Hey, everyone. Welcome back.
Today, we're going to be taking a deep dive
into the world of tech leadership.
Specifically, how it's being totally transformed by AI, right?
Exactly. We've got this fascinating transcript
from a McKinsey Live event called
Redefining the Role of the Tech Officer.
And it's all about the impact of generative AI and all that.
Think of this deep dive as your cheat sheet
to understanding how AI is changing the game for tech leaders.
But also, and this is key, what it means for you.
Like, no matter what your job is.
Yeah, because this isn't just a tech thing anymore.
This is like reshaping everything.
It really is, and the numbers are pretty mind-blowing.
McKinsey's research suggests that generative AI
could add a whopping $4.4 trillion.
Wait, trillion?
Trillion with a T to the global economy.
Wow, that's like, what, the entire GDP of Germany or something?
Pretty much.
Crazy. It's no wonder companies are jumping on this AI bandwagon.
Yeah, I mean, 65% of enterprises are already using generative AI in some way.
65%.
That's more than double the rate from just a year ago.
That's a huge jump.
So with all this AI craziness going on,
what's happening to the people leading the tech charge?
It's definitely forcing tech leaders to evolve, right?
Like, their roles are changing big time.
So how are they adapting?
McKinsey outlines four major shifts they're seeing.
Protector, operator, orchestrator, and builder.
OK, I'm intrigued.
Break those down for us.
What does it mean to be a protector in this new world of AI?
It's all about cybersecurity, but the stakes are so much higher now, you know?
Yeah, cyber attacks are getting scarier by the day.
Cybercrime could cost the world something like $10.5 trillion a year.
That's insane.
And it's not just some future threat either.
Downtime from these attacks is already costing global 2000 companies.
Yeah, those big companies.
Yeah, like $400 billion every year.
Ouch.
That's a lot of money down the drain.
And here's the kicker.
Only about 30% of enterprises feel like they're actually
well protected from these threats.
That's a surprisingly low number.
You'd think with all the technology at our fingertips,
we'd be better prepared.
But here's the thing.
It's not just about having the latest fancy tech.
So what else is there?
McKinsey found that a lot of these outages, like up to 60% of them,
aren't even caused by tech failures.
Really?
What are they caused by that?
Outdated processes, like clunky, inefficient processes.
Huh.
So it's not the machines.
It's the humans.
In a way, yeah.
So even if you're not a tech leader, this applies to you.
Think about those processes you use every day at work,
or even in your personal life.
Yeah, like how I still use sticky notes to remember my passwords.
Exactly.
Are those processes as efficient and as secure as they could be?
That's something we all need to be thinking about.
Got it.
So back to those tech leaders for a second.
How can they up their game in this protector role?
McKinsey has some really solid advice.
First, don't try to protect everything at once.
OK, so prioritize.
Exactly.
Figure out your most critical assets, like the 20% that drive
80% of your business value.
The MVPs of your company's data.
Exactly.
Focus on protecting those first.
Second, shift security considerations
earlier in the development process.
So bake it in from the start rather than trying to fix it later.
Exactly.
Like if you're building a house, it's
easier to lay a strong foundation from the beginning, right?
Makes sense.
Retrofitting security always feels like a Band-Aid solution.
And finally, tech leaders need to be champions for digital trust.
What does that look like practically?
Clear policies, transparency about how you're using customer data,
effectively managing those third party risks.
So basically, walk the walk and don't just talk the talk
when it comes to data security.
Exactly.
Because in this world where data is everything,
trust is non-negotiable.
All right, makes sense.
So we've talked about protecting the organization,
but what about that second shift you mentioned, the operator role?
What's that all about?
This is where things get really cool.
This role is all about harnessing the power of tech
to optimize how a business actually runs.
So we're talking about using AI to streamline everything.
Totally.
Think generative AI for boosting administrative tasks,
automation to make supply chains smoother,
AI powered tools for speeding up R&D.
So AI is like the ultimate efficiency guru.
Right.
And the potential gains are huge.
It's interesting because McKinsey highlights
how this shift is changing the very structure of some companies.
Like one global life sciences company actually
merged the roles of their CIO and chief strategy officer.
Oh, wow.
That's interesting.
I hadn't heard that.
Yeah, they recognize that, especially with AI in the mix,
technology and business strategy are basically inseparable now.
Yeah, they're two sides of the same coin.
So it's not just about changing job titles.
It's about a whole mindset shift.
So tech leaders need to think less like techies
and more like business leaders.
Yep.
They need to understand the company's big picture goals.
And figure out how to use tech to achieve those goals.
Exactly.
It's like, how can we leverage technology
to make this company more successful overall?
So do you have any real world examples
of how this is playing out?
How are tech leaders actually operating in this new way?
Oh, for sure.
Let's take the banking sector, for example.
One bank decided to give their CIO responsibility
for customer experience.
By connecting technology directly to customer needs,
they saw awesome improvements in both their digital offerings,
A&D customer satisfaction.
It's like they're breaking down the silos between the tech
department and the rest of the company.
Exactly.
And that's a big part of the shift.
Tech leaders are becoming key players
in shaping the whole customer experience.
And driving strategic initiatives.
It's a far cry from the traditional view of the CIO,
as the person who just keeps the servers running.
Right.
It's a much more dynamic and strategic role.
And this is happening across all kinds of industries, too.
Tech leaders are really stepping up.
They really are.
So we've gone from protector to operator.
What's next in this tech leader evolution?
That brings us to the orchestrator,
which is about leading big changes
across the entire organization.
So we're talking about big picture strategic leadership.
Totally.
It's about driving the strategy and making
sure everyone's ready to embrace things like AI and all
these emerging technologies.
But wouldn't that be kind of overwhelming?
Oh, for sure.
It's a lot to handle.
Yeah, like where do you even start?
What are some of the challenges?
Well, it's about managing people, processes,
and technology all together in a way that actually works.
It's not just, hey, here's this new software.
Use it.
It's about more than just new tools, then.
Right.
It's about creating a culture of innovation and collaboration.
Got it.
McKinsey actually uses their own in-house AI platform
called Lily as a case study for this orchestrator role.
Lily.
Tell me more about that.
What makes it such a good example?
So about a year and a half ago, McKinsey
realized that they had all this valuable knowledge
trapped inside the company, hidden
in all these different departments.
So all their expertise was siloed.
Totally.
And it was really hard for people
to find the information they needed.
So their tech team took charge and created
this generative AI platform called Lily.
Sounds impressive.
It basically makes all that knowledge accessible
to everyone in the company.
So Lily was like this big company-wide transformation
project.
Exactly.
And here's a cool detail.
50% of the people working on Lily
weren't even from tech backgrounds.
That's awesome.
Yeah, it really highlights how important collaboration
is in this orchestrator role.
So it's about bringing together all these different people
with different skills and perspectives.
Exactly.
OK, that makes sense.
But how can someone actually make
this shift from being an individual contributor
to becoming an orchestrator?
What are some steps they can take?
McKinsey actually outlines six key shifts
that are super important.
I'm listening.
One is building teams with both tech and business people,
not just one or the other.
Yeah, breaking down those silos again.
Right.
Then there's things like continuous upskilling
programs for everyone, not just the tech folks.
So everyone needs to be on board with this AI stuff.
Absolutely.
And then there's treating data as a product, something
that can be used across the whole company.
Instead of just hoarding in one department.
Exactly.
But that also means you need good data governance,
solid infrastructure, all that good stuff.
It's like laying the groundwork for a data-driven culture.
And of course, you need vision and leadership.
Tech leaders need to be proactive, set the agenda,
and make sure everyone's on the same page.
Working closely with the CEO and all the other bigwigs.
Right.
So it's a lot to juggle, but it's super important.
Sounds like it takes a pretty unique mix of skills.
Oh, yeah, for sure.
Technical expertise, business smarts, leadership abilities.
It's not just about understanding the tech.
It's about understanding how to use it
to make the business better.
Absolutely.
All right, so we've gone from protector to operator
to orchestrator.
That brings us to the final shift
you mentioned, the builder role.
What's that all about?
This is where things get really interesting.
Think of it like this.
Tech leaders are now taking full responsibility
for the profit and loss of external products.
So not just internal tools anymore.
They're creating things that make money and compete
in the marketplace.
Exactly.
They're becoming entrepreneurs within their own companies.
That's a huge shift in responsibility.
Do you have an example of what that
looks like in the real world?
Sure.
McKinsey has a great one from the e-commerce world.
There is this life sciences company,
and they asked their tech team to build an e-commerce
platform.
For what?
It was for renewing subscriptions,
like on those products that aren't super popular.
Seemed like a pretty basic project, right?
Yeah, not exactly groundbreaking.
So what happened?
Well, the tech team saw an opportunity to do more.
They didn't just build the platform and call it a day.
They got ambitious.
They dug into the data, analyzed customer behavior,
and realized there was a huge unmet need.
For what?
For a more personalized, easier way
to buy those less popular products.
They used data to completely change the game.
That's pretty awesome.
Yeah.
They ended up creating a whole new business model,
expanding beyond just subscription renewals.
And it was all driven by the tech team.
Yep.
They used their expertise to build
a platform that let customers buy a wider range of products
tailored to their specific needs.
It led to a big boost in revenue and happy customers.
So the tech team wasn't just building a product.
They were shaping the company's strategy.
Exactly.
That's the power of the builder role.
They're not just techies anymore.
They're innovators.
They're strategists.
They're driving real business value.
It's making me think about my own role
and how it might be changing with all this AI stuff
happening.
I think it's a question we should all be asking ourselves.
Whether you're a CEO or a product manager or a marketer,
this AI revolution is going to impact how we work.
It's not just about keeping up with the latest gadgets
and gizmos.
It's about understanding how to use technology to achieve goals
and create new opportunities.
Couldn't have said it better myself.
OK.
So we've covered a lot of ground here, from protector to operator
to orchestrator to builder.
It's clear that tech leadership is evolving at warp speed.
But let's be real.
Most tech leaders are already super busy.
Yeah, they wear a lot of hats.
So where do they even begin to implement all these changes?
That's a great question.
It can definitely feel overwhelming.
But luckily, McKinsey did a bunch of interviews
with CEOs, tech leaders, and board members
who have been through this and come out the other side.
So they've got some real world wisdom to share.
Oh, yeah, they do.
And it boils down to a few key things.
All right, lay it on us.
First, shift your mindset.
You're not just a functional leader anymore.
You're a business leader, a people leader, a change agent.
So think bigger picture.
Exactly.
Second, set aspirational goals.
Figure out which of these four roles, protector, operator,
orchestrator, builder, really resonates with you
and where you want to focus your energy.
Third, you've got to get the CEO and other execs on board.
Their support is crucial.
So build those alliances early on.
Yeah, and don't be afraid to take initiative.
Identify opportunities where tech can solve problems
and just go for it.
So be proactive.
But also, don't forget about your existing commitments,
right?
You've got to live around those, too.
Oh, absolutely.
Flawless execution is key.
You've got to build that trust and prove
you can get things done.
OK, so you're a reliable leader.
You're delivering on your promises.
But what about those hidden obstacles that can trip you up?
Like McKinsey talks about this thing called tech debt.
Oh, yeah, tech debt.
That's a big one.
Can you explain what that is for our listeners who might not
be familiar with the term?
And why should they care?
Tech debt is kind of like the hidden cost
of using outdated tech and inefficient processes.
It's all those shortcuts and quick fixes
that pile up over time.
So it's like building a house on a shaky foundation.
Eventually, it's going to collapse.
Exactly.
And a lot of companies don't even realize
how much tech debt they have.
McKinsey estimates that like 20% to 40%
of many companies' balance sheets
are tied up in tech debt.
Wow, that's a huge amount of resources
that could be used for something better.
Right.
Imagine if all that money was invested in innovation
and growth instead.
So how does tech debt actually impact a business?
What are some real world consequences
we should be worried about?
Well, it can slow you down big time.
It can stifle innovation, make your operations more expensive,
and even hurt your relationships with customers.
Yeah, if your systems are always crashing
and your data is messed up, no one's going to be happy.
And it's easy to let tech debt build up
because it happens gradually.
You take one shortcut here, another quick fix there,
and before you know it, you're drowning in it.
So for anyone listening who's thinking, oh, crap,
I think we might have some tech debt,
what can they do about it?
Where do you even start?
The first step is admitting you have a problem, right?
Do a thorough assessment of your tech and your processes
to figure out how bad this situation is.
So it's like taking inventory of your technology.
Exactly.
Once you know what you're dealing with,
you can start making a plan to tackle it.
OK, so you've identified the tech debt.
What's next?
Do you just rip and replace everything?
Not always.
It's more about being strategic and focusing
on the areas that will make the biggest difference.
You might need to modernize some legacy systems,
clean up some code, maybe even get rid of some applications
altogether.
So it's about making smart investments that
will pay off in the long run.
Exactly.
It's a long-term commitment, but it's worth it.
By reducing tech debt, you can free up resources,
become more agile, and create a more sustainable tech
environment.
It's like getting rid of all that dead weight
that's been holding you back.
Exactly.
And speaking of being prepared, McKinsey
also talks a lot about business resiliency,
especially when it comes to those unavoidable system
outages.
Yeah, because no matter how much you prepare,
sometimes things just go wrong.
Right, so it's not just about preventing outages.
It's about being ready for when they happen.
So how can tech leaders make sure their companies are
prepared for those moments when the tech goes kaput?
Well, one key thing is to test your systems regularly
and plan for different scenarios.
Work with your business partners and vendors
to simulate different kinds of outages.
So like a fire drill, but for your IT systems.
Exactly.
By practicing your response, you can minimize the downtime,
reduce the disruption, and protect your company's
reputation.
Because when things go wrong, it's
how you handle it that really matters.
Absolutely.
And don't forget to include your vendors in these drills,
because a lot of outages actually
come from third party systems.
Communication and collaboration are key.
Always.
You know, throughout this whole conversation,
it's really striking how much technology and business
are becoming intertwined.
Oh, yeah, absolutely.
It's not just about coding and servers anymore.
It's about understanding how technology
can drive business outcomes.
And that's especially true with the rise of generative AI.
It feels like a whole new way of thinking about the role
of technology in business.
It is.
And as AI gets more embedded in how businesses run,
tech leaders really need to get fluent
in the language of business.
So it's like they need to become bilingual,
speaking both tech and business.
Exactly.
They need to be able to translate
those complex technical ideas into something
that business people understand and vice versa.
So those soft skills are becoming just as important
as technical chops.
Oh, absolutely.
Communication, collaboration, strategic thinking,
those are all essential now.
And McKinsey also talked a lot about the need
for continuous learning and development,
not just for the tech teams, but for everyone.
Yeah, in this world of crazy fast technological change,
everyone needs to be constantly upskilling.
It's like investing in your people.
Exactly.
And it's not just about technical skills either.
It's about those soft skills we were talking about.
Communication, collaboration, problem solving, adaptability.
Because the only constant is change.
Right.
And McKinsey also had some really interesting insights
about how data needs to be managed differently
in this new AI era.
Yeah, tell me more about that.
Well, for a long time, data has been kind of siloed
within different departments.
Each department hoarding its own data.
Pretty much.
But to really unlock the power of AI,
companies need to start treating data as a product
that everyone can use.
So breaking down those data silos
and creating a more data-driven culture.
Exactly.
And that means having good data governance policies,
strong data infrastructure, and a commitment to data quality.
So it's a big shift in how we think about and manage data.
It is.
But it's essential if we want to fully realize
the potential of AI.
OK, so we've covered a lot of ground here,
from tech debt to business resiliency
to the importance of soft skills and data management.
I'm sure some of our listeners are feeling
a bit overwhelmed by all this.
Yeah, it's a lot to digest.
But luckily, McKinsey has some great advice
on how to get started.
Start small.
Pick one or two areas where you can make a real difference.
Don't try to do everything at once.
Build a strong team around you, people who share your vision.
And don't be afraid to experiment and learn as you go.
So it's about embracing the journey
and being open to new possibilities.
Exactly.
And remember, it's OK to not have all the answers.
Yeah, asking questions and learning from your mistakes
is all part of the process.
Totally.
The most important thing is to be proactive,
be willing to adapt, and never stop learning.
It's a marathon, not a sprint.
Well said.
You know, one of the themes that has really stood out to me
today is this idea of the tech leader as a change agent.
Yeah, that's a powerful concept.
It's not just about keeping the lights on anymore.
It's about leading the charge into the future.
Exactly.
And that takes a different kind of leadership.
It takes vision, courage, resilience,
and a passion for innovation.
They need to be able to paint a picture of the future
and get everyone excited about it.
They do.
And they need to be comfortable with uncertainty
because the tech world is constantly changing.
So being able to adapt and learn quickly is crucial.
Absolutely.
And building strong relationships is key, too,
both within the company and with outside partners.
You can't do it alone.
Nope.
You need a strong network of support and expertise.
And McKinsey also emphasized the importance
of being proactive.
Oh, yeah, that's huge.
Tech leaders can't just sit back and wait for things to happen.
They need to be driving the change.
They do.
They have a unique opportunity to shape
the future of their organizations,
but they need to seize that opportunity.
Be bold.
Be visionary.
Be relentless.
I love it.
So for our listeners out there, if you're a tech leader
or you're hoping to become one, what's
the one key takeaway you want them to leave with today?
The future of tech leadership is about being bold,
being visionary, and being relentless
in your pursuit of innovation.
Don't be afraid to challenge the status quo,
push the boundaries, and use technology
to create a better future.
So it's not just about the technology itself.
It's about the impact you can have with it.
Exactly.
And that's what makes tech leadership so exciting.
You have the power to make a real difference in the world.
I love that.
So it's not just about coding and algorithms.
It's about making a positive impact.
Absolutely.
Well, I think we've given our listeners a lot
to think about today.
We have.
What's one final thought you want to leave them with
as we wrap up this deep dive?
The world is changing faster than ever.
And technology is at the heart of that change.
It's an incredibly exciting time to be a tech leader.
But it's also a time of great responsibility.
The decisions you make today will shape the future.
So be bold, be thoughtful, and never stop learning.
It really is.
It's a call to action for all of us, no matter what our job is.
Definitely.
This AI thing, it's going to touch
every part of our lives.
So we've got to figure out how to use it for good, right?
Absolutely.
It's all about being proactive, being curious, and just
being open to change, I think.
Yeah.
The future belongs to those who are willing to learn and adapt.
To kind of evolve with it all.
Well said.
So for everyone listening out there,
I want to leave you with this one thought.
We spent this whole episode talking
about how tech leadership is changing with AI, right?
We've talked about those four big shifts.
Protector, operator, orchestrator, builder.
We talked about all the challenges like tech debt,
making sure businesses are resilient,
the importance of soft skills, all that stuff.
But now, it's time to take all this and apply to yourself.
OK, yeah.
Think about your own job, your industry, what you
want to achieve in your career.
How is this AI revolution impacting you?
What opportunities are out there for you?
What can you do today to get ready for the future?
Yeah, that's the question, isn't it?
It's about taking control.
You know, don't wait for someone to tell you what the future's
going to be.
Go out there and create it.
I like that.
Make it happen.
Yeah, exactly.
Thanks for joining us on this deep dive
into the world of tech leadership.
It's been fun.
We hope you learned something new
and we hope you're feeling inspired.
Yeah, go out there and make the future awesome.
Until next time, keep learning, keep growing,
and keep pushing the boundaries.
See you.