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How Can the Labor Market Keep Up with Tech Disruption?
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00:00Hello, hello, everyone. Hi, can you hear me? Hi, thanks for joining us. My name is Neil Firth and I'm
00:07the executive editor at MIT Technology Review and we're here to talk about AI on technology and job market.
00:16So, this is a topic that we have been worrying about for literally hundreds of years. What happens when a
00:24new technology comes in and what happens to the existing workforce?
00:29Like, in the 30s, the economist Keynes was worried about what he's called technological unemployment, where the pace of tech
00:39development was going so quickly that the labour market couldn't keep up.
00:42And as it turns out, things did change, there was disruption, but ultimately, the economy kept growing and things just
00:49adapted.
00:50So, is that what we have happening now with AI? It remains to be seen, but I think we're starting
00:57to get to the first early signals of what might be around the corner.
01:02Luckily, I have a bunch of absolute experts here who can tell us about what they've been seeing in the
01:07market.
01:08So, starting over here on my left, we have Riccardo Barbaris, he's the regional president of Northern Europe and France
01:16for Manpower Group.
01:18Hi, Riccardo.
01:20And next to him, in the middle, we have Tamara Basic-Vasiev, head economist of EMEA LinkedIn.
01:27And then, right next to me here, we have Claire Lepas, who's chief technology and AI officer at Malt.
01:35Hello, everyone. Hi. Thanks for joining us.
01:39So, tell me about what are you seeing?
01:42What signals are you seeing in the market about any disruption around AI and technology?
01:48Riccardo, I'll start with you.
01:49Yeah, I think that the first element is a structural trend that is here to stay since many years already.
01:56We see clearly as Manpower Group a very big bifurcation in the labor market that was already present before AI
02:03acceleration.
02:05In our survey as Manpower Group, we have every year, almost in the last five years, around 70% of
02:11our employers saying that they don't find the talent.
02:14So, there is a skill gap already.
02:17And now, there is this big acceleration of AI that probably will create a canyon from the gap, considering the
02:24trend at the moment.
02:26What is interesting for us is that we don't think that it's so interesting to discuss about replacing the human
02:33job.
02:34I think that it is much more interesting to discuss what could be the combination of the human augmented versus
02:42the possibility that the AI would offer.
02:46Thank you. Tamara?
02:48Hi.
02:48Yes.
02:49So, for us, we look at it from two angles.
02:54So, on one hand, we have employers posting their job ads on our platform.
03:00And on the other, we have the members or people looking for jobs and then announcing themselves as ready to
03:07work or maybe starting a new job and so on.
03:10So, we look at data from both angles.
03:13And for us, the key takeaway currently is really change.
03:17Probably not surprising, right?
03:19But we like to kind of highlight what we mean.
03:22What exactly does the change mean right now?
03:26So, it means two things.
03:28On one hand, a nice statistic that we kind of use to portray the change is this one.
03:34If you look at the new starter, so somebody that just graduated and is joining the labor force today, they
03:41are expected to hold twice as many jobs throughout career compared to people just 15 years ago.
03:48So, we're not comparing to their grandparents.
03:50We're comparing just 15 years ago and it's twice as many jobs.
03:54To be specific, it's 16 now versus 8-15 years ago.
03:58So, that means for a young person joining the labor force today, they have to be very ready to change
04:05and they appear to be so.
04:07So, that's one thing.
04:09A lot of jobs, a lot of changes.
04:10We see that they're also changing industries, not just the employers and so on.
04:15On the other hand, what's changing also is the skills that they take with them.
04:20This we portray with this piece of statistic.
04:22We expect if the current trends continue by 2030, so just five years from now, for the skill set that's
04:30needed for an average job to change 70%.
04:33So, that means when you have a job ad and you have that list, you're expected to speak English, you're
04:39expected to know how to, I don't know, maybe code or for you maybe it's some CRM skill and so
04:45on.
04:4570% of that list will change in the next five years.
04:49Now, part of that change is linguistic.
04:52I'll give you an example.
04:54Today, there's almost no job ad that tells you you need to be literate in Microsoft Office.
05:00That's just taken as a given.
05:02You still need to know how to write your template PPT or how to use the Excel and so on,
05:08but nobody spells it out.
05:10So, part is linguistic, but part is not linguistic, part is real.
05:15It's just different skill sets and people on our platform seem to also very well grasp the fact, seem to
05:22add the new skills permanently, speeds up every year.
05:26So, yes, prepare for change, prepare to upskill, but also prepare to be more agile, to move more quickly from
05:33here on.
05:35Thank you. Claire?
05:36We are seeing a lot of change.
05:40Good change or bad change?
05:42So, every year we publish our Malt Tech Trends.
05:45So, we look at the data on the marketplace and if you're not familiar with Malt, Malt is the leading
05:50freelancing marketplace in Europe.
05:53So, we have on one hand 800,000 freelancers, maybe 1 million by the end of the year at the
05:59pace it's going.
06:00And on the other hand, 90,000 companies, almost 100,000.
06:05And so, we have millions of searches from companies looking for talent that we analyze every year.
06:10And so, we recently published our latest Tech Trends.
06:14And what we're seeing is actually not what the American hyperscalers are telling us.
06:21There's still a lot of demand for talent.
06:23So, we're not, like you said, you know, from the data from LinkedIn, the data from Malt confirmed that.
06:28There's a lot of demand for talent, but there is a shift in what companies are looking for and what
06:34they're hiring for.
06:35The first thing is we're seeing really an explosion around AI.
06:39We saw demand in the last 12 months triple around AI.
06:42So, we really moved past, you know, the exploration.
06:47Now, they're going full steam.
06:48And it feels like they're just getting started.
06:50You know, just the premise, the starting project.
06:52They're really starting to bring in AI expertise in the company.
06:56And so, it's also changing all the, you know, the leading technologies being used,
07:02the type of tech competencies that are being looked for.
07:04So, there's a shift definitely going on there.
07:06On the tech side, for tech profiles, we see companies are looking more and more into full stack.
07:12Very broad type of profiles because sometimes they actually don't know what specific expertise they'll need for the project because
07:19it's so new for them.
07:20So, they need someone who will be able to integrate an LLM via an API, but also build the backend
07:26and maybe the frontend.
07:28And maybe potentially some low code, no code in there.
07:31We actually saw demand for low code, no code expertise rise in 2024 by 40%.
07:38We also saw another trend, which nobody is talking about, which we saw actually the segment in terms of expertise.
07:47The demand that is growing the most is around the very expert profiles.
07:51If you look at cloud engineers, cybersecurity, it's people that have more than 15 years of experience that are the
07:57most in demand.
08:00And it's also the very data-executive type of profile where we see three-digit growth.
08:05Because companies need this guidance to help them with a strategy and need that expertise beyond the hype that they
08:11hear in the news.
08:12All right, thank you.
08:13You can share a lot more after in the conversation.
08:15Yeah, absolutely.
08:16Yeah, sorry.
08:16Building upon this, I think that for sure, as you said, it's about big change also in type of job
08:22and characteristic of the skills.
08:24But also in terms of unpredictability of those changes.
08:29Who would have said three years ago that today coding is not anymore a top thing to look in the
08:35market?
08:36Everybody was creating programs in the schools.
08:38Every parent recommended to the children, you have to study coding because this will be the future.
08:44And now, I think that we can say that this is one of the things that unpredictably came.
08:51I tend to disagree with you because if you allow me, yeah.
08:55Because I think there's a trend that is not new, which is there's been more and more abstraction in how
09:01we actually build programs, right?
09:04I remember when I was back in school, I was studying C++, which is already a little bit of an
09:08abstraction on top of C.
09:10And it was not fun.
09:11This is how actually I didn't go into engineering at first.
09:13It was really, really tough actually to build programs on C++.
09:17I don't know if people are old enough in the room to remember that.
09:20Honestly, now when I could, you know, Java or Python, it's really, really fun.
09:25And I think now we're getting to a new disruption in how you actually build programs, develop as an engineer,
09:33develop products,
09:34which is a trend that's been long going, which is, you know, we extract further from the core machine.
09:40And that makes it the pace of democratization.
09:45Maybe it's what is accelerating and hard to grasp, but the trend was already there in a way.
09:50Yeah, probably what we are saying is very similar in terms of is the movement from job to very vertical
09:57expertise that would be also probably fueled by AI.
10:01AI will ask, will push ourselves to rethink also the organization.
10:07This is something very visible in those days in Vivatec.
10:09As Manpower Group, we have visited a lot of partners and clients and startups.
10:14And every discussion starts from which is the technology tool that you have that will be disruptive and finishes with,
10:21but do we have the skills?
10:24Are you designing your organization differently to make sure everybody's struggling with the first level of AI that is adoption
10:32to generate productivity gains?
10:34Because this is what the companies want for.
10:37So the majority of the company already are struggling with this.
10:39The future, as you said, would be really how to generate value from this technology.
10:45In terms of, you talk about companies are struggling to sort of integrate it.
10:49Why do you think that is?
10:50What's the, is it because they haven't entirely decided what they need it for?
10:54They just feel like we've got to have AI in our company, otherwise we'll be left behind.
10:59Or what's the, what's driving that?
11:01Yeah.
11:02I think a combination of both.
11:04We start the discussion in a very strong technology ambient.
11:08And then we discover that there is a lot of change management needed.
11:11So there are things that are happening in this direction.
11:14One example, Moderna one month ago decided to unify the HR function with the technology function.
11:21Because they understood that if they want to invest in technology, it's not just about the money for the tool.
11:26It's about the capabilities of the people and redesigning the organization.
11:32Another example coming to the IT in our survey for the CIO this year.
11:38One of the most relevant topics that the CIO are saying, next time that I will launch a new AI
11:44tool, I will be partnered with the CEO.
11:47Because they understand the need of making sure that these tools are scalable and can generate a value.
11:54This would be probably a potential part of the interpretation.
11:58All right.
11:59Thank you.
12:00I want to bring you back to something both you two mentioned about starting out in work.
12:08Like a small anecdote, I've got a friend who started a company.
12:12It's just two people in the company.
12:14And he was telling me the other day how to look for new business leads, to write proposals, to put
12:21together decks for presentations.
12:23He's just using Gemini for everything.
12:25Whereas just a few years ago, he would have probably hired a new graduate and trained them up to do
12:31that.
12:32And what he's getting for him, for his purposes, is good enough that he doesn't need to hire that person.
12:38And I imagine that conversation is happening across all businesses.
12:41Do we need to hire someone with a salary and benefits and all that kind of thing when we can
12:47get something that's kind of usable and pretty good just with AI?
12:51And what does that mean for graduates coming out of university looking for those sort of entry level jobs to
12:57start their careers on?
12:58Yeah, so maybe I can.
13:00Sure.
13:02Yes, there is statistics saying that unemployment rate among the new graduates has edged up a little bit.
13:10It holds true for UK and for US especially, somewhat less for the European markets.
13:17But we think that's maybe a consequence of the fact that young people now go to tertiary education more than
13:25ever in the past.
13:2665% of population in UK now has a tertiary diploma at the new entrant level.
13:33So at the generation who's turning maybe 22 or 21.
13:37So we think that's really what's going on now.
13:39We don't think it's AI because it didn't start after AI appeared.
13:43It started after COVID.
13:45That said, I fully believe and understand somebody saying, why do I need a junior?
13:51I'm going to just use, like you say, Gemini or ChatGPT or GAI or so forth.
13:58Well, I think this is true.
14:01It will be tougher for the new starters to get up to speed.
14:06But I think if anybody was ever ready for it, it's them.
14:10They're just much quicker to learn.
14:12We see the behavior on our platform.
14:14So the stuff that the 21 year old today does on the platform compared to what they did 10 years
14:20ago, it's two separate worlds.
14:22So they come already with several apprenticeships with a page long of experiences related to work or outside with two
14:31pages long list of skills.
14:33They take the courses.
14:35A lot of them are available for free.
14:37So they come to the workforce already well prepared.
14:40Back when I was starting, it was almost a given that at least half a year or maybe a year
14:46you will not be useful in your job.
14:48You were allowed the grace period to just come to the job and maybe learn.
14:53Maybe you help a little bit, but you're more of a nuisance.
14:56The good old days.
14:56Yes, exactly.
14:57That's gone.
14:58But the young people, I think, are prepared.
15:01We maybe need to be kind to them a little bit given, you know, how hard we are making it
15:06for them.
15:07But they are ready to take the challenge.
15:10I would say yes.
15:12Yeah.
15:13I fully agree.
15:14Maybe one thing I'll warn about is that a lot of the studies we've seen recently, they conflate some of
15:20the macroeconomic impact.
15:22The inflation we've had actually in the years post-COVID.
15:25Some of the uncertainty currently around the tariffs.
15:28And that has massive macroeconomic impact.
15:31There is uncertainty for companies and they will impact, you know, decision to invest, recruitment plan and so on.
15:38And that's what's driving as a first driver currently, the trend around employment.
15:44It doesn't mean AI will not impact this job and it's not starting in the situations where people are the
15:50most tech savvy and already high adopters of AI.
15:53But the pace of adoption of this technology in companies is actually much slower than what some of these studies
16:00imply and infer.
16:02The thing I'll say, and this is actually what you were saying, Tamara, is I'm actually, I started to hire
16:06back new grads.
16:08Why?
16:09Because they helped me actually accelerate the change in my organization.
16:14Yes, I'll be looking for actually a very high potential new grads, very geeky.
16:20They've explored the technology and they're going to come challenge the senior, you know, engineers in the organization and accelerate
16:27the base of change.
16:27So, and we've seen that, you know, with internet back in the day, same story, you know, how did the
16:32marketing teams department transition from the good old school marketing to digital marketing?
16:38The same phenomenon, but it's happening much faster, although not as fast as what we're hearing in the news.
16:43And also for us as Manpower Group, we interview 10 million people in 70 countries, 5 million of them are
16:51here in Europe.
16:53So we see clearly this trend that we've just confirmed of the difficulties for the newcomer to enter because there
17:00is a level of AI.
17:01But there is also the other side of the coin because it's like when the plastic, AI can be the
17:08new plastic.
17:09So we celebrate or we are scared and then after some years, we discover the negative effect.
17:14In reality, it could be a negative effect, potentially, as you describe.
17:17On the other hand, AI can also be helpful because some of those people, they don't know that they can
17:23work in other sectors.
17:25So AI can understand which are the skills that you have for the future, the attitude that you have for
17:30the future.
17:30So the human aspect that are not detected in a CV that can create more opportunity of jobs in adjacent
17:39verticals that the traditional interviews of 10 years ago were not able to capture.
17:4610 years ago, 5 years ago, in some cases for many places here today, the conversation is about the past
17:53experiences as a proxy or where you can work.
17:57And if you don't have past experiences, it will be a problem.
18:01In this case, AI can be a positive effect because it can detect and can help the recruiters to understand
18:09and to help how to develop talent in different segments.
18:13So it always depends on the humans.
18:14If we want to take it as a threat or if you want to look at the opportunity that this
18:19tool will offer to the possibility of knowing ourselves better, understanding where we can go.
18:25I mean, I was going to mention two, not really data points, but sort of two reports recently.
18:31And I wanted to see how they chimed with what you're actually seeing on the ground.
18:35There was a WF reports last year, which said that 40% of companies that they surveyed were going to
18:43automate part of their workforce and lose jobs as a result.
18:47And then it was last month, Anthropics founder, Dario Amadei, described a white collar bloodbath, he said, particularly for entry
18:56level jobs.
18:57And that's, you know, the figure was like 20, 20 or 30% of those jobs will be gone in
19:03just, yeah, 20% of those jobs be gone in the next one or two years because of AI that
19:09he is developing.
19:12Yeah. And just wondering if that sort of chimed with you, those sort of more doom laden reports seem right
19:17or from what you're saying, it seems like that's not what you're really seeing.
19:21It's not what we're seeing. That said, we do see the premise of every, and that's what I do believe
19:30in how we're approaching things even internally at MALT, which is every job is going to look different.
19:36Right. Your workflow of tomorrow, you know, as a product developer, as a marketer, as a sales, your day to
19:45day tasks are going to look different.
19:47And we're starting to see that also in how freelancers are adapting to AI.
19:53We actually saw in the trends of the last 12 months that freelancers are more AI ready than companies.
19:58The upskilling has been much faster on the talent side than the adoption on the company side.
20:04And not just on the tech jobs, but really every other roles, you know, on the legal consulting side, marketing,
20:12communication, product design, like all the other functions.
20:16And yes, you're going to favor actually profiles who know how to work with AI, you are AI augmented.
20:23And actually at MALT, we built a platform so that any employee can build AI assistants.
20:28They can use low code, no code to embed that in their working tool and get to the stage eventually
20:32of building agents.
20:33And for me, that's the way where you get actually the team, the experts, the main experts to reinvent their
20:41workflow eventually.
20:42You know, so some teams are a lot more advanced. Our customer care team actually has been really the one
20:46reimagining their workflows with AI agents.
20:50And so it's true what they were doing, you know, the way they work today is very different from a
20:56year ago.
20:56And I believe next year, it's also going to be very different.
21:00So this job, the job description, yes, of 2020 is very different than the one from 2025 and beyond.
21:12That said, this is the same people in my company, right? And they are going through that process.
21:16I think the question is who is going to be jumping on the tool, get a culture, learn the tool,
21:21test the tool, build a assistant,
21:23and how much a company is actually investing in their current employees to make the move.
21:27And we see that this is actually massive investment to upskill.
21:31There's not like one learning and development team was not having AI as a top priority.
21:38Some people may not follow. That's true.
21:41And I think the question is actually for these people, like every technological transformation.
21:47But we see that happening within the companies.
21:51The change is here. I think that when we talk about jobs, we do jobs equal people.
21:56But people are evolving, you know, within the company to another job.
22:00And I think what's exciting is to see them reinvent the work of tomorrow.
22:04Thank you. Oh, sorry. Yeah.
22:05Yeah, I think that is interesting too. All those predictions are very long tail.
22:14So to make sure that we are capturing really what is happening is very difficult.
22:18It's early stage. But what we see as Manpower very clearly is that today,
22:24100% of the company are using AI for having faster and cheaper tasks done, right?
22:31But this is not the future. The future will be much more how to move to discover.
22:37And so how I can help the human to do things creating inside that we don't see.
22:42Attraction rate, the prediction for HR or type of potential clients,
22:48segments that we are not attacking with our sales strategy and things like that.
22:52To arrive to the next level, that is how I deliver value, doing co-creation.
22:59And so for me, the question about are destroying jobs the various AI is the wrong question.
23:09We are not talking anymore about jobs. We are talking about tasks and competencies.
23:14This is the name of the game. And if this is the name of the game,
23:18to say that some job will be destroyed, of course they will.
23:22And majority of those tasks will be done by AI. Of course they will.
23:27But still, this type of tasks have to be driven by humans,
23:31because the humans are the only ones that can innovate, can generate something more,
23:37and can create the next level of AI.
23:40So I don't think that to talk about the destruction of job is the right question.
23:45Let's work together to create competencies, to be ready for the task ecosystem.
23:52Sorry.
23:52No, no, obviously. Thank you. I absolutely agree. Two things.
23:57First, we absolutely do not see any sign of falling in jobs demands.
24:04So number of job openings on LinkedIn platform now are higher than ever.
24:08So it's not happening yet. That said, do we think it will happen in five years' time?
24:14Honestly, I personally do not believe. And I think it's a very good approach to be concentrating on change.
24:21What can you do to adapt rather than thinking,
24:24Oh my God, what happens if the AI can do everything I can do?
24:28The way we see it, so we've done some quite sizable research looking at,
24:33we took 600 occupations, we listed 30 normal everyday tasks for each of the occupation,
24:40and then we analyzed, okay, if you're a veterinarian, what do you do in a day?
24:44Can any of that be done by AI?
24:46I concluded, no, not really. Veterinarian gets to keep his job as it is.
24:50But then we looked at librarian and we said, what does he do or she do during the day?
24:55Can that be done by AI? And we concluded, well, actually most of it can.
24:59Does that mean librarian will lose his job? We think no.
25:03We think if you concentrate on skills, what skills does the librarian have?
25:08And are those skills usable at a similar job?
25:13Then you realize, yes, some sectors will probably lose some of the headcount.
25:18And we know that that's already happening, not because of AI, but just longer term trend.
25:23For example, in media, there has been shrinking.
25:27That burden was taken over by healthcare.
25:29We all know aging population and so on. Healthcare needs more people.
25:33Then you think, okay, what does the librarian know and can do that you can maybe use in a healthcare?
25:39And we think the future is going in that direction.
25:42Like you mentioned, we call it skills based hiring.
25:45So look at the person not based on CV, what they used to do, what industry they spend their careers
25:51on,
25:51because in the future that will not exist.
25:53Look at the person as this is what the person can do.
25:56Where can we fruitfully use that skill set?
25:59And I think that individuals too should concentrate on what do I need to learn to add on top of
26:05everything I can do
26:06to be the person that's successful in the job market of tomorrow.
26:10If we think in terms of, okay, so let us know what is it?
26:13What do we need to know?
26:15On that front, we do this.
26:17So we look at all the job ads every year and we have some ridiculous number.
26:22I don't even remember.
26:23It's like tens of millions and whatnot globally.
26:26We do the language analysis on the skills that appear on the job ads.
26:32The trend is clearly moving in the direction of what we call human-centric skills.
26:38Absolutely number one new word is adaptability.
26:42So people actually specify it as a requirement to be adaptable, ready to change.
26:49But it's also communication, negotiation.
26:52There's a lot of data analysis, truth be told, that's still pretty up there.
26:56But there's a lot of just talking, communicating to other people.
27:01And the number one job opening in Europe right now across several major markets is project manager.
27:06So that to me means a future where, like you say, obviously AI will replace us in some of the
27:13analysis,
27:14some of the data gathering, data analysis, data preparation, all sorts of language manipulation.
27:22But what remains for us is to take that output and then present it to another person
27:27and reach an agreement with that person of what's the final output.
27:31Not just because AI obviously makes a lot of mistakes and it cannot be unsupervised,
27:36but just because the labor market always worked that way.
27:41If you look at historically, we were all in agriculture and then it took about 200 years in Japan
27:46to move from 98% of people work in agriculture to just 2% do.
27:52Then you move to industry and again, the same thing happened.
27:55A lot of people worked in industry or majority of them in UK.
27:58And then it took shorter, maybe shorter than 100 years to move from industry is the boss to industry is
28:04not really that important.
28:06Now, unfortunately, it will probably be decades, if that.
28:09So it will just like compress and it will be hard to kind of live with that dynamism, with that
28:15speed of change.
28:15But it's highly likely it will go in the same direction.
28:19We will just move from manufacturing, move from, you know, mowing the lawns and whatnot, machine will take over.
28:25We will have to think of something that's specifically human.
28:29We know now healthcare will definitely be one of the winners.
28:31We can pick a few more winners.
28:33But for me, if you want to kind of prepare yourself, polish your skills that are human centric.
28:40So your communication needs to be excellent in the job market of the future, and then learn to use the
28:46AI as a tool.
28:47With those two goals, I think there's less reason to worry and more reason to just be prepared and be
28:55optimistic.
28:56Oh, thank you.
28:57That sounds very positive.
28:59Yeah, the only problem is that we don't have 200 years if we want to compete in global stages in
29:03Europe.
29:04So we need to speed up this process.
29:06We will need to be quick.
29:06In terms of these sort of new human centric roles, what kind of new jobs are you seeing or do
29:12you expect to see?
29:13So you mentioned project manager.
29:15I mean, obviously that's a job that's been around since forever.
29:18What other kind of new roles are any of you seeing or can you imagine that are going to exist
29:23that don't really exist right now?
29:25Yeah, so new is everything around data.
29:27We looked at back in 2000, people wouldn't understand if you said like data scientist, what?
29:34So everything around data, data centers, data manipulation.
29:38Full stack engineer, like you said, that's on our platform also.
29:42A new thing that's absolutely big.
29:44You maybe have a few more to add?
29:46Yeah, exactly.
29:47I can tell you what we're seeing as maybe a predictor of the future.
29:51AI engineer is skyrocketing.
29:54More than 300% growth.
29:57We also see a lot of actually increase in demand for cybersecurity experts.
30:03And more importantly, it's actually people who are broader than one expertise.
30:08So for example, if you are a cybersecurity expert with a leg in AI, that's a massive boost in demand.
30:15So full stack profiles.
30:18We also see actually new roles, new type of demand, which are this profile to actually help the company accelerate
30:25their transition, their adoption of AI.
30:27So roles that are like AI data, data product manager, AI project manager, AI ops, this low code, no code
30:43flavor.
30:44You know, these champions internally who are going to drive this group, you know, of AI champions across the company,
30:52animate them, give them the tools.
30:54This is really where we see a lot of demands today.
30:57And these new roles where the job titles are not very dry, you know, like companies are experimenting because they
31:04are actually hiring people who don't have this title today.
31:07What we're seeing, for example, is the rise of AI officers.
31:11And it's interesting to see who are these people jumping into these jobs.
31:15Actually, sometimes they're coming from design and products.
31:17I mean, I'd be tech people per se, but they've highly experimented with the new tools.
31:22And so they're confident in driving, you know, the next level of change in the companies.
31:28Yeah, if I can add it.
31:30Sorry, just one thing and I'm handing it over to you.
31:34It almost sounded a little bit worrying.
31:37It's not just the software engineers.
31:39So it's almost science.
31:40Oh, we just need the AI people and the data people, the rest of you step aside.
31:45Not true at all.
31:46So one good example is the talent acquisition manager.
31:50And for example, workplace experience manager.
31:54So there are a lot of people who are remember like maybe 20 years ago or we want to say
32:00more.
32:01You know, HR was just about figuring out when you get paid, when you take your leave.
32:06And that was about it.
32:07Sign the contract when you're on boarded and that's it.
32:10Nowadays, you have a full team of people who worry about stuff.
32:13How well do you feel at your workplace?
32:15How do you feel about your work?
32:17Do you have some personal worries?
32:19How can they help with that?
32:21How can they develop your talent, upskill you and so on?
32:23There's a full army.
32:25So the talent acquisition industry, as they now call it, it grew manifold.
32:31And similar is happening across, again, human centric.
32:35So experience management is now a thing.
32:38That's another thing that somebody in 2000 wouldn't recognize.
32:41So I think there's no kind of room for worrying in the direction.
32:46It's all data and AI driven.
32:49No, that will just get much more productive.
32:52And then we'll be able to expand what we're doing already.
32:55Add on a lot of layers on top of that.
32:58That just makes us feel better at the workplace.
33:01So it looks to me, if you can concentrate in that direction, that could be a fruitful career too.
33:06Because obviously we cannot all be full stack developers.
33:09That will not work.
33:12Sorry.
33:12No, no, absolutely.
33:13A perfect fit building upon what you just said.
33:16Because if we keep the frame that we have been discussed before about,
33:21it's not anymore about job and job title, but it's more about task and competencies.
33:26We see clearly that AI will push the need, especially for Europe, to have much more higher educated competencies.
33:35To have much more scientific type of competencies.
33:41Much more cross functional competencies.
33:46To be able to run all this complexity that you just described, Tamara.
33:51And this is the new framework.
33:52So I wouldn't, I don't know if I have to still talk about jobs that of the future, but which
33:58are the tasks that we need.
34:00For if you think about the dark factory phenomenon in China.
34:04So we are competing with a model in which there are, are called the dark factory because there is no
34:11light, because there is not too many humans.
34:14So we need to create a labor market, thanks to AI, that push up our education.
34:20And based on the competencies and higher education on processes and transversal view, can be really marketable.
34:28More than just a job title or two.
34:31Maybe I'll add that, you know, I get to, I get to meet a lot of C level in the
34:38HR functions, VPHR, different like big companies, and they don't quite know what the future holds.
34:44And that's, but that's a question they're all asking themselves.
34:47And so at Malt, we built some, you know, leveraging large language models.
34:52Large language models are actually very good to do this mapping and think in terms of matching of talents to
34:59roles based on competencies.
35:00They do that translation.
35:02And so they're always interested in saying, hey, can I deploy this technology in my organization to actually assess the
35:09competencies of people and think, you know, better in terms of internal mobility programs.
35:14Because now you have all the biases that you don't see someone from HR jumping to a product roles or
35:20things like that, because it doesn't quite happen.
35:23And so here the technology can actually help this organization move past their taxonomies, you know, which they're never happy
35:30about.
35:32And help this organization actually make that move that you describe to competency based internal mobility or hiring.
35:41But the reality is also, they actually don't know what they will need.
35:44And so they are looking for adaptability, first and foremost, as you, that's 100% what you were describing, Tamara.
35:51Thank you.
35:52Thank you all.
35:52Just to take us in a different direction, just before we get to the end.
35:56What role do you think policy has in all this?
36:00Like whose responsibility is it really to make sure we're kind of filling the gaps that are needed to be
36:05filled?
36:06Or is it just sort of thing that the marketplace is going to work out for itself over the next
36:10few years?
36:11Should there be a policy or a governmental sort of step in to help adjust the workforce, especially if we're
36:17talking about things changing really quickly versus, you know, 100 years as it was in the past?
36:24I know.
36:25Yeah, I think it's a very, very important question for our future.
36:28I think for me, a very strong point of reference is the Draghi document for Europe.
36:34If we start from there, first thing, it doesn't speak about the jobs.
36:39It speaks about the competencies, first.
36:42Second is saying that, thanks to the AI, we can create European skill intelligence centers to predict the future gaps
36:52and to plan strategically education programs in Europe for the skills.
36:57This could be an hypothesis. Another one is, and Europe in this area is really very weak, to move the
37:04investment that we are using today in many countries in Europe for passive policies, welfare, which are important.
37:11I'm not saying to cut them, but to rebalance those passive policies to help people when they lose a job
37:17with active policies to help people to find a new job.
37:22This is another area in which we don't have to have more money from Europe, just using more cleverly the
37:27money that are already spent in different countries.
37:30The third element is to involve the business community. We have a lot to contribute. For instance, to create the
37:38standard of certification of competencies.
37:41Because if I am a worker today, as you said at the beginning, with many jobs along my career, how
37:47I can certificate all the experiences that I am doing and to grow on them.
37:52So how business community can contribute with the government to define standards that can certify the competencies of a worker
38:02that has been in a company for one or two years or five years.
38:06This is a new frontier because we have delegated for ages to the university and to the public schools this
38:13responsibility, but in an old type of labour market.
38:17The future labour market will be, the name of the game will be transitions, right?
38:22So how to create a system around the transition, this is what the Draghi document is trying to do.
38:29And those are three, four things that, it's not by Ricardo, I'm not so...
38:33But just reading the document and try to be together and organizing them.
38:40Yes, absolutely agree. I would just maybe say, for once, it's a good thing that people seem to be moving
38:47faster than the corporations and especially faster than the government.
38:50And it's exactly the advantage of AI for allowing you to, at your home, sit at your screen, get the
38:58skill you want, learn the knowledge you need.
39:01You do no longer need to go to the library or the university, you can do it on your own
39:06and we know that people are.
39:07So I'm optimistic in that sense that maybe even if our European governments are a bit behind the curve on,
39:15you know, upskilling in the school, upskilling at university, upskilling the older labour force, people are making moves on their
39:22own.
39:23So I'm optimistic.
39:25Yeah, I'll give you a short answer, which I think remains the traditional one when it comes to tech disruption.
39:32One, the question of what social safety nets for the people who are not necessarily going to jump on that
39:37transition and we know it's always a distribution.
39:40There are the early adopters. I think all of us are part of it. Everybody at VIA Tech is. That's
39:44probably why you're here as well.
39:45There are the followers and they are taking the train and it's happening. And there are the people who are
39:51going to be a little bit behind.
39:52I think what is the shape today of distribution? We don't know. But we know there's a question of the
39:58social safety net. The second piece is education.
40:02I think this is how you actually get this distribution to look better and for people to be more and
40:08more comfortable and create more value with the technology.
40:10Because technology is ultimately what we do out of it. And so how do we use AI to build the
40:15right things, bring value to society?
40:17I think that's also via education that we probably get there much faster.
40:21Great. Thank you. OK, one final question. I'm going to ask all of you for one line to finish off
40:26with.
40:27If there are people in the audience who are watching us right now who are worried about parts of their
40:33job at least being automated away,
40:35either right now or in the near future, what advice would you give as a takeaway?
40:41Reinvent your job. Get hands-on, reinvent it.
40:47I think to believe that we have people first and digital always. This will be the future. Technology won't drive
40:54anything.
40:55We'll apply what we drive them to do. And so human will be still in the driver's seat of the
41:02future of the labor market.
41:04So take ownership, of course. As we said, train yourself. Don't wait for something that comes from outside. And taking
41:12ownership of your own self-skills.
41:16There is no AI that will beat us.
41:19Thank you. Tamara, final word.
41:21Yes, absolutely. Absolutely agree. I would add on that, learn how to use GAI.
41:26Whether it's ChatGPT, Gemini. Learn how to use it. And by that, I don't need the trivial stuff. Log on
41:33there and ask some questions.
41:35Really learn how to. There are a lot of advisory websites that can help you do it. Learn the tricks.
41:42You will need it.
41:43You will fall behind if you don't know how to use it. So use GAI professionally. You need to.
41:49And of course, I'd say subscribe to MIT Technology Review as well. Obviously, obviously.
41:55Take it for granted. Of course, without saying.
41:56Confirmation that was a very serious panel. Nobody answered, follow your passion. That I think is already an achievement.
42:02Yes, we missed that.
42:04Maybe if it comes alongside with the skills, it would be good. But maybe we were very clear in the
42:09messages.
42:09For once, it makes sense. It used to be an empty phrase. Nowadays, you actually, I think, can afford to
42:16follow your passion.
42:17If you want to be a historian, go ahead and be a historian. There'll be room for you as long
42:22as you learn how to use GAI.
42:24Brilliant. Thank you all. Ending on a very optimistic note to send us off into the afternoon.
42:29So thank you all for joining me. And thank you all for coming as well. Brilliant. Thank you.
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