areat this experimentation stage
when lots of AI projects are initiated from various parts of
organizations, sometimes from the top, sometimes from the
(06:27):
bottom, sometimes like multiple AI projects in various
functions. But together with that, we also
see that AI is not bringing regional investment as a as we
hope it will. So I mean we're still like
trying to figure out how that how that should work.
So the latest, the main questionis they will have to use AI,
(06:47):
Everyone will have to use AI. We we can understand that.
But the question is like why? Yeah, I'm not against that at
all. Yes, why and how?
Like what is the reason? What is that we want to use AI
for and what are the norms, how we're going to use it?
Because I've seen situations where kind of people just dive
in, OK, let's use AI for everything, and then that causes
(07:08):
team disengagement, loss of motivation, and eventually loss
of productivity and effectiveness.
So you you help companies build effective teams.
High performing teams. Name some characteristics of a
high performing team. Oh, I can have you 55.
Yeah, name as many as you want. I guess while while working with
(07:30):
teams and like not just the favorite, not just in practical,
but like, yeah, reading literature and scientific
literature about how like great what what does it make to be a
great team? I came up with five major
pillars of any successful team, high performing team, team that
is more self-sufficient, more autonomous, that can manage
(07:51):
themselves and they don't need leader for every decision.
So the first thing is they have they have a clear purpose and
that's pretty obvious. Yes, you need to understand why
you're together. And the tricky part here is not
every team has that. So if if you have a bunch of
people and like just being reported to one manager, that
doesn't make them a team. They become a team only when
(08:11):
they have a shared purpose, something that they can achieve
together by collaborating and and working together and not
just by combining the individualcontributions.
So that's, that's the one important part.
The second one is linking connections.
When people are connected withinthe organization, there were a
(08:32):
lot of connections manager to employee, but what about like
people employee to employee, people, team members to team
members And more importantly, what about the connections of
this team members to other, to their stakeholders.
So it's not just the manager whogoes out to the boss, to the
stakeholders, to peers presenting the results.
So it's people, team members go now to their stakeholders,
(08:55):
understanding their needs, presenting results, taking
responsibility for the mistakes that they've made.
So that's the second part, linking connections.
The third one is integrated work.
And that that's what many leaders are missing is how do we
work together as a team? What are our team norms?
What is what do we support in terms of behaviour?
(09:16):
What kind of behaviour do you want do we want to see in our on
our team and what kind of behaviour we never want to
tolerate? So what is not tolerated on our
team? So this team knows how many
meetings do we want to have? Like what are the communications
channels that we're going to use?
It creates a lot of clarity and it removes frustration from
(09:36):
people. OK, what's next?
The 4th 1 is collaborating decisions.
How do you make decisions on your team?
Because you as a manager, you don't have to make all decisions
on your own. And then finally, knowledge
sharing and feedback. How do you as a team learn and
grow together? How you learn from your
mistakes, how you give feedback to each other, how you collect
(09:57):
feedback from your stakeholders?So those five pillars, clear
purpose, linking, connections, integrated work, collaborative
decisions, and knowledge sharingis what will make your team
click. Have you seen anything that like
you, let's say you have a clientthat you help them build high
(10:18):
performing teams. Do you, have you seen any cases
where they used to be performinggreat, but recently they've
started phasing out certain things that they're doing
because of changes in technology?
Have you seen anything like that?
Well, I have AI have an example of a of a team.
I'm not sure they were like super high performing team, but
(10:39):
they were recently like they were pretty decent before AI, it
was a customer success team. They were like working with the
clients, pretty happy together, engaged, working well.
It's a good team and at some point, and they were a good
team, they were curious about new things.
So they implemented and started using AI quite a lot.
(11:01):
So they they had that conversation with clients.
The conversation was recorded. They had a transcript of this
conversation. AI generated insights from the
conversation. They uploaded it to CRM.
Some of the items went to backlog and then AI helped them
generate agenda for the next meeting with the client.
So I mean, a lot, a lot was automated.
(11:21):
Everyone was happy. They had lots of time.
They had to like pick up the projects that they didn't have
time for before they had some time to breathe and kind of OK,
relax and not behind all like the days all the time.
But here was what happened next.At some point during the, the
team meetings, they, they couldn't like recall some of the
(11:44):
things they used to know about their clients.
They used to know they're like, like, you know, but now they,
they keep forgetting they need to go to the, to the CRM to look
at their insights that they havenot generated that were created
by AI. They couldn't prioritise items
for, for the backlog because, OK, they didn't have this
understanding what's more important for their clients
(12:06):
because again, they, they were not the ones who generated those
items. It was AI and they started to
feel like they're losing connection with their work.
They became just operators, putting data from one source to
another operate, helping AI do the work for them.
But they lost the meaning. They lost meaning, they lost
engagement and like eventually they lost productivity because
they were not so much involved in everything that's happening
(12:29):
by their clients. And that's when I joined this
team and kind of helping them to, to be like, to regain their
like get the engagement back andproductivity and become more
efficient with AI and how they use AI.
And So what they did is well, they started again with, with
why with a clear purpose. Why, why are we using AI?
(12:52):
Like what are we using AI for? What's what's in it and what is
what should stay with us as a team?
What's our word value proposition for organization for
our clients? Again, this, this understanding
and feeling of what the clients need and being able to support
their needs the best way possible is what should stay
with them as humans, as teens. And some of their automated work
(13:14):
can be created by AI. And the next thing they did is,
I don't know if you've heard about it.
There's a research called Your Brain on ChatGPT that tells that
if you like ask AI to do something and then like try to
edit it, your brain is disengaged and it stays
disengaged for like the whole project.
(13:36):
But if you do something, if you initiate the draft, if you do
something 1st and then ask to edit it or get some input, your
brain stays engaged longer. So what they did is they before
generating insights from the conversation and from the
transcript at the end of each conversation, when the
conversation was over, they kindof just was speaking, speaking
(13:56):
some things that they thought ofthis conversation, their
feelings, they got the insights,the idea, and then AI generated
insights based on what manager said and they're trusting the
conversation. So they were the first one to
give this input. They still own the conversation,
they still own the result. And then, well, they had team
(14:16):
meetings when they looked at those insights, looked at the
backlog and they were like, really, really go deep into that
and analyzing what's there and saying, OK, this is relevant,
this is not relevant. So they they they became part of
the process rather than just theobservable support AI is doing
for that. Yeah, you know what?
That sort of made me think of two real life scenarios.
(14:40):
One, phone numbers. So now you just hand your phone
to whoever they put the phone number in, you call them to like
give them your own phone number.That was the transactions.
So the numbers have not even gone into your brain at all.
So it's kind of similar to that.Another one is if you are, if
(15:01):
you work in a restaurant and you're the person taking the
order and you pass it to the chef, you may remember what it
is, but that was like really just the level.
And you may not even remember ifthere's like 100 customers.
So what you pointed out about you being the first engaging
(15:21):
your brain, I think that's like a really, really good point
because there are many things that we are starting to do it
like that. If you have to go somewhere, put
the address in the GPS, you may not remember how you get there.
I know that happened to me a fewtimes.
So by them kind of taking back that ownership of the insides of
(15:41):
the idea, how have you seen themgone back on track?
Well, they started having this conversation, well, first of all
between themselves when they started, when they, they engaged
in team meetings discussing the outputs, the inside the backlog.
Well, not only they understood it better because they.
(16:02):
Understood it better. OK.
But they also had again had a chance to talk.
We love connection with people. We love working together.
We love like seeing how ideas are built on ideas that we
share. Something someone fixed it up,
what's the question? And that not only helped them
understand better their clients,but it also helped with the team
(16:24):
climb and how they feel together.
Yeah. And I feel like they may have
insights that AI will never be able to generate for them
because we understand situationsdifferently.
And you sort of have to feed allthe new ones into AI for it to
give you like a well-rounded suggestion or insights.
So I'm glad. So what you were describing like
(16:46):
it never touching their brain, is that what you call cognitive
offloading? I mean it's it's it's a, it's a
term and this term is actually what you like properly described
with phone numbers and GP and GPS.
It's deal with that for quite a while right there when we
offload some of the information from our brain to technology,
(17:06):
which is good. I mean, there's so many, like
there's so many things we need to remember.
So that's so much information. We don't need to remember it
all. So at some point, cognitive of
loading is helping us to, to live with this excessive data
that we have around us. But when you offload too much,
when you like, one thing is a floating data numbers and things
(17:28):
like that. The other thing is when you
offload decision making. And that's when things go wrong.
And that's, that's the difference between like
automation and AI, because with automation, you don't expect
anything from a machine. But with AI, we kind of think
we're talking to a human being. We kind of have a real
conversation. We kind of assume that this
(17:49):
thing is telling us the truth, that this thing knows, which is
not true. So that's why it's very
important to be mindful about how much do you want to upload
to AI and at this, you know, lose this connection with your
work. So what in your opinion?
So besides data and like everyday business scenario, what
(18:12):
else would be suitable a suitable category of information
to offload and what they people should definitely not offload
like you mentioned decision making.
Yeah, I mean, there are lots of things we can offload.
Whether we cannot and should notoffload is something that needs
empathy and and human to human connection.
And a great example is you never, should never fire a
(18:32):
person with AI, with the help ofAI.
And there was A, and it's true and it sounds ridiculous.
There was a company that was a post on LinkedIn and some CEO or
CEO or some of the company they mentioned, like a relay of lots
of people here was an AI tool you can like reach out to and
talk to make you feel bad about that.
(18:53):
Oh, that's that's, that's so bad.
This post was bleeded but Internet remembers everything so
the screenshots are there. But yeah, things like that
should never be delegated to AI.And if you work with again, high
sensitive data, obviously, and be very mindful about like who
is getting access to that data. And again, it thinks AI telling
(19:18):
us they're not true. I mean, it depends on how you
train this AI, but it's if it's generated AI, they're not true.
They have probabilities that AI predictions based on what it
knows. So and always checking,
rechecking their output that AI gives you is a critical skill.
For now, at least, we'll still need to do that.
(19:40):
Do you have any good success cases like we can step away from
just focusing on AI? How has your biggest success
been going into a team and trying to fix, quote UN quote,
fix their issues and turn them into a high performing team?
Great question. I'm a lot of indicators of of
(20:01):
high performing great team. One of them is how much revenue
they can generate, how much theycan perform.
I've been working with company that.
Increased performance 3, three or four times.
But they were really pretty goodteam to be honest.
So the transformation they they've been through was, was
successful because they're very good team.
(20:23):
But I have an example where there's a lot of conflict on the
team. It's it's a manufacturing
company and the CEO reached out to me say, hey, like I have a
lot of conflict on my team. People cannot make, make
decisions together. They think the ID is better.
So when I joined the team and westarted having those
conversations, team sessions, ithappened that that well, people,
(20:46):
all of them, they were really engaged and they're really
motivated in company success. They just saw it differently.
Some saw that they need to focuson quality, others so that the,
the, the most important thing isdistribution channels and things
like that. So one of the things we did
together is apart from like being clearly, clearly being
(21:06):
clear on the purpose of the team, we created a list of
behaviours like what are the behaviours that the team wants
to see and wants to support and want to see more of like sort of
the keep it up behaviours, behaviours that need to stay on
the team. And what are they cut it out
behaviours, behaviours that they're not going to tolerate.
(21:28):
So they had the list, they had the list of keep it up behaviors
and carried out behaviors and all.
Eventually they, they had like they started to have meaningful
conversations with each other. They learned how to work
together. They moved forward and I think
it was a success. But the most interesting thing
happened about six months after when the CEO reached out to me
(21:48):
and said, you know what, we're moving fine.
We're going in in that direction.
A lot of conversations, lots of argument, but they're not like
personality conflicts, but people really bring in some
ideas and challenging them. Yeah.
And the team decided that the sales leader needs to go.
Why? Because she didn't follow the
(22:11):
keeping up behaviors and she constantly demonstrated some of
the cut it out behaviors and theteam mentioned that several
times. She didn't change and and the
team, they decided that she needs to go.
It wasn't C the CEO, it wasn't like the divorce.
It was the teams that she's not part of our team because she's
not following what we agreed to follow altogether.
(22:34):
I think that's that's a great example of TNB more
self-sufficient brand. They don't need their leader to
make every decision. They can make decisions on their
own. If they can solve problems on
their own, they can be more autonomous and they moving
without delay because they can make those decisions and they
can, they can do that. Are the clients that you work
(22:54):
with, are they like more concentrated in certain
geographies or you work with different people in different
continents? I actually, yeah, I was
counting, OK, how many countries?
I've been working with people inIndia, in Zimbabwe, in Latin
America, US mostly it's North America and Europe, but
Australia, yeah. And it's, it's, yeah.
(23:16):
I I love this opportunity to work with any like people from
any country like due to again, due to technology.
Yeah, 'cause what I wanted to ask is, you know, like I know
one of your effort is to help teams be like, to avoid burnout,
both burnout for the leaders andburnout for the team.
(23:36):
And in the example that you gave, the team can make
decisions themselves so they don't have to go to a leader
every single time. That hierarchy sort of depends
on the culture. To some cultures, that is fine.
Some cultures you the final say,still come from the top.
So how? How do you balance the culture
(23:57):
versus the nature of a high performing team and how to keep
people from burning up? That is, I mean, that's I love
that question. And and the the the best thing
about like a high performing team and how they're formed is
that the team themselves, they people on this team, they decide
what works for them best. If they think that the manager
(24:18):
need to have a final word, they can do that.
The cultures were like company organizational cultures.
When they say you work hard, youwork 1212 hours a day, like
you're not getting promoted for five years, but you'll get in
return like rapid growth or healing skills or whatever.
(24:39):
So it's it's a very clear contract and a very clear
agreement. So you can have any type of
culture you want I guess, as long as you sit together and
agreed on your team norms and team goal.
I haven't really thought about it that way, but that is a very
good tactic to kind of frame people's mindset before they go
(25:02):
into how do we get to become a high performing team.
So there's this like cycle of you have farming, storming,
norming, performing. So that's a typical cycle of any
team. Some teams may skip some.
Some teams may be stuck in Yeah Storming, for example, and they
(25:23):
come to you. Yeah.
But again, it's not a cycle. It's it's more like a spiral
because like with with any new challenge, with any new member
coming in, coming out, you go through the same cycle again
over and over again. So and then it's important for
men to kind of catch those cycles and make sure that to
help team go through that cycle because they will repeat.
(25:46):
Yeah. Now with technology like what
would be something that any leader or team members who are
burned out, anyone listening whowants to make a change so that
they can use AI to help them better, What would be something
that you would suggest they start?
To actually depends on the on the stage of AI and like
(26:09):
wireless. Yeah yeah in the company like
personally for themselves where they are because I mean I know
there were people who are using AI daily, but companies just OK
thinking should we do it? Should we not So they are in the
different like levels. But well, first is being curious
about what's there, like how it works, being curious about like
(26:31):
not only how should I use it, but also like what's really
happening when AI produces some outcomes.
Like the thing I mentioned that it's not true, it's predictions
like how actually LLMS work and start trying it out, make
mistakes, be mindful about the outcomes again, like repeat the
(26:52):
cycle, learn something else, tryit out, share with other people,
see what they're doing. And that's how we learn.
Yeah, the theme of curiosity, what has been floating through
the whole Mind Blend series so far, is like to keep an open
mind and iterate, learn from your mistakes.
Yeah, well, that's that's the drive of the progress.
(27:13):
Yeah. What would be your worst case
study? That it's always something that
you talk about as like casual family gathering or dinner party
or something. I have AI, have an.
I have an example. I was, I was having a
conversation with the CEO when Ifound one company and well, they
said that they value, I think itwas either transparency or
(27:37):
honesty, like transparency or honesty, probably honesty was
their value and and they wanted and they want to build honest
relationships with their customers.
And he talked a lot about that. But like throughout some
conversations, trust, hey, it was trust.
So he was talking about trust and he wanted to build trustful
relationship with with the customers.
(28:00):
But like while talking to that person I found out that he's not
paying full salary for the employees.
OK. Like using some like kind of
schemes to minimize taxes as OK.You talk about trust, how people
can trust you if you're doing things like that and like the
response was OK, You don't understand how to lead a
(28:21):
business. You cannot lead a like you
cannot run a business if you don't do things like that.
I mean, what happened a few months after that?
Is that one of the suppliers so brought bad product and and some
of the customers got quizened because of that product.
Wow. OK.
And I mean, if you if you build your relationship on trust, you
(28:45):
need to make sure everyone can trust you.
But if you build, if you like, if you're trusting here and not
trusting there, make sure you control everything like very,
very thoroughly. Because the trust is one thing,
but like if you're lying on someother things, it like it
destroys your culture and finally it destroys your
(29:06):
business. So that is a great example of
how I declare values and not actually part of the company and
how it can do in a company. Yeah, like you mentioned it in
the beginning, like the pillars of high performing team, like
shared values. Yeah.
So for this last part, let's play something out of the
(29:27):
ordinary. So I have a few rapid fire
questions. Just like really quick whatever
comes to your mind, say it. What's 1 human skill you think
is underrated in the age of AI? Well, we simply talked about
curiosity. I have this curiosity in my
mind. I think like we, we
underestimate curiosity and we underutilized curiosity to be
(29:48):
more curious and open to new things.
Yeah, I am 100% with that. So you've worked with, like
many, many continents, What culture taught you the most
about teamwork? It's it's not like culture, it's
again that don't put labels frompeople based on their origin.
(30:08):
Like see the human we as a leader, you have 10-8 people on
your team. We can learn about them as human
beings without labeling them like based on their culture.
Yeah, yeah, I see this a lot. It's not intentional, but people
will be called Oh the the, the Scottish guy like the Chinese
(30:31):
guy. Yeah, know them by their name.
Call them by their name. OK, When you feel mentally
overloaded, what's your go to way to reset your mind?
I studied practice in Tai Chi was in Canada.
I love it. Tell tell me more like I'm
interested. Well, like I used to do yoga
like long, long time ago. And I went, OK, I need to get
(30:53):
back to yoga. I could get back to doing yoga,
but I couldn't do that. It's important.
My husband shared a video with me and like a lesson and I was,
I was impressed with the wisdom is that can't let go together
with with the body movement and and the wisdom for me was very
(31:15):
important. And the point is that we you
cannot achieve anything with force.
This force is just one black powder, one thing, but you need
to be able to release, and that is as powerful as force if you
do it right in the right way. And this balance between like
(31:35):
moving forward and releasing andletting go is what I'm
practicing in my business and life.
And Tai Chi is is really helpingme with that.
Interesting because I see peoplein parks sometimes doing Tai chi
in the morning and like I have amental image of the movement
(31:56):
just because like I grew up in Asia.
But interesting that helps with business too.
So complete this sentence. I wish AI could.
I wish AI could change the worldfor the better.
I'm not sure if it's possible. Well.
This is why we're having this conversation today.
(32:19):
Like, I think if we can early onadopt A healthy mindset of using
AI and how we should use it to help us, partner with us, even
not just like an operational tool.
If more people can think of things like this, then yeah, we
can change it for the butter. Like we have so much more
information. Humans.
(32:40):
Can yeah, it itself will not do anything.
I, I do want people to walk awaywith like knowing this AI
shouldn't be used on its own. We should always be the humans
in the loop. Well, thank you very much for
having this conversation with me, Daria.
I will leave your information inthe show notes so anyone who
(33:03):
would like to continue this conversation, they can get in
touch with you or you can leave us a comment and we'll keep the
conversation going. Thanks for having me.
Thanks for listening to this episode of Mind One.
Maybe you enjoyed the conversation.
Don't forget to follow and shareit with anyone who needs to hear
it. And let's keep the conversation
going. Connect with me on LinkedIn or
(33:25):
leave me a comment. Until next time, stay curious,
keep exploring, and let's continue to blend our minds and
discover what's possible.
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