Melanie Rosenwasser: AI is changing everyone’s expectations around talent in general, and that includes early career talent, but it’s not necessarily by eliminating those roles.

Pete Brown: AI can get people to the interesting bit faster, but they still have to do the thinking and organisations have to create an environment where they're able to develop those skills.

Melanie Rosenwasser: Culture actually matters more than technology. So a lot of companies focus on tool adoption, but the biggest challenge is actually creating a culture where your employees can experiment

Lizzie: In many careers, progression is obvious. You start with an entry level job, then work your way up the ladder to senior positions.  

Femi: But, as AI automates simple tasks, the types of skills needed for these jobs are changing, with human skills like creativity and judgement in high demand.

Lizzie: So, are workers ready for the new types of roles AI is creating? 

Lizzie: I’m Lizzie O’Leary, a podcaster and journalist.

Femi: And I’m Femi Oke, a broadcaster and journalist. And this is Take on Tomorrow, the podcast from PwC.  

Lizzie: Today… how is AI reinventing the career ladder?

Lizzie: Shortly, we’ll hear from Melanie Rosenwasser, Chief People Officer at Dropbox, a collaboration platform for AI-powered work, on how AI is redefining careers inside her own company.

Femi: But before we get there, to help us understand what’s happening across the wider workforce… we’re delighted to be joined by Pete Brown, PwC’s Global Workforce Leader. Pete, welcome back!

Pete: Thank you Femi. Lovely to see you. 

Femi: So Pete, there's a lot of worry that AI is going to eliminate jobs, especially at the entry level. When you look at the data around the world, what is actually happening?

Pete: I think some of the data here is actually really quite encouraging. People that are using AI regularly aren't telling us that they feel less relevant. It's actually quite the opposite. They're saying they feel more empowered and actually they have more confidence around their own job security. Now that doesn't mean that jobs won't disappear or change. They absolutely will, and we can't duck that. But what we are seeing is, much more immediately, is that AI is changing the content of people's jobs. So take something that perhaps used to take half a day, pulling some research, creating a first cut of a document. If AI can get me to that in 20 minutes, the job hasn't changed. But what I do with my time and what's expected of me has changed.

Lizzie: So if AI is taking over some of these tasks, these routines that you're describing that are sort of traditionally handled by people early in their careers, what happens to those first few rungs of the career ladder? How do you learn how to be an employee?

Pete: I think there's a very real and genuine issue here. And I, I see this firsthand actually at home. My 21-year-old daughter is going through exactly that, trying to work out how does she get onto the first rung of the career as she leaves university. and I think if I reflect back on how many of us learnt, we sat in lots of meetings. We saw more experienced colleagues and a lot of that actually was pretty mundane. And I wouldn't preserve that mundane work simply because we had to do it. We were learning whilst we were doing that. So if AI takes away some of the work people used to learn through, what do we replace that experience with? Can I get them in front of the customer faster, into the discussion earlier? I'm able to ask them what do they think? Do they agree with what's been produced by AI? What's missing and what would they recommend? Let them see how somebody with experience approaches the same problem. And I think that creates a fantastic learning opportunity for colleagues as they join in the lower rungs of the ladder. 

Lizzie: It sounds like roles are being redesigned at rapid speed.

Femi: To understand what that looks like day to day, I spoke to someone who’s thinking about this in real time Lizzie.

Melanie Rosenwasser is the Chief People Officer at Dropbox. And we began by looking at how AI is actually impacting the job market – both at the tech company and beyond.  Her answer... might surprise you:

Melanie: So there are a lot of headlines about AI replacing jobs. I recently read something like there's been, you know, 175,000 AI related layoffs in the last few years. But if you actually look at the labour market data, the percentage of actual jobs fully replaced by AI is like closer to zero. And it is true that AI is replacing tasks today, right? But not necessarily entire jobs. And as AI takes on more of the tasks within a role, jobs, teams, and organisational structures will change. And so because of this, I think about adaptability as the new job security. So as AI is automating routine work, I think the employees that thrive will continuously evolve and use AI to amplify things like judgement and creativity. 

Femi: here's definitely anxiety from young people going into the workforce about what will happen to their early career jobs. What would you say to anxious young people trying to get their first step on the job ladder?

Melanie: You know, AI is changing everyone's expectations around talent in general, and that includes early career talent, but it's not necessarily by eliminating those roles. So many of our interns and new graduates arrive already using AI to code and research and prototype. And this actually significantly accelerates their ramp time. So we're expanding our internship and new grad programme by about 25%, because we see this cohort as a source of innovation and a pipeline for leadership. And actually our data reinforces this investment. So our emerging talent hires actually outperform external hires by their second year at Dropbox. 65% are promoted by their second year, 87% by their third. And they also demonstrate higher retention rates and higher engagement. And just in terms of engineering a lot of our interns and new grads are in engineering. They actually commit two times more code and do so two times faster than comparable external hires. 

Femi: That's really impressive. Why do you think that anxiety still exists when in reality young people, graduates, coming into employment are more qualified to handle AI than perhaps older people who are already in the companies?

Melanie: We're all learning and we're all kind of making assumptions before we actually see it play out in real life. And so the assumption is sort of, oh, lower level work will all be automated by AI and so therefore you don't need entry level, therefore you don't need roles that perform more administrative tasks. But I think the real value is how do we then apply their talent differently from entry level tasks or admin type functions. And the capability is there. So, education that’s doing its job by preparing students in the AI age, and then as employers, it's our job to then embrace that talent and basically enable it to thrive.  

Femi: I'm thinking about a career ladder and how people used to approach their careers and how they would plot it out. I'm gonna do this and then I'm gonna have this milestone and I'm gonna do this milestone. Has that career ladder changed now that AI is very much part of the picture?

Melanie: I think really what's happening is that AI is blurring the boundaries between job families. So this is making breadth increasingly as valuable or potentially even more valuable than depth, right, or specialty. And we're kind of starting to see roles converge as a result. One of the trends in the tech industry is this notion of a full stack builder. This is effectively an AI native, like, product creator that combines product management, design, engineering, customer insight to take ideas from concept to customer impact just on their own. So I think the future will be less about functional ladders and more about expanding capability, where expertise will still matter, but you'll have to have some working knowledge across disciplines. But I think something that's really important is this notion of also testing for these innately human durable skills alongside AI skills.  So it's things like awareness and judgement and adaptability and connection. 

Femi: Can you share some of the lessons that you've learned at Dropbox from experimenting with AI, experimenting with the workforce. What are the lessons that other companies could learn from the experimentation that you've been doing?

Melanie: I would say probably two things. So first, there's a lot of hype. Whether it's headlines about AI replacing jobs or this sort of fallacy that AI immediately creates measurable ROI. We found that it's actually much more useful to just start from first principles. So what are the problems we're solving? What work are we trying to improve, and how do we actually redesign the work, not just layer AI on top of what's existing. So that's probably the first lesson. And the second is that culture actually matters more than technology. So a lot of companies focus on tool adoption, but the biggest challenge is actually creating a culture where your employees can experiment, they can share what works, they can redesign their own workflows, right? And there's this continuous learning loop that we all participate in together, and that's ultimately what determines whether AI is becoming just another productivity tool or whether it's truly transformational. 

Femi: As you're experimenting with AI, how do you bring all the workforce along with that experimentation and that progress?

Melanie: I'll give you just a couple of examples of what we've done. We make it easier to apply AI in everyday work. So we have what we call an AI use case library. So this includes all of the workflows we've automated and all of the tools we've used to do it. And this gives employees practical examples that they can build on, rather than having every team start from scratch. We have this culture of experimentation. So we ran a competition called AI Applied, where folks would submit their workflows that they've automated with an AI tool. We had over 120 submissions and the winning project was basically like a homegrown version of Mythos, which is like a security software, which handled hundreds of vulnerabilities in just a couple of months at a fraction of the cost. We also built something called a Career Compass. So this is an application, an AI app, that puts employees in the driver's seat of designing their own jobs. So it helps them identify what to automate, which AI tool to use, what new responsibilities to take on, and which skills they need to develop. It even generates like a personalised career growth plan and mentor recommendations, and even an updated job description. So instead of waiting for HR or your manager to redesign your role, employees have the agency to proactively shape it on their own.

Femi: So if we are looking at AI being more than just creating more efficiency, more productivity, that there's new services, new products, more money is coming into the company, that's AI. But what about the people part of that, the workforce?

Melanie: Yes 

Femi: Do they have a role to play as well? Or is the AI doing the heavy lifting in this instance?

Melanie: I think the employees, often are the architects of what AI is doing. But I think the other thing to really think about is the impact on wellbeing. There are things like cognitive atrophy where the fear is that we'll stop thinking for ourselves. But the opposite of that spectrum is brain fry, right? Where humans never stop thinking. So we've added AI specific wellbeing questions to our employee engagement survey to understand its impact on mental load and energy. Results showed that while employees feel that AI is improving their productivity, their work is becoming more cognitively demanding as routine work disappears. And lastly, we try to create intentional space for human connection. So as a remote first company, we've redesigned gathering around this notion of analogue, device free experiences. So at a recent executive offsite, we actually replaced screens with reflection and visioning and relationship building. We even brought in a breathwork specialist and the impact was actually significant. So feeling cared about by other executive team members went from 44% to a hundred percent. And we also looked at our communication pattern. So, it shifted from scheduled meetings towards more spontaneous texts and phone calls, right, which is generally a, a measure of increased trust. 

Femi: Let's look into the future 10 years from now, how will that balance between the workforce working alongside AI, how would that have changed? What will it look like?

Melanie: There's the technology dimension, which is can AI do it? There's kind of this governance angle, like, should AI do it? And then there's this humanity angle, like, if AI can do it, then what should remain uniquely human? So I think there are probably a few things that we can do today to sort of protect our humanity as this transformation unfolds so that we have, you know, a future that's worth looking forward to. Right? So the first is protecting our attention. So this notion of deep thinking is not just a competitive advantage, it's actually good for your mental health. I think the second thing is strengthening human relationships, right? So purpose often comes from being needed by other people, not just being productive. And then finally, and this seems very anti-technology, but staying rooted in the physical world, right? So building things, making things, playing sports, gardening, spending time in nature. I think the more AI pulls us into the digital world, the more intentional we need to be about staying connected to the real one. 

Femi: Melanie Rosenwasser, thanks for joining us.

Melanie: Thank you so much. It was such a pleasure speaking with you.

Lizzie: Pete, when we listen to Melanie talk about how Dropbox is looking for more human skills - judgement, creativity, decision making in their early career hires, how do workers develop those skills if they had not had the chance to learn them in a traditional entry level role?

Pete: Yeah, I, I, actually agree with Melanie. I don't think judgement comes simply from doing repetitive work for, for 10 years. It comes from being exposed, where you can create a view, have it challenged, watch how experienced people approach different situations and occasionally getting things wrong and learning from that. And I think AI can actually help younger people get that learning much earlier in their careers. If AI can produce the analysis, great, but then you're able to ask, well, so what, do you agree with that analysis? What's missing? What would you do? That's where I think the judgement muscle is developed and nurtured. 

Femi: So Dropbox has found that because new hires are performing so well, they're actually expanding the internship and the recruitment programmes that they have for young people because they're more likely to be familiar with AI and embracing it. Is that approach being seen anywhere else? Have you seen that in other companies? Pete?

Pete: Femi, I think it's too early to say that there's one pattern across all employers, but I really like the Dropbox example because I think it challenges an assumption that AI, because it can do junior tasks, we therefore need fewer junior people. We spend a lot of time asking about how we prepare young people for an AI enabled workplace, but some of those people are joining the workforce already comfortable using AI, experimenting with AI and arguably they're more capable than many of the people in the organisation they're joining. So I think there's a question for leaders and for organisations to actually ask, what can they learn from this talented workforce that's joining them?

Lizzie: Following on that a little bit, PwC just released the Hopes and Fears report, which surveys 50,000 workers around the world, and it showed that workers who use AI daily feel more empowered and have higher confidence in their job security. What does that tell you?

Pete: Well, first Lizzie, I, I found that really encouraging. I'd be really careful to say that AI causes confidence. It may also be that confidence and adaptable people are more likely to use AI regularly. But I think there's a very clear lesson for employers around the world that giving somebody access to AI and making them capable with AI are two very different things. You can buy 50,000 licenses and give everybody that license. That doesn't mean you've suddenly got an AI capable workforce. 

Femi: PwC's Hopes and Fears Workers Survey also noted trust in management was going down. What does that mean for upper management?

Pete: I think this is one of the findings that all leaders around the world need to pay a lot of attention to. Of course, people need to trust the technology. Is it safe? Is it reliable? Is it secure? But I think there's another question, which is, what is my employer actually going to do with it? Yet, if you put yourself in the shoes of an employee, you tell me that AI is going to make me 20% more productive. And I'm thinking, great, what am I gonna do with that 20%? Does my job get better? Am I gonna do more interesting work? Or I might also be thinking, ah, you need 20% less of me. Does that apply to the whole workforce? And I don't think that's a resistance to AI. I think it's a totally rational response from a human being. And I think that's what makes the Hopes and Fears findings really interesting together, that people can be positive around using AI, which is what they tell us they are, whilst at the same time becoming less trusting of management. So I think, you know, people do need confidence and trust in the technology, but they also need that trust and confidence in the intent behind it.

Lizzie: Your research also suggests that workers who have strong AI skills are among the most ambitious, but also the most likely to leave. So if you are an organisation, how do you hold onto the people who have these skills who are more likely to lead the transformation? And have them motivate other colleagues?

Pete: Lizzie, I think you get to part of the answer there in your, in your question actually. 'Cause I don't think, retention is quite the right lens to put onto this. You know, these are people who are naturally curious. They are often very ambitious. They learn quickly and they can see where things are heading and they know that those capabilities have value. So rather than starting with a, how do I retain them question. I'd ask, what am I actually going to do and what am I gonna focus them on to keep them engaged? Give them real business problems, let them change how work gets done, give them, opportunity to help other people in the organisation. I really liked, uh, Melanie's example. I think more than 120 employees submitted workflows they'd automated using AI. And I think if somebody's worked out how to remove four hours from a process, I wouldn't just congratulate them and say, well get you get back to your day job. I'd actually ask, how can I use that capability to actually help another a hundred people in my organisation? And I think that's the opportunity and it's how the capability starts to spread across the organisation. 

Femi: I love how you're challenging us to think about the momentum that AI is creating. The momentum is with the workforce. So what's the bold idea that makes sure that leaders keep the momentum up?

Pete: It's interesting Femi because I think there is a danger that the workforce is actually outpacing the ability of an organisation to change. and I, I think for me, people tend to adopt what they've helped to create. I think far too often small groups disappear away. They design an answer, they build everything and then they, you know, near the end they suddenly say, ah, look, we need to get everybody to adopt this. And they're surprised actually when that doesn't happen. With AI, the people doing the work often those that know exactly where the frustrations and wasted effort are. Give them the tools, give them sensible guardrails and skills and then ask them, what wastes your time? What frustrates your customers? What could get better? And where could AI help?

Lizzie: So the people who are listening to this show are business leaders, and if you had to leave them with a few tips for building real momentum about how AI is shifting careers and shifting the career ladder, what tips would you leave them with?

Pete: I think probably three pretty simple things. First, I would start with the work. What business problem am I trying to solve for here? What's not working? What's taking too long? And then I'd work out where the technology can help me on that journey. Secondly, invest in people as seriously as you're investing in the technology itself. Skills, experience, coaching, time to learn and experiment, and don't just invest in the enthusiasts, make sure that the core workforce is getting the opportunity as well. Third, involve people. Be straight about what's changing, including the difficult bits, and give people a genuine role in working out how AI can improve their work.  For me, the opportunity is getting the technology, the organisation, and its people moving together. 

Femi: Pete Brown, thanks for joining us.

Pete: Thank you.

Lizzie: Femi, when I listen to Pete. And then also Melanie, one of the things that I'm thinking about is just sort of like what builds a good employee? An employee who wants to stay? Is it skills? Is it getting honest feedback from management and some sort of leadership and direction? And listening to both of them, they're talking about using these new tools, giving employees confidence, but then also I, would say maybe guiding them in a way where they don't feel like they've just had a new tool thrown at them and their job is gonna get harder and more complicated.

Femi: My takeaway was that there, the common narrative that AI is going to take your job is a fallacy in many respects, because AI is creating more space for jobs and people to flourish and to thrive, if you get into it and experiment and play with it, and then define how you would like your job to be,  

Lizzie: Yes!

Femi: But that does need a fabulous leadership for those two things to happen.

Lizzie: If this episode had you thinking about your business differently, please follow Take on Tomorrow wherever you listen to podcasts. For more go to pwc.com/takeontomorrow

Femi: Next time: 

Daniela Rus: Imagine a future where your tasks get automated. Maybe fresh produce shows up on your doorsteps where roads maintain themselves, at night, where garbage bins take themselves out.

Femi: What does our world look like with more robots in it?

Lizzie: Take on Tomorrow is brought to you by PwC. PwC refers to the PwC network and/or one or more of its member firms, each of which is a separate legal entity.