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70% Change Management & People:
The Truth About AI Transformation
Pierre talks with Ernesto Pagano of BCG about how companies
are implementing AI across different business functions.
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9 September 2025
With guest Ernesto Pagano
In this episode of The Shift Code Podcast, host Pierre Le Manh is joined by Ernesto
Pagano, a Managing Director and Senior Partner at Boston Consulting Group (BCG), to
share insights on the real-world implementation of AI across industries, focusing on
transformation challenges, organizational approaches, and practical success factors.
 
Meet Our Guest
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Ernesto Pagano
Managing Director and Senior Partner at Boston Consulting Group (BCG)
Ernesto Pagano is a Managing Director and Senior Partner at Boston Consulting Group
(BCG), specializing in AI transformation and digital innovation across creative
industries. With vast experience in managing complex AI implementations, he leads
strategic transformations for major media and entertainment companies worldwide.
His work spans multiple regions, including significant expertise in Asian markets,
particularly in the gaming and social commerce sectors.
Full Transcript
Read Episode Transcript
Introduction
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ERNESTO PAGANO
I cannot think of a project right now where there is not some AI component
to it.
PIERRE LE MANH
Hello, Ernesto. How are you doing?
ERNESTO PAGANO
Hello, Pierre.
PIERRE LE MANH
So, Ernesto, you are the global head of the media and entertainment
practice at BCG, and I'd like to take this opportunity of us being in Cannes to
understand how companies are actually using AI today in the world of
media, entertainment, and creative industries.
ERNESTO PAGANO
So they're using AI in many ways, with a different level of maturity, but
everybody is using AI. Let's start from that. I think the key thing is to what
extent.
Safe vs. Risky AI Adoption
ERNESTO PAGANO
So, the areas where everybody is using AI are support functions. So, finance,
HR, legal, IT, and so on. The reason being that those are areas where the
risks are a little lower and it's less controversial to use AI there. And the main
goal there is to standardize, find efficiencies, and automate things.
Then you have the core business, and there are two really main streams
there. There are the creative industries where they're not using AI as much.
They're still using it to some extent, but because of ethics and because of IP
and because of the relationship with the creators, it's a little bit controversial
there. So it's a little bit more of a safer, slower approach. And then there are
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other industries where there's less creativity involved. It's still media, but it's
dealing with IP that they own or IP that is more standard, but it's not as much
about IP rules that they need to respect. So in those areas, they're using AI
to automate the time it takes and the cost it takes to create content. So think
of news, think of textbooks, and similar. So in those areas, even though that's
the core business, those companies are using AI.
PIERRE LE MANH
So it's interesting. Like, a lot of things you're saying here are fascinating,
especially when you start to say they use it for support functions because
it's less risky. That's, to me, a little weird in a way. Is it really less risky to use
AI when you do finance, legal, HR?
ERNESTO PAGANO
When I say risky, I mean, you're not exposed to what your customers or your
creators are going to say. Because as you know, in Hollywood, there's a lot of
debate about the fair use of AI. So they're using AI also in the core business.
It's just that they're doing pilots. They're rolling it out more slowly. But there is
a lot of applications of AI, for example, in FX, in post-production, in editing.
There are many places where they're using it. It's just that they're going
slower. And you're not seeing it being used to the large scale that we're
seeing, for example, in IT, in tech, where there is now a big rollout of Copilot.
So and there are expectations of big efficiencies there.
PIERRE LE MANH
Mostly to automate software development?
ERNESTO PAGANO
Yes.
PIERRE LE MANH
Do you see this as potentially killing a lot of jobs, to be honest?
ERNESTO PAGANO
Yeah. I think entry-level jobs, yes.
PIERRE LE MANH
Entry-level jobs. Yeah.
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ERNESTO PAGANO
I think you still need the upper layers because you need to monitor. You
need to control. You need to ensure that there is the right data governance,
the right cadres, that the use of AI is consistent with the strategy of the firm.
So entry-level, yes.
Augmenting, Not Just Replacing
PIERRE LE MANH
So we're seeing in the US, for instance, like, a lot of statistics showing that
entry-level jobs are disappearing. It's very difficult for young people out of
college to find jobs, even from top-notch universities. Do you see this
already happening? For instance, at BCG, does it have an impact already? I
started as a consultant. A lot of the stuff that I was doing at the time when I
started was, you know, taking minutes, doing some research, things that are
vastly automated now with AI. Right? So how does it work?
ERNESTO PAGANO
So there are two ways in which you can make value out of AI. One is to hire
less and find efficiencies. And then there is another way, which is to do more
with the people you already have. So at BCG, we're definitely using AI to do
more with the people we have, and we're continuing to hire. Maybe we're
hiring less than we would have without AI, but we continue to grow. We
continue to hire. Because at the end of the day, the business is growing, and
we need the talent to use AI in the right way. What is changing is that we're
using AI to automate some of those tasks that are not as value-added.
I'll give an example. Today, we have a big repository of data and documents,
which is all the prior work we've done with the right levels of safety and
security and privacy. As a consultant, now you have a chatbot, and you
engage with the chatbot to understand what prior work has been done that
is relevant. Before, you had to use a traditional search methodology to find
the materials, then you had to read it to understand whether it was relevant
or not. Now the AI is doing that for you. So that's much faster. So that's an
example of the productivity improvement.
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Another example is that we used to spend a lot of time drafting the story of
a presentation, and then you have to create the slides one by one. We now
have a tool called Dexter that creates the first draft of the presentation for
you end-to-end in PowerPoint with content, with some prompts based on
proprietary content at BCG. So these are two concrete examples of how
we're using AI to augment what the consultants are doing.
AI Transformation: 70% People
PIERRE LE MANH
Yeah. In project management, we're seeing the same thing, right? Many
reports are being automated. You can spend less time doing the pure
production of outputs and focus more on managing stakeholders, managing
risk, building your team. So, Ernesto, I'd like to understand now from your
standpoint and what you're seeing, so you're managing so many AI
transformation projects. How much of that is your current business, by the
way? How much of your business is about AI transformation today? Just for
us to get a sense of how top of mind it is for the C-suite.
ERNESTO PAGANO
Yeah. So I can tell you about my personal work. I don't know. I don't have the
data at the tip of my finger of how much AI work BCG is doing. It's a lot. For
me, it's a majority of the work I'm doing. I would say I cannot think of a
project right now where there is not some AI component to it, but the AI
transformations are a majority of the work I'm doing for sure.
PIERRE LE MANH
So how do your clients typically manage these projects? They are usually
complex, corporate-wide. Are the outcomes very clear? Do they apply
proper project management techniques, or is it completely experimental?
How does it work?
ERNESTO PAGANO
Companies are doing it in very different ways, so there is not one or two
ways in which they're doing it. At BCG, we believe that AI transformation is
10% technology, 20% tools and processes, but 70% is change management
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and people. So, obviously, we have clients with the end-to-end
transformation. The technology has to be the right one and the processes
have to be in place, but we spend a lot of time with change management.
The reason is that change is hard. People like doing things in certain ways,
and they want to change the way that they do things. Also, it's scary
because many people don't know how to use AI in the right way, and it's not
easy to upskill so many people quickly. So we spend a lot of time on the
people side of the equation.
And in terms of project management, we treat it as a transformation as we
used to treat those transformations in the past with other innovations that
we've experienced. So we have a dedicated team of consultants that
spends a lot of time really engaging the customers to ensure that also the
change is driven by the organization as opposed to imposed by us. That's
for me the biggest mistake I see, that sometimes consultants may come in
and impose things top-down, then they have a 200-page document that
tells you everything to do. Then the moment we leave, nothing happens. So
that's the wrong way of doing it. So the way we do it, we work side-by-side
with customers. It takes longer. Sometimes it's frustrating because we wish
things moved faster, but we need to make sure that this is a cooperation,
and customers have to buy into the idea.
Responsible AI and Agility
PIERRE LE MANH
And anything really unique to AI transformation projects? For instance, for us
at PMI, what we're seeing is you need to have probably more attention to
data, to governance, to privacy issues, to ethical concerns, to sustainability
consequences of this. And also because the technology is not stable, it's
evolving very fast, those projects tend to be a little bit more fuzzy in terms of
what are the outcomes that you're expecting, so you have more agility
maybe in the way you operate. Do you also see that?
ERNESTO PAGANO
Absolutely. So responsible AI is a big topic for sure. Data infrastructure, data
governance is extremely important because if you don't have the right data
in the right place, you cannot really use it in the AI world. Agile for sure,
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because when you're doing a pilot using a specific LLM, maybe in six
months you need to change. So I need to make sure that you have enough
flexibility to test and update as you go.
Centralized vs. Decentralized AI Strategies
PIERRE LE MANH
Yeah. And by the way, we have our own now AI project management
certification, the Certified Professional in AI-powered Project Management
(CPMAI). I'm not surprised we do. Yeah. Many of the things are the same, but
you do have some specificities, definitely, which leads me to another, maybe
even broader topic. Do you think that AI is changing the way companies are
managed? Are companies more agile by nature trying to implement a
technology that is not fully baked yet and without knowing exactly what the
use cases will be? Like, do you feel this need for more corporate agility, or do
you feel that on the contrary, because you operate in such an uncertain
environment, you need more structure than ever?
ERNESTO PAGANO
It's a great question. I don't know if there is one answer for all companies.
For sure, everybody has to change. How you change, it depends. And, I can
tell you that I've seen a couple of archetypes. There are some archetypes
where the clients are deciding to centralize things because they want to
gain scale, and they want to make sure that there is one way of doing AI and
that that investment will yield ROI for all the businesses and the products
they have. That's one way of doing it, and that allows you to have scale, to
have consistency, to show that the right governance is in place, that
responsible AI principles are respected and so on. There's another
approach, which is a little bit extreme, is that you have each product or each
business actually experimenting with it. And what that means is that you
might have more innovation, more pilots, but then it might be harder to scale
and to have synergies across the businesses. These are two extremes.
PIERRE LE MANH
Have you seen anything work better so far?
ERNESTO PAGANO
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It really depends. I think you need both. In an ideal world, you are in a world
where each business feels that there is freedom and autonomy to innovate.
But when things work, then you can quickly scale them up so that you can
invest behind it. Because one of the problems I've noticed is that there are a
lot of pilots, but then those pilots are not being adopted.
PIERRE LE MANH
That's what you need.
ERNESTO PAGANO
That's what you need project management. That way, where you need the
framework so that companies can work differently so that they can invest in
different things, but then pick those that are worth scaling up.
Global Perspectives
PIERRE LE MANH
Yeah. Last question. I understood. Last time I met with you, I ran into you,
remember, in this hotel in Tokyo. You have a very global... I remember that.
Yeah. So you're a very global person as well. You see companies from all
across the globe. Do you see any differences? Or is corporate America... let's
put the Chinese world a little bit on the side. They have their own tools, their
l b t i th t f th ld ll d i b h t' h i i
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