The Future Of Less Work
00:24:56 · Laurent Aufils
[00:24:56] S1: I think it's a tremendous opportunity for the HR function to completely redesign and rethink its strategic contribution to the company because skills, you know, organizational design, engagement, change management are really the key success factors for this transformation. And that's not only for the HR function itself, but it's also what HR can bring on the table discussing at the executive committee level with the peers on, you know, this transformation. I think it's very important to also have a balanced approach because we are all convinced that AI can deliver a lot of value, can bring a lot of opportunities, but we also have the responsibility to make it sustainable and to have the right guardrails in terms of, you know, ethical usage of AI, you know, the frugality around AI as well, not to use AI, you know, for things that are not necessary, for instance. And I think it gives really, it's really the right opportunity for HR to be at the center of the discussion of the strategic discussions. It's also a risk because at the same time, if HR doesn't take the seats, you know, at the table for the strategic discussion, HR can also be the HR function can also be translated into, okay, you know, you are there to execute and a lot of what you are doing can actually be taken over by AI. So, you know, it's, I think, an existential type of question for HR, but I see it very positively because for me, it's again a great opportunity for the HR function to grow and to bring a lot of value on the table for the company, for the employees and for the society at large.
00:27:07 · Nirit Cohen, Laurent Aufils
[00:27:07] S0: Thank you. So, Laurent, as we wrap up, I usually ask for one question. What do you think is the one question we should all be asking ourselves about the future of work? [00:27:22] S1: I think the one question I will ask is when we decide not to use AI and it has to be a decision and it's very... You know, now AI is everywhere, but actually deciding what room or what space we leave to AI rather than the other way around, what space or room we leave to human is also a mindset that will, you know, that can lead to different directions. So for me, the the real questions is when not to use AI is is is a very important question. [00:28:05] S0: What's an example that you've actually changed in the organization where the the default was to go for AI and you raised the question, you changed it?
00:28:16 · Laurent Aufils
[00:28:16] S1: I I I think that for me, I see it on my on my job, on my day to day job. There are subjects on which I would have thought better without AI. For instance, for some strategic question, you know, like it's better to start with my own convictions in some ways and then get it challenged or, you know, have like kind of a back and forth discussion with AI and with other people actually, not only AI, because for me the reasoning through a problem is really how we build judgment. So, you know, we question assumptions, we have to weigh trade offs, we decide what matters, and AI can help, but it cannot take responsibility for what we choose. And I think that, you know, I've been writing, I'm writing an article right now around AI and responsibility, but I think it's a key questions that we need to have in our mind. And, you know, it's very important again to see that sometimes AI can be more costly, sometimes AI won't be serving the real need, you know, of our customers and then productivity is also one way to look at AI, but we have to look at how we increase revenue, how we increase the top line, how we also deliver more value and AI can help on this. But again, you know, we have taken a little bit of bias, I feel that's my personal opinion that AI equals productivity. And again, we are in companies to help the company grow, to help our employees to grow. Productivity for me is to do more with less and it's not growing. So, you know, let's also remember that, you know, not using AI can also help us have different, you know, perspectives on on a lot of things in our day to day life. And it's, you know, I think it's it's very good to have this kind of reminder from time to time.
00:30:31 · Nirit Cohen
[00:30:31] S0: So I'm I'm curious, really, one last question, but I can't seem to let that go. The entry level people. Right? You talk about the building judgment and a person with experience, their ability to know maybe to judge when to use AI or when to start with their own reasoning. But how do you build that ability for people who are coming into the organization when AI is already part of their job?
00:30:57 · Laurent Aufils, Nirit Cohen
[00:30:57] S1: I think that's... For us, it's it's one of the of the key questions on the table because we have decided that we would keep on recruiting entry level young graduates, you know, on on different jobs. Okay. Even on jobs that we know might not have, you know, a long term perspective because we know that AI will take, you know, some take over some of the, you know, like work on the legal side or on the accounting side or so on and so on. But for us, it's very important because it we need to have people growing the company, knowing the processes and also knowing, you know, distance they need to take also from what is being produced by AI. And you cannot do that when people are actually been using AI by, you know, by default in some ways. So you need to have this kind of training and growing within the company on a certain function that helps understand that, okay, you know, this might be done through AI, but this is the type of judgment that you need to apply, the type of distance that you need to apply to what is being produced and how also you are there to be accountable and responsible. And it starts with asking the right things and the right questions to AI. And this in some ways, you cannot ask the right questions if you don't have a certain level of experience, skills in the domain. And it's [00:32:39] S0: very So does that mean does that mean in some cases you can use AI, but the people will still do the job without AI so that they can build the the skills or domain, or have you figured a different way to build the skills?
00:32:51 · Laurent Aufils
[00:32:51] S1: It's one way to look at it, it's another way is also to have this hybrid, you know, ways to address some of the functions, meaning that, okay, you are doing part of the work, you know, and you are outsourcing to AI the other parts of the work, but basically all that together is your work and you are responsible for, you know, the outcomes of and delivering, you know, what is according to your job desk or your role. And it's also in some ways building experience because it's very important. I think that beyond skills, you need to build experience and treating things differently, treating, you know, like when I was talking earlier about, you know, people who are dealing with tickets, you know, when they have to deal with specific tickets that are coming out of the norms or out of the regular ways or, you know, the standard processes, that's actually when you learn a lot and when you question the way you are doing things as well, when you have to manage a crisis, it's a good example as well, even though we don't like to manage crisis, but it usually gives you, you know, a lot of learnings and a lot of experience that are not only skills, but that are truly applicable and replicable to all the parts of your work. So that's very, very important. And again, we have to be careful because if we don't hire young graduates, if we don't, you know, we don't renew the age pyramid of the company, and I think it's really a risk that we're taking, because again, you know, we need to serve the diversity of our clients and by that, we need also to have the diversity of our own employees to, you know, to deal and to, you know, to deliver value. So it's very, very important. It's very important in terms of innovation. It's very important in terms of, you know, challenge. And we see a lot of reverse mentoring that we have put in place, for instance, around AI. And it's very, very powerful.