How do you lead a workforce through a moment
when the speed of change outpaces the average
worker's ability to keep up? This is one of the
questions I hear everywhere I go, from board
rooms to front lines to conference halls and
today's guest, he's someone that sits right at
the heart of this conversation. His name's David
Martin, he's a senior partner at BCG and the
leader of their people and organisation practice.
where he spends his days helping companies rethink
skills, roles, culture and working patterns all
as AI is reshaping every corner of the workplace.
And he also serves on BCG's global AI leadership
team which gives him a rare vantage point over
the adoption divide that he's widening between
those who instinctively fold AI into their daily
rhythm and those that just keep hitting friction
at every step along the way. Sound familiar?
Well, our conversation today will move through
the patterns BCG is seeing across more than 10
,000 survey respondents. He'll explain why AI
fluency is increasing in some pockets while new
joiners are stalling at the starting line, why
middle managers are quietly becoming the heavy
users and why frontline workers still lack that
hands -on learning that they need to thrive.
but we'll also explore together the reality behind
those big headline claims about productivity
jumps in engineering and customer service and
look at how the biggest gains only arrive when
companies rewire the whole workflow rather than
just drop a tool on top of an existing process
so yeah, that means we're going to be talking
about leadership behaviours the psychology of
learning under constant disruption under honest
fears around shadow AI that many leaders are
quietly trying to contain right now. So the theme
that we'll run through everything David will
share today is this phase of AI change has very
little to do with shiny new models and everything
to do with people, trust, skills and confidence.
So how do you lead through all of that with clarity
and care? But now. It's time for today's interview.
Let me introduce you to today's guest. So a massive
warm welcome to the show. Can you tell everyone
listening a little about who you are and what
you do? Yeah, sure. So my name is David Martin.
I'm a senior partner at BCG. I lead our people
and organization business unit. So everything
around talent and skills, organizational and
operating model design and culture and change
management. And then I serve with a cross -functional
group of folks on our AI leadership team globally.
Awesome. And of course AI continues to be a huge
topic. It's been what three years since chat
GPT first arrived. We have the early adopters,
those that are caught in pilot phase, not getting
out. I've got to ask, what do you see as the
main reason behind this growing divide between
those AI fluent teams and those that are just
struggling to keep up and struggling to get out
of those pilot phases and into life? Yeah, you
know, it's funny because i was really impressed
with how quickly and broadly companies started
to attack this i think what we see with folks
who are getting value out of it is they're actually
doing fewer things and attacking it bigger and
more holistically which was surprising to us
um companies that are still struggling are the
ones who you know we're approaching it by what
we call a thousand flowers blooming and they
took on You know hundreds of use cases across
the organization but thinking about it very narrowly.
And because of that it's really hard to capture
value if you save you know five minutes of someone's
time of week i'm translating that into dollar
impact is really difficult so they're doing fewer
things bigger. And I appreciate this is a question
that everybody wants the answer to right now,
but how can an organization move beyond simply
providing AI access to actually enabling their
employees to use it confidently and effectively?
Cause we're three years down the line now. So
you think we'd start to see more happening. Yeah,
for sure. It's funny because, and we especially
see adoption lagging on the front lines and Part
of it is because people have so much day -to
-day work to do. You ask employees and they say,
I just don't have time to learn the tools. And
so one thing that organizations are starting
to do well is full immersive training. I think
what we've also seen is in our workshop is just
not sufficient to help someone understand how
to use it effectively in their day -to -day life.
So they're doing more immersive training. They're
building awareness. They're providing access
to good quality tools. And we're also seeing
leadership behavior being a big contributor.
And so I think our recent data showed that supportive
leaders have employees who are four times more
likely to use the tools effectively. And so leadership
behavior obviously another big piece there. Wow,
I never saw that one coming I must admit because
I've heard so many stories of some bosses some
teams outright banning issues because of the
fear of the data etc Which is a valid point,
but there's workarounds around that now, but
training is it's a great point I mean, why is
AI training still such a gap for frontline workers?
And what kind of hands -on learning make is making
the biggest difference? So one of the other reasons
I asked that I was speaking somebody recently
and I was said inside the average organization
It's the people at mid -tier at that organization.
They're the heavy users, not the junior users,
not the C -suites. What's going wrong with training
here? Well, OK, so maybe a couple of things.
And your stat, I think, is spot on. We saw 90
% of middle managers using it at least once a
week, I think it was, where frontline lags significantly.
I would say that for the frontline folks using
it, they are much more frequent users and probably
more effective users in the middle managers.
And so we do look at volume and effectiveness
of usage and adoption, not just, you know, weekly
usage. Yeah, at the front line, I think one big,
one big piece is what they have, you know, their
everyday work to do. And so the tools need to
be relevant for the work they're doing. It's
not just using chat GPT to summarize emails or
to write emails. It's actually If you're a software
engineer, it's using Claude code or cursor to
write your code more effectively. And marketing,
same thing on content creation. If you're an
HR professional, you're using some of the embedded
tools inside of your HR IS. And it's really difficult
for employees to keep up with just how fast the
ecosystem is changing. And we saw this in software
engineering. We were working with a large tech
company. and their engineers were using it about
once a day, but they had no idea the capability
of the tools that had recently rolled out. And
so their ability to use things like the model
context protocol and some of those tools that
Claude has rolled out is just far lacking relative
to what the capabilities are. So that immersive
training helps, I think, really educate people
on what the... the quality of the capabilities
are and how impactful it could be for your day
-to -day life. And middle managers, I would say
it's slightly less so. It's more in that chat
GPT world, which is great. And we do know that
leaders and managers who are using tools have
their frontline employees using them more effectively,
but they're seeing a little bit less value at
that layer of the organization than the frontline
employees who are using it well. And you mentioned
everyone from tech teams, software engineering
to marketing teams who are largely unaware of
some of the capabilities of this technology.
So on that side of things, what role does leadership
play in helping accelerate AI adoption across
a company? And I'm curious as well, what behaviors
separate those successful leaders from the more
cautious and hesitant ones? Yeah, so I think
leaders Generally embrace the notion that they
need to communicate to their employees that the
employees need to be using the tools. But a good
leader is actually using the tools themselves
so they can understand the capabilities and the
disruptive change. But I think above that is
curiosity. I think there's a lot of apprehension
for leaders to actually reinvent themselves.
And what you'll see, I think, going forward at
all layers of an organization is that curiosity
and the always on learning mindset is critical
and leaders who exhibit that we do see are much
more effective at helping their frontline drive
it. I would say the other thing is communicating
a vision for how they view work to be in the
future. We've seen a lot of leaders get overwhelmed
by just how fast the world is changing and the
uncertainty. And employees can pick up on that.
And leaders who are able to actually craft a
vision of where they think their function's going,
or if you're a CEO, where you think the organization's
going, and communicating to employees on how
they fit into that vision, you see much larger
uptake of the tools. Whereas if you don't do
that, you see increased amount of fear of job
loss. And obviously, there's just a lot of uncertainty
that employees you know aren't very comfortable
with if you don't have a good leader communicating
that vision. And we started 2025 talking about
the ROI, the big questions that organizations
were asking as they were struggling with scattered
AI experiments caught in pilot phase. Then it
evolved, all the conversation evolved into agentic
AI and the work that agents were doing. We're
recording this at the end of the year now and
begin to look back and look ahead at what could
be happening next year. How have you seen organization
shift from those AI experiments at the beginning
of the year to true workflow transformation that's
driving that real measurable business impact?
Are you seeing that this year? Yeah, you are.
And I do think that customer service, marketing,
software engineering, some in the back office
functions like FP &A and some HR functions, you
are actually starting to see not just experimentation
and pilots, but but really strong value coming
from the investment there. And it is to your
point, you have to start with thinking about
the workflow end to end and identify not just
places where you can use AI, but identify what
that new workflow looks like and what the role
of agents are in that workflow. And then consequently,
what the role of the humans are. Sometimes that
includes redefining roles. And that's why companies
who you see have done it really well in 2025
have also redefined roles and they have redefined
competencies in that as well. But the biggest
thing they've done is think about the workflow
end to end. If you go back to software engineering
as a good example, the tech company I mentioned
earlier, when you started just by looking at
the workflow, you saw the engineers were only
spending 35 % of their time with their hands
on the keyboard. And the other 65 % was going
back and forth with the product manager on getting
clarity on the requirements and working downstream
with quality assurance and deployment. And so
if you don't address some of those upstream and
downstream parts of the workflow, then even if
you're driving huge productivity increases on
their time spent coding, you're still only at
a fraction of what the opportunity is. So start
with the workflow and then think about how GNI
fits into that. not the other way around. I love
that. And as I said this year, AI agents has
been talked about everywhere. Adoption has remained
relatively low as I think companies try and get
to grips with the capabilities there. But anything
you're seeing that's holding companies back and
how do you see their role evolving next year?
Yeah, a couple of things. You mentioned it earlier.
I do think data quality to some degree is holding
some companies back. And so they're having to
address just some of their core infrastructure.
Maybe more importantly is apprehension or risk.
I do think there's like, and maybe well justified
reservation from companies about turning over
too much of the workflow to be run by agents
because there's this fear of either hallucinations
or alignment risk or a variety of risks that
they want to figure out before they embrace that
too much. And the last one would just be, I don't.
I think a lot of companies just aren't familiar
with the possibilities or the capabilities of
some of those tools. I think what we saw, 70
% of employees said they had heard about agents
and only 15 % could describe what they actually
are. And I think that mirrors a lot of companies
too, which certainly has inhibited adoption.
Another topic this year is how IT has added Shadow
AI to the list of losing battles. Others on the
list of course would be Shadow IT. before it
was BYOD, but I mean, with more than half of
employees more than willing to use unauthorized
AI tools on their machines and devices, how can
businesses strike that right balance between
the innovation and the increased capabilities
and productivity? And as an XIT guy, that governance,
you know, the boring stuff. Yeah, it's incredible,
right? Like one of... company's biggest concerns
is not being able to get employees to adopt it.
And then we see the data that says 50 % are using
it for work outside of their IT infrastructure,
to your point, which is kind of ironic. One is
access to quality tools. I think we see if companies
aren't providing quality tools to their employees,
then they are finding ways to go outside of the
enterprise ecosystem and use tools. And then
the other thing I would say is Just really, really
good quality training. And I think specifically
on that one, there's huge risk for an enterprise
that needs to be managed. I think by both IT
and HR, um, about using tools outside of the
enterprise, um, IT infrastructure, obviously
there's, you know, huge risk with that. It's
not just an IT job though, to help navigate that
risk. It is an operating model. and a culture
change that some companies have to have to make
sure that their employees understand the risks
and that they practice the right behaviors. The
other piece on that shadow IT, which is maybe
not surprising, is you see while 50 % of employees
are using tools outside of the ecosystem for
Gen Z, it is far higher. And so you would expect
that trend to only increase if companies don't
get on top of it quickly. Yeah, such a great
point. And when I was doing a little research
on you before you came on the podcast, one of
the things that I found was that you said that
the secret to AI success is 10 % algorithms,
20 % technology, and 70 % people and processes.
And it is so true. So for people that may disagree
with you, why does that human factor matter so
much in this equation? Because I think it often
gets lost in large organizations, but it's more
important than ever, isn't it? Yeah, well, and
this is based on empirical data. We were on consistent
tracking surveys and this data that you mentioned,
the 10, 20, 70, as we call internally, is been
consistent really since companies started investing
in digital transformations even prior to AI.
And the people process is so important. I mentioned
earlier just reimagining the workflows and how
critical that is, but clearly talent. And culture
also just really important drivers of a company's
ability to get a return on investment. And so
if 10 % is data, then 20 % is the tech infrastructure,
as you mentioned. You still have to have really
good, high -quality talent managing that other
30%. And we do see companies who have been early
adopters and companies who are what we define
as leaders. They're actually extending their
lead and a lot of it is because of the people
in process You see those companies attracting
better talent and so consequently they're able
to realize value more effectively and more quickly
in their investments But yeah that the 70 % on
people in process is huge And you are in a fantastic
position here. You get to not only speak to customers
and clients all around the world, but you also
get access to a lot of information, a lot of
data, a lot of reports. So when you put all this
into your own little AI in your brain, what excites
you about the road ahead from everything that
you're seeing and hearing? I think a lot of us
are in the consulting business because there's
a little bit of ADD in us and we love change
and we love to, you know, just to be a part of
What's at the bleeding edge? And I think what
excites me is just the amount of change we have
in front of us and and really the quality of
life improvements that will come out of this
as well. I think there's really exciting opportunities
and in the field of health care like back to
your point on us having, you know, pretty good
data and pretty good visibility across a lot
of industries. I'm I'm really excited about the
impact AI can have on humanity and solving some
of our most complex challenges, whether it be
health care or food scarcity or things like that.
And then I'm just fascinated to see where the
technology takes us. I think I've seen some of
the tech leaders over the past couple of weeks
or even year just talking about how quickly some
of the breakthrough technologies are changing
and are gonna be in front of us. and as I said
you've got access to so much information now
you might find it easy it might even be more
challenging for you someone leading the road
ahead but for many people listening that pace
of technological change and how do they continuously
learn and keep up to speed with everything I
think that's something many people are going
to be thinking about as they hit 2026 and this
is what I'm going to do differently this is what
I'm going to learn and all those kind of resolutions
before we resort back to our usual self -buy
end of January but for anyone that is thinking
that How do you self -educate? How do you keep
up to speed? Any tips or anything you'd be doing
there? Well, I do listen to a lot of podcasts
and I guess I'll start by saying another piece
of data from the survey was asking people if
they're saving time by using generative AI, what
are they doing with that time? And you could
say how much of that productivity improvement
do you get? I'm to invest into your own learning
and i think right now the data showed well companies
are really demanding a lot of different things
and so they're spending it more on leisure activities
and things like that and i do think that. Spending
time investing in yourself and learning is gonna
be critical to the specific question i spend
a lot of time listening to podcasts i read as
much as i can. I have children who are. One just
started college and and I have twins who are
just about to start high school and I'm convinced
that they need to also be learning about it.
And so I'm trying to be a good role model for
them. But yeah, lots of reading and lots of podcasts
primarily. Brilliant, and I think that's a brilliant
moment to end on, but before I do let you go,
for anyone listening wanting to find out more
information about you, your work at BCG, et cetera,
or where they can keep up to speed with anything.
Anyway, in particular, you'd like to point everyone?
Yeah, so we've been pretty prolific in publishing.
We put all of that on our bcg .com website. We,
as I've alluded to a couple of times, have a...
A variety of different research reports that
are out. One is called AI at Work, which I'd
encourage people to check out. It covers a lot
of what we talked today about with respect to
training and adoption. We have research called
Build for the Future, which is some of what I
alluded to around value and return on investment.
And then we actually just this week published
research in concert with MIT about kind of the
impact of AI on the workforce. And so those would
be a couple of specific ones to check out. But
like I said, we publish significantly. People
can also, of course, hit me up on LinkedIn and
we can connect that way as well. And you can
see some of what I've been posting about this
topic. Brilliant. Well, I'll have links to everything
you mentioned there. Make it easy for people
to find out more information. Love chatting with
you today. We had a little bit of fun along the
way, but more than anything, just thank you for
sharing your insights today. Pure gold. Thanks
for joining. Thanks, Neil, and thanks for all
you do. So this is great. I think what stood
out most in that conversation was just how much
of the real progress happens far away from those
headlines in our news feeds. Yes, AI capability
is accelerating at a wild pace, yet the human
readiness that unlocks its value is often uneven
and overlooked. And David's point about immersive
learning landed strongly for me because one hour
workshop Scattered pilots might look neat on
a slide and ticking a few boxes, but they don't
move the dial It's when people receive focused
hands -on coaching and see leaders using the
tools themselves These are the moments the magic
moments where confidence rises and real change
takes hold So it's a reminder that adoption is
built through rhythm and repetition rather than
announcements and slogans So thank you to him
for bringing some much needed clarity to the
debate around AI agents as well because I think
plenty of companies are curious right now very
few feel fully prepared and that is okay but
many still need to strengthen their data foundations
before they go one of the repeated phrases I'm
hearing at conferences all over the world is
no data no AI and despite all this though optimism
from workers who understand the tools is quite
striking When people see how these agents fit
into the wider workflow and understand where
human judgment remains essential the fear fades
and that tension between excitement and caution
I think is something that could shape 2026 in
a very real way and leaders who guide their teams
with transparent communications rather than just
trying to replace people with technology these
are the ones that will benefit the most. So As
we wrap up, I'm keen to hear your thoughts. Where
do you see yourself in this adoption story? Are
you feeling energised by the pace of change or
overwhelmed by it? And if you had to choose one
area to upskill in 2026, what would it be? Share
those reflections with me because your experiences
matter just as much as the expert insights on
the show. So please head over to techtalksnetwork
.com. You can leave me an audio message there
or go to LinkedIn X Instagram, just at Neil C
Hughes. But that's it for today so huge thank
you to everyone at BCG, my guests and indeed
you for tuning in every single day. I'm conscious
I do throw a lot of interviews your way so thank
you for coming back and hopefully you'll join
me again tomorrow. Speak with you then. Bye for
now.