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What does it really take to scale AI across the enterprise? How do leaders move from ambition to impact? In Winning with AI, world-renowned AI pioneer Andrew Ng and Bain partner and digital re-invention expert Sarah Elk host candid conversations with global CEOs on the frontlines of AI transformation.
Together, they explore the opportunities and obstacles of deploying AI at scale: reimagining operating models, empowering teams, and leading culture change to prepare their organizations for the future.
Winning with AI helps leaders of global organizations navigate times of radical change with clarity and vision, uncovering the very human challenges – and opportunities – that transformation brings.
About the hosts:
Dr. Andrew Ng is an internationally acclaimed thought leader in artificial intelligence. He founded DeepLearning.AI, cofounded Coursera, and serves as an adjunct professor at Stanford University’s department of computer science. He was named one of the Time’s 100 Most Influential People in AI in 2023.
Sarah Elk is Bain & Company’s AI practice leader in the Americas, and a leading voice on digital reinvention. She partners with CEOs and senior executives to reimagine how their organizations operate – aligning strategy, operating models, and culture to turn AI into sustained competitive advantage. Sarah is the co-author of Doing Agile Right (Harvard Business Review Press), and her perspectives on leadership and transformation have been featured in the Harvard Business Review and Forbes.
Bain & Company:
Winning with AI is brought to you by Bain & Company, a global consultancy trusted by the world’s most influential business leaders. With decades of experience guiding organizations through growth, transformation, and leadership development, Bain’s executive insights offer what it takes to lead at scale.
Denis Machuel:
Adoption has been fueled by excitement and excitement has been fueled by the trust and the co-design process that we did with people. It's AI with people.
Sarah Elk:
Today, we're excited to welcome Denis Machuel, the CEO of Adecco. Adecco is a world-leading talent advisory and staffing organization focused on upskilling and recruitment.
Andrew Ng:
In addition to hearing from Denis about AI and his business with all of the popular media narratives of the AI job apocalypse, I'm also looking forward to hearing what he has to say given his data on where the labor and talent market is going.
Sarah Elk:
This is going to be a great episode.
Denis, thank you so much for joining us. It's great to have you.
Andrew Ng:
It's great to see you, Denis.
Denis Machuel:
Thanks for having me today. Really appreciate it.
Sarah Elk:
I'm so excited that you're a guest because in particular, I would love to discuss what we're seeing a lot in the press around the job apocalypse. And as somebody who's at the heart of staffing and the heart of the job market, I'm sure you have a lot to say on this topic. I know in conversations that I've had with Andrew, we're very much believers in the job creation that will come from AI, but I'm curious what you see in the data and what your perspectives are as someone who's at the heart of it.
Denis Machuel:
Sure. Well, I believe that job apocalypse is an absolute nonsense. And if I were to judge by the activity that all of us humans have at this moment with AI coming in, I'd say I think it's going to keep us busy for some time. We know that every general purpose technology has over time created as many job, if not more jobs, than it has destroyed. There's fundamentally no reason why, even though AI is accelerating at the speed that nobody has seen before, there's no reason why this wouldn't happen.
AI creates complexity, additional complexity that will have to be handled by humans on one side and there's no signal at the moment on the labor market that tells us that there's going to be massive job destruction. We see a shift in skills. We see, of course, some tasks being automated, but we also see people having to deal with agents, additional complexity that needs to be dealt with with people.
Andrew Ng:
Yeah. It feels like earlier today, my team and I were wrestling with really difficult technical problems and we're looking at each other saying, "This is such hard work. We think AI is amazing, but why isn't this AGI thing working? It feels like we have more work than ever." And it was nice seeing you in Switzerland a few months ago and you, me, Sarah have chatted before about this AI jobpocalypse. I'm with you. I think the AI jobpocalypse is nonsense, but why do you think people are telling stories about this particular bogeyman hiding under our best? Why is there this story being told? There
Sarah Elk:
Certainly isn't the evidence to back it up, at least not yet.
Denis Machuel:
No. And there's two pieces or element. There's, first of all, what we see, the Adecco Group is the world leader in career transition services, which means we accompany the people that are being laid off so that they can find a new job. And what do we see? We ask people when they've been laid off why they've been laid off. A few months ago, only 1.4% of the people that were part of layoff plans told us that they were actually replaced by AI. And if you compare that with the common narrative of CEOs saying, "I'm laying off that many people because I've replaced them by AI," there's a total disconnect between the way CEO speak about AI creating layoffs and the reality. The reason for that is it's much better today and much more attractive for investor to say that you're laying off people because of AI than to say, "Well, I'm adjusting my workforce as I've done constantly over the past whatever years to deal with the ups and downs of the economy or the investment that you make in places and that you don't make in other places." That's one thing.
The second thing is there's so much investment made in AI, in AI capabilities, in data centers, in compute capabilities that it has to be justified by immense productivity. And of course, the immense productivity is meant to come with no one else in the workplace. I think it's totally wrong, but there's so much investments that is being made that people justify that with immense productivity.
Andrew Ng:
You talked to a lot of CEOs, staffing teams, large businesses. I'm just curious, what impact is this particular story having on businesses? Is it making businesses worry about maybe they shouldn't hire when there's more ambiguity?
Denis Machuel:
Well, actually what we see on the labor market today, we see that definitely the AI narrative has slowed down to some extent the way people think about recruitment permanently, their future employees. We see that, but we have to be conscious that it's accompanied by this massive uncertainty that we have in the world which impacts the way CEO makes decisions. What we see at the same time is we see traction. We are also the world leader in flexible employment and today we are growing at very strong pace on this kind of employment, which means the economy is solid and our clients still need a lot of people to get the job done.
Sarah Elk:
Yeah. And it's interesting because the enterprise journey on agentic, if we think about just the augmentation or automation potential of agentic, we're in such early stages of that, that there's so much time for us to think about reskilling and think about more flexible work options. And I think at least my experience from a Bain perspective has been that companies have been really thoughtful on that and planful.
Denis Machuel:
Yeah. And actually if you talk about agentic, there's one thing that everyone has to have in mind, I guess it's difficult to put agents on messy processes on a messy organization because this doesn't work. And the second thing is if you want to create traction and adoption and also to properly understand how work gets done and how processes have to be adapted, you have to do it with people. We strongly believe and everything we hear from our clients is that if you want to be successful, AI has to happen with people, not to people. And it's all about how you bring the workers along, it's how you co-design the way agentic AI is going to land in the workplace that you're going to be successful at scaling agentic AI. And at the moment, a lot of our clients struggle with that.
Sarah Elk:
Yeah. Denis, could you talk more about how you've handled that at Adecco? Because I think it's a very valuable and important perspective that I wish more CEOs would more deeply understand and adopt because it seems like the common narrative is that there's a tension between being more human and automating with AI when there is a way to think about that going hand in hand and being a both and. And I would love to know how you pragmatically approach that at Adecco.
Denis Machuel:
Yeah. You talked about being pragmatic. We are a people company and we believe in human-centric AI and we believe that we have a role to play in demonstrating that we can find ways to have a harmonious workplace when people work alongside agents. The way we've done it is particularly in the core processes of how we deliver our service to our clients. For 70% of what we do, we help our clients recruit people either on a permanent basis or on a flexible basis.
What we've done is we've taken this core process and we've taken recruiters working together with the business leaders, working with the tech teams to really design the way we're going to identify that process. Let's be clear. We started with a position where our recruiters, they heard so much of this narrative, "All the recruitment is going to be done fully with AI, you're going to be useless in the future." And we were absolutely adamant to say, "No, this is not going to happen. We're going to work with you guys, yes, to put agentic AI, but to augment you and not to replace you." And we walk the talk, which means we've worked with the recruiters. We've identified every single step of the process all along, end to end.
And with the recruiters, we identified where either a task was cumbersome or not adding any value from a human perspective and where they felt that they had the most impact and progressively we've injected agents in all the tasks or subtasks that AI was very good at and kept the humans in what they are best at, which is the sort of in recruitment, the human to human connection, all the exercising judgment on soft skills, on behaviors, on all that kind of things that are not in the resume but are fundamental to a successful recruitment.
And that was done with our recruiters, which means when they started to see that AI was making them so much more productive because it was handling task at scale rather than giving 100 calls to do the first outreach to candidates, this first outreach and pre-selection can be done very efficiently if the agents are well-trained. And then rather than having to give 100 calls, you just give 10 calls to pre-selected candidates and then you go deep into, first of all, what recruiters like most, which is that human-to-human connection, but also you make them much more efficient. And when you start to do that and then the word of mouth goes across the whole enterprise, well, I enjoy my work more because I'm doing all the stuff that I love than adoption scales.
Andrew Ng:
I think that's great. I'd love to hear a little bit more about the people change management process you went through. Initially, recruiters were worried, then some of them became much more productive, much more happy than worse. We'd love to hear about that journey and how you led your organization forward on that path.
Denis Machuel:
Right. We decided to first of all replace fear by knowledge. So we trained all our colleagues with a program that was adapted to the different roles. So we created a series of personas and programs linked to each persona, which help people have the first level of understanding of what AI was about and how to use AI. And this of course linked to the role or the tech proficiency, but this first approach and this first training helped, as I said, replace this first fear that people had with the knowledge that they needed to have to sort of embark a bit more courageously in the transformation. That was the first thing. The second thing was about making sure that, as I said, that people were involved in co-design. Of course, we could not involve every recruiter, but they were aware that this was happening, that they had ambassadors of their roles that were really actively involved in the transformation.
And then when we started to scale, we really activated a narrative around this is making people more happy, this is making them more efficient, these are all the good things that are going to happen. And I must say we are also fortunate to be on very fragmented market. So we could have also an internal narrative that AI was not there to do the same thing that we do with less people. We said on the contrary, because we are on fragmented market, we're going to do so much more efficient job in serving our clients that we will expand our market share, that we expand our reach. So we're going to do more with the same number of people. So that was a little bit of a counter-narrative to the mainstream thinking that was, "Oh, AI is going to do so much with so many less people."
Creating that trust with our colleagues was fundamental in them adopting AI, not resisting to AI. And that's what we see, by the way, across. We've done a survey around how companies adopt AI and we felt from everything that we heard, survey around more than 30,000 people and 2,000 leaders, we see that trust, the way you cultivate trust in the workplace is fundamental to generate appetite for AI adoption.
Andrew Ng:
Hey, I'm curious, maybe two questions in one, but with this journey, if you're willing to share what fraction or what percentage of the teams were able to make this transition to a new way of working and then also why do more with the same number of people as opposed to do even vastly more with even more people?
Denis Machuel:
First of all, of course you have resistance. Okay, I would say we probably had, as for every transformation or change, you have one third of people who are super willing to get go and eager to learn and transform maybe one third of people who resist and one third who is going to go whichever way the success is going. We started by cultivating the happy few that we're really willing to get going, not trying to convince the people that we're not coming along. So we started with a few countries that were early adopters and then of course they were ready to live through the difficulties because there's no magic with AI. I think you know that very well. So it's hard work, it's time spent, it's investment, et cetera. And we're not done. We are not fully deployed, we're not fully adopted also because in some places the processes are not fully in place or fully in order, I would say. It's still a journey. It's still a journey.
Andrew Ng:
Why do more with a fixed number of people as supposed to do vastly more with a larger team and growing the team?
Denis Machuel:
I love your point of view and...
Sarah Elk:
He sounds like a board member. He's putting power in your growth targets. Just a casual chat, can you up your growth for me?
Andrew Ng:
It's just I know Sarah and I were both trying to hire as many good AI people, including, frankly, every good AI engineer I can find. I just can't find enough good people to grow my own team. And I think there's so many options for growth.
Sarah Elk:
It's my number one through 10 priorities, more AI engineers.
Denis Machuel:
I love your way of thinking and we will probably go this way, okay, for sure. I'm pragmatic and I want to sort of secure a critical mass of things that are running nicely and serving the clients well before I scale even more. But I appreciate your board-minded question because I'm sure I'm going to have it in my next board.
Sarah Elk:
I do think you're further along the journey than most. I think we're also seeing that those that have been on the journey for some time and are further along see how they can compound that advantage into a growth advantage and create distance from their competitors. I'm curious in the conversations that we've had, one of the real difference makers has been the posture of the CEO and how the CEO has led. Is there anything in particular that you would point to that is a core tenant or principle that you have in how you've led through the transformation so far if that's where your time has gone or things that you're paying particular attention to?
Denis Machuel:
Well, I have been very clear that this was my first responsibility. I managed this AI transformation directly. Of course, I had a team and I had a few leaders that were really actually activating and working with me, but I've been very clear to the team that I felt that I had to lead that initiative directly. I've spent a considerable amount of my time learning, discussing with you, Andrew, discussing with a lot of AI advanced leaders to be knowledgeable also myself. It turns out that I'm an engineer by education. It was a long time ago. I learned AI at university, but it was not the same AI as today, but then I updated myself in what was going on and I led it known to people. In the company, people could see that I was really extremely active on the domain pushing, being involved in the meetings and discussing with our tech partners directly.
I went of course several times to the Silicon Valley, talked to our tech partners at the highest level just to understand that this was not something on the side, but that was something core to what we have to do.
Andrew Ng:
I think that's interesting. I think I'm reflecting. I've heard you speak in public and private about AI a few times and the fact that you've gone deep enough to have an understanding of AI I think means you say sensible things rather than there are also leaders that will sometimes parrot whatever they read in the newspaper headline last week and that sets a very different tone than a CEO that actually understands enough to say consistently sensible things.
Denis Machuel:
And if I may, it's also important when you talk with your tech, we are not a tech company, but of course we use tech and we work with tech partners, for example, that provide the agent infrastructure like Salesforce, for example, with Agentforce. And it's interesting because when sometimes we have to push and in the use cases that we have today, we are pushing some of our partners to the limit and for that you need to have the top level conversations so that you are top of mind on the tech partner side because they need to push their own boundaries and it's easier when it's the CEO that says, "I need that for this particular service or this particular enhancements of the way we operate to get that done and to have traction with your tech partner."
Sarah Elk:
Denis, is that part of what led to the venture with Salesforce, this idea of sort of pushing the boundaries and being at the frontier? Could you tell us more about that?
Denis Machuel:
Absolutely. I think it's interesting because at the very beginning we were thinking about being an example of a human-centric AI adopter. And for that, because we are people company, we were discussing with several tech companies to partner with the same vision. And it's true that at that moment, the discussion we had with Marc Benioff and his top leadership team actually generated a common understanding that these tech companies didn't want to appear as the dragons that are going to destroy all the jobs, but they could also take that angle that bringing people alongside AI is the right path to achieve. And that's actually that joint venture that we started together was created by a workshop that we did two years ago and there was the Kill the Company workshop. I started this saying maybe the company is going to be destroyed by AI. So I'd better create the company that is going to destroy the Adecco Group because if I own the company that is going to destroy me, at least I have something left.
So from that Kill the Company workshop, we created this joint venture together with Salesforce that is intended to accompany the clients in the way they strategize their workforce when the workforce becomes hybrid with people working alongside agents. So that venture called our potential is there to accompany the C-suite in the way they can focus on proper AI adoption. That means helping them make the right choices, identify where in their organization they have the highest chance of successfully scaling AI on roles or tasks, but on not only that, taking the human factor into consideration rather than saying, "I'm going to get rid of all these people." Well, actually maybe these people that are being replaced for some or augmented, maybe the people that are being displaced could be useful in other roles. So immediately strategizing how you can upskill, re-skill or repurpose people in other roles and upskill and risky people that are going to have the need to work with agents properly.
Andrew Ng:
Hey, I'm curious, I've heard you say that you want 50% of your company's revenue to be part by agentic AI by the end of 2026. How are you measuring that and how is that journey proceeding?
Denis Machuel:
We've been relatively simple on that. We look at the revenue in a country that we have, for example, and we look at the way we have agents involved in generating that revenue. So if I take the recruitment process, for example, this agentification of the recruitment process now covers 50% of the revenue generated by the recruitment. So that agentification is present in all the processes that generate 50% of the revenue and we are on track because adoption has been fueled by excitement and excitement has been fueled by the trust and the co-design process that we did with people. Again, it's AI with people with the risk of repeating myself.
Sarah Elk:
That's a great message to land on. I guess before we wrap, anything else that we haven't asked you that you would love to cover?
Denis Machuel:
No, I think you covered a lot. There's maybe one thing that I have in mind which I could mention is I think we've all made mistakes when we started to embark. And I remember this dinner that we had with you, Andrew, and a few other CEOs in Davos where all of us were saying, "We started by so many of these AI initiatives, so many of these AI pilots that went nowhere," and almost all of us around the table were sharing the same thing. And there was a lot of learnings through that, but I think one of the things that I've learned through the process was, well, actually you've got to be probably a bit more intentional in where you want to apply AI because it helps you on capital allocation, it helps you on where you put your efforts, it helps you on how you embark leadership.
So the learnings on the way was probably good at the beginning to have so many of these pilots, but being intentional, being focused and deliberate in where you want to scale AI is probably, I think, one of the learnings that I would take from the journey so far.
Andrew Ng:
That's a great call. I think to me it's a reminder that, as Sarah was saying as well, in moments like these, leadership matters because deciding where to focus means making a choice rather than letting everyone try everything all at the same time. And that decision means you need a CEO, which I think Adecco was fortunate to have with the judgment as well as the courage to make some choices because choices could turn out to be right or wrong, but you make good choices. It really changes the trajectory of a business.
Sarah Elk:
Yeah. And being willing to do that in the heart of your business where you're driving competitive advantage and using AI to fuel that with humans, not against them. I love it. Thank you so much for being with us. Really appreciate it. It's been a wonderful discussion.
Andrew Ng:
Thank you, Denis. It's always been a time with you and chat with you.
Denis Machuel:
Thank you, Andrew. Thank you, Sarah, for the conversation. Really enjoyed it.