Unlock the secrets of generative AI's profound impact on the business landscape in our latest episode, where we promise you'll gain insights into how this evolving technology can transform your workplace. We've invited top industry experts to dissect the hype and uncover AI's true potential for enhancing company culture and sparking creativity. Using the metaphor of AI as a new fruit tree, we explore how its long-term benefits might outweigh immediate returns. Listen in as we tackle the challenge of bringing stakeholders on board and share practical strategies for integrating AI into your business, such as establishing AI labs and fostering a culture of experimentation.
As we stand on the brink of a new AI-driven era, education becomes the cornerstone of responsible integration into our daily lives. This episode emphasizes the necessity of teaching both technical and essential soft skills like critical thinking and adaptability. Our discussion highlights this societal shift and the roles we play in ensuring AI's development and use are ethical and wise. We delve into how AI can be a valuable partner in decision-making, challenging leaders to lead by example and create learning environments that benefit everyone. Engage with us as we call for action to shape a future where AI serves the greater good.
Episode Transcript
All right.
So today we're diving intogenerative AI and specifically
its impact on businesses.
You know we hear so much aboutAI these days it's almost
impossible to avoid, but we'regoing to try to get beyond the
hype and really understand whatit means for how we work, and
for that we've got some, somegreat conversations for people
who are really thinking deeplyabout this stuff.
Speaker 2 (00:20):
Well, I think it's fair to say there's a lot of
excitement around AI, especiallygenerative AI, but there's also
a lot of confusion.
You know, businesses want tojump on the bandwagon, but it's
not always clear how to actuallyuse it strategically.
Speaker 1 (00:33):
Yeah, that makes sense.
I've heard it compared to likeimagine this new fruit tree just
appears one day right.
It's full of juicypossibilities, but not everyone
knows how to cultivate itproperly.
Speaker 2 (00:43):
I like that analogy, but you juicy possibilities but
not everyone knows how tocultivate it properly.
I like that analogy but youknow, it makes you think.
Maybe the real value isn't eventhe fruit itself.
It's the shade the treeprovides or the ecosystem it
supports, the way it enrichesthe whole environment.
Speaker 1 (00:55):
So you're saying the true ROI of AI it's not always
obvious right away.
It's not just about those quickwins, but also those less
tangible benefits that mighttake time to unfold.
Speaker 2 (01:07):
Exactly.
We're talking about things likea shift in company culture, a
boost in creativity andengagement.
These are things that are hardto measure with traditional
metrics, but they can make ahuge difference to a company's
success.
Speaker 1 (01:19):
But how do you convince stakeholders who are,
you know, fixated on numbers andspreadsheets?
How do you convince them toinvest in something when the
full potential might not beobvious right away?
Like, how do you even measuresomething like a more creative
workforce?
Speaker 2 (01:34):
That's the million dollar question, right and
honestly, something a lot ofcompanies are struggling with.
It does require a bit of a leapof faith, a willingness to see
beyond the immediate bottom line, but there is data out there.
Some studies have shown thatcompanies with more engaged
employees tend to be moreprofitable and innovative.
Speaker 1 (01:51):
So there is evidence that a more engaged workforce
can lead to better businessoutcomes.
But even if you can convincestakeholders, there's still this
learning curve right?
Not everyone's comfortablejumping headfirst into the world
of AI.
Speaker 2 (02:03):
Oh, absolutely.
One speaker we looked at saidit's like being handed the keys
to a super sophisticated car,but without any driving lessons.
Kind of intimidating, right.
Speaker 1 (02:13):
Yeah, you don't want to crash this expensive car, but
I guess the point is we're nottalking about self-driving cars
here.
We're talking about AI.
That requires a certain levelof understanding to operate.
Speaker 2 (02:23):
Right.
It's a tool, not a magic wand.
Like any tool, it takes timeand practice to master.
We need to get over this fearof making mistakes and create a
culture of learning andexperimentation.
Speaker 1 (02:34):
It's like that Swiss army knife analogy Everyone's
got one, but most people onlyuse the basic blade.
Never explore all those othercool tools tucked away inside.
Speaker 2 (02:42):
Exactly, and that's what we see with AI Companies
using it for basic tasks but notreally tapping into its full
potential.
Speaker 1 (02:49):
So how do we encourage people to dig in and
discover those hidden features,those aha moments where they
realize, wow, I can actually usethis for that?
Speaker 2 (02:57):
It's about creating a culture that encourages
exploration and doesn't punishmistakes.
You've got to reward those whofind creative ways to use these
tools and share those successeswith others.
Speaker 1 (03:09):
And that's where leadership comes in right.
It's not enough to just tellpeople to embrace AI.
Leaders need to be activelyinvolved themselves.
Speaker 2 (03:15):
Absolutely.
If you want people to beexcited about using a Swiss army
knife, show them how you'reusing it to solve all sorts of
interesting problems.
Don't just tell them it's cool.
Show them how cool it can be.
Speaker 1 (03:26):
Lead by example right .
Show people that AI is apractical tool, not just some
abstract concept.
Speaker 2 (03:32):
And that's especially important when you consider
this whole idea of theproductivity paradox.
Speaker 1 (03:37):
The productivity paradox.
What's that?
Speaker 2 (03:38):
Well, it's this ironic situation where AI is
supposed to free up our time,but learning to use it
effectively actually requires aninvestment of time up front.
Speaker 1 (03:48):
So we need to invest time to save time, which feels
counterintuitive in ouralways-on hyper productive world
.
But if we don't make thatinitial investment, we're
essentially stuck with thatbasic blade on our Swiss army
knife, never going to experiencethe full potential of the tool.
Speaker 2 (04:03):
Exactly.
It's a tough sell.
That's why it's so important tohave leaders who understand
this paradox and are willing tocreate space for that necessary
learning and exploration.
Speaker 1 (04:13):
So how do companies actually do that Create that
space for exploration withoutsacrificing productivity in the
short term?
What are some practicalstrategies that leaders can
implement?
Speaker 2 (04:24):
Well, I think it starts with recognizing that
exploring AI it's not just someoptional side project.
It needs to be woven into thefabric of the company, how it
operates.
Speaker 1 (04:33):
So you're saying it's not enough to just have like a
training session here and there.
It's about really integratingAI into the workflow, the
culture, the mindset of thecompany.
Speaker 2 (04:43):
Exactly.
One approach is to create whatsome companies call AI labs or
innovation teams.
Give people the time andresources to just experiment
with different tools andapplications, like a sandbox
where they can play around, testthings out without the pressure
of immediate results.
Speaker 1 (04:59):
That makes sense.
Speaker 2 (05:00):
Yeah.
Speaker 1 (05:00):
But what about companies that don't have the
resources for a dedicated AIteam?
What are some more practicalways to encourage this kind of
exploration?
Speaker 2 (05:08):
Well, even small changes can make a big
difference, you know.
Encourage employees to setaside even just 30 minutes each
week to explore a new AI tool orexperiment with an existing one
.
Host internal workshops orlunch and learns where people
can share their discoveries.
Speaker 1 (05:24):
Oh, I like that.
It's about creating thoselittle pockets of time for
experimentation and learning,rather than expecting people to
find the time on their own.
And it doesn't have to be thisbig formal thing.
It could be as simple as sayinghey, team, let's all spend 15
minutes today playing aroundwith this new AI image generator
and see what we come up with.
Speaker 2 (05:41):
Exactly Make it fun and engaging, not just another
task on their to-do list.
And remember thisexperimentation shouldn't just
be limited to technical teams.
Ai has the potential to impactevery department, from marketing
and sales to HR and finance.
Speaker 1 (05:57):
Right, it's not just about the coders or data
scientists, but how do we getpeople who might be intimidated
by AI or who don't see therelevance to their work?
How do we get them on board?
Speaker 2 (06:07):
Communication is key.
Leaders need to clearlyarticulate the company's vision
for AI and how it aligns withtheir goals.
Explain how AI can helpindividuals be more effective,
free up their time, maybe evenopen up new career opportunities
.
Speaker 1 (06:21):
It's about painting that picture of how AI can
benefit them personally, notjust the company as a whole.
But let's be realistic.
There are going to be somebumps in the road, right?
Not every experiment is goingto be a success.
Speaker 2 (06:30):
Yeah.
Speaker 1 (06:31):
How do we create a culture where people aren't
afraid to fail?
Speaker 2 (06:33):
That's where it's crucial to shift the mindset
around failure.
Instead of viewing it as anegative, frame it as an
opportunity for learning andgrowth.
Encourage people to share theirfailures as much as their
successes.
Speaker 1 (06:45):
I like that Normalizing failure as part of
the process, not something to beashamed of.
Hey, we tried this crazy thingwith AI and it didn't work.
But here's what we learned andhere's how we can do better next
time.
Speaker 2 (06:56):
Exactly, and this goes back to leadership.
Leaders need to model thisbehavior themselves.
Don't be afraid to talk aboutyour own AI experiments, both
the successes and the failures.
Speaker 1 (07:06):
It's like saying look , I'm not afraid to try new
things, even if it means I mightmess up sometimes, and you
shouldn't be either.
It creates that psychologicalsafety for innovation and
risk-taking.
But how do we go beyond justexperimentation?
How do we actually ensure thatthose AI experiments are leading
to tangible results?
Speaker 2 (07:24):
Well, one approach is to start with small,
well-defined projects, projectsthat have a clear connection to
business outcomes.
For example, instead of tryingto revolutionize the entire
marketing department with AI,focus on a specific task, like
automating social media postingor personalizing email campaigns
.
This way, you can demonstratethe value of AI in a more
(07:45):
concrete and measurable way.
Speaker 1 (07:47):
It's about having those quick wins that can build
momentum and demonstrate the ROIof AI in a way that
stakeholders can understand.
And once you have those earlysuccesses, you can start to
scale up and tackle more complexprojects.
Speaker 2 (08:00):
Exactly.
It's also important toestablish clear metrics for
success from the outset.
What are you actually trying toachieve with this AI
application?
Is it increased efficiency,improved accuracy, higher
customer satisfaction?
By having those metrics inplace, you can track progress
and demonstrate the impact ofyour efforts.
Speaker 1 (08:18):
It's about moving beyond those vague notions of
like boosting creativity orimproving engagement.
It's about being able to sayhey, by using AI for this
specific task, we were able tosave X amount of time, increase
revenue by Y percent or achieveZ level of customer satisfaction
.
Speaker 2 (08:35):
And that data becomes crucial for building a business
case for further AI adoption.
It provides that evidence thatstakeholders need to justify
continued investment.
Speaker 1 (08:43):
But it's not just about the numbers, right,
there's also this human elementwe need to consider.
How do we ensure that AI isbeing used ethically and
responsibly?
How do we avoid thoseunintended consequences that can
sometimes arise when weintroduce new technologies?
That's a huge point andsomething we definitely can't
ignore.
We've talked about thepotential of AI, the challenges,
the strategies, but it allcomes back to using this
(09:05):
technology responsibly.
We're talking about tools thatcan write like a human, create
images, even code.
That's a lot of power, and wehave to think about the
implications.
Speaker 2 (09:16):
Absolutely, and it's not just about avoiding the
negative.
It's about using AI to makethings better.
You know, a better future, amore equitable world, a more
sustainable world.
And we have to be careful aboutbias in the data.
Make sure AI is helping humans,not replacing them.
Speaker 1 (09:31):
Yeah, the job displacement question.
That's a big one, a lot ofanxiety around that, but it
seems like the more realisticscenario is that AI changes the
type of work we do, not that iteliminates work altogether.
Speaker 2 (09:43):
Exactly.
Think about the car.
It didn't get rid oftransportation, it transformed
it.
Ai will probably be similar.
Some tasks will be automated,but that frees up humans to
focus on other things.
Speaker 1 (09:55):
So it's not humans versus machines.
It's more like humans andmachines working together, each
using their own strengths.
But we probably need to thinkabout how we train people, help
them adapt to this new way ofworking.
Speaker 2 (10:06):
That's where education comes in.
We need to teach people aboutAI, how to work with it, even
how to shape its development.
And it's not just about thetechnical stuff, it's critical
thinking, creativity,adaptability.
Speaker 1 (10:21):
So those soft skills, those human qualities, maybe
they become even more importantin the age of AI being able to
think critically about theinformation we're getting, to
know what's real and what's not,to ask the right questions, to
use AI as a partner.
Speaker 2 (10:30):
Exactly.
It's not enough to just knowhow to use the tools.
We have to use them wisely,ethically, really understand
what they can and can't do.
Speaker 1 (10:37):
This has been a fascinating conversation, and I
think it shows that AI isn'tjust a technology.
It's a societal shift how wework, how we learn, how we
interact, even how we defineprogress.
Speaker 2 (10:48):
And that's what makes it so exciting.
Right, we're at the beginningof something new and we have a
chance to shape it, make itsomething that benefits everyone
.
Speaker 1 (10:55):
So, as we wrap up our deep dive into generative AI,
the question I want to leave youwith is this what role do you
want to play in all of this?
How will you embrace AI whilealso making sure it's developed
and used responsibly?
Speaker 2 (11:09):
It's a journey we're all on, and the choices we make
now will determine where we endup.
Speaker 1 (11:14):
That's a great thought to end on.
Thanks for joining us for thisdeep dive into generative AI.
We hope this has given you somevaluable insights and maybe
even more importantly, a renewedsense of curiosity and
possibility as we navigate thisnew landscape together as
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