Anand Chopra-McGowan — Managing Director, Europe, Valence. Host and moderator.

Holly Tyson — Chief People Officer, Cushman & Wakefield.

Allison Pinkham — Former CHRO, Galderma.

Diane Gherson — Former Chief Human Resources Officer, IBM (2013–2020). Board Member, Kraft Heinz; Senior Adviser, BCG; Senior Lecturer, Harvard Business School; Advisory Board Member, Valence.

Davos 2026 | CHROs on AI, Jobs, and the Future of Work

Recorded at Davos 2026, this conversation brings together three of the world's most experienced CHROs — Holly Tyson of Cushman & Wakefield, Allison Pinkham formerly of Galderma, and Diane Gherson formerly of IBM — to share the biggest themes, debates, and takeaways from the World Economic Forum for the HR leaders who weren't in the room. Hosted by Valence's Anand Chopra-McGowan, the conversation covers the reality of coming job displacement, design principles for navigating it responsibly, the shift from individual to team-level AI deployment, the future of education, and what CHROs specifically need to bring back to their organizations and boards.

Key Takeaways

• Job displacement is not a debate at Davos — it is a given. Both Dario Amodei of Anthropic and Demis Hassabis of Google DeepMind were direct: serious unemployment is coming in three to five years. The conversation at Davos has moved past "will AI take jobs?" to "how do we design for what comes next?" HR leaders returning to their organizations need to treat this as a planning premise, not a risk to monitor.
• The CHRO's job is to build AI around human purpose — not jobs around AI capability. Diane Gherson's framing is the sharpest formulation: instead of asking what jobs AI can do and building around that, HR should start with what makes work meaningful — purpose, skill growth, human contribution — and build AI to serve those principles. Entry-level job erosion is a particular risk: without those roles, the pipeline for future leaders dries up.
• AI strategy must start with why, not what. Two top-tier consulting firms gave contradictory findings at the same Davos event — one saying 70% of leaders view AI primarily through a productivity lens, another saying 80% view it through a growth lens. The contradiction is the point: organizations are confused because they haven't answered the why first. Allison Pinkham's framing: define the business strategy, then build org design, skills, and AI deployment around that — not the other way around.
• AI's biggest near-term impact may be on physical and emotional work — in the opposite direction than expected. Holly Tyson's hypothesis: as AI democratizes intellectual capability, it may actually raise the value and cache of physical roles and relationship-based, emotionally-skilled work. With 40,000 employees in skilled trades, Cushman & Wakefield is already watching this dynamic play out — and humanoid robotics, while coming, is a longer path than AI's near-term white-collar impact.
• Deploy AI at the team level, not just the individual level. One of the clearest Davos consensus points: the productivity gap in AI adoption comes partly from deploying it only at the individual level. Integrating AI as a neutral observer of team dynamics — giving it permission to surface behavioral observations without the defensiveness that comes with peer-to-peer feedback — is an underused lever for improving team performance at scale.
• CHROs need to help redesign the global education system — not just their own L&D programs. The education system was built for a world that no longer exists. Allison Pinkham's call to action: CHROs have an obligation to feed insights from the working world back into educators from grade school through university — because if the education system doesn't evolve alongside how work evolves, it becomes a direct contributor to the unemployment crisis. The "degree for life" model — lifelong learning contracts with institutions — offers one structural response.

Questions This Session Answers

What were the biggest themes for HR leaders coming out of Davos 2026?

Three themes emerged clearly. First, the job displacement debate has matured — the question is no longer whether AI will cause serious unemployment, but how to plan for it. Second, the tension between using AI for productivity versus growth remains unresolved at most organizations, and CHROs need to help CEOs answer the why before building AI strategy. Third, the shift from individual to team-level AI deployment emerged as a significant opportunity — using AI as a neutral observer of team dynamics to surface feedback without the defensiveness that undermines peer and manager-to-employee feedback.

What did Dario Amodei and Demis Hassabis say about AI and job losses at Davos?

Both Dario Amodei, CEO of Anthropic, and Demis Hassabis, CEO of Google DeepMind, were direct that serious unemployment is coming within three to five years. This puts them among the more candid voices at Davos, where many AI builders emphasized job creation and human-AI collaboration. Amodei and Hassabis acknowledged the scale of the coming labor market disruption and the urgency of figuring out societal responses before it arrives.

What design principles should HR leaders put in place for AI-driven workforce transitions?

Diane Gherson identifies several: be explicit about the displacement philosophy (will affected employees be offered upskilling? under what conditions will roles be held open?), involve people whose roles are changing in the design of what comes next, and move from a compliance-and-monitor model to a movement-building model. Most critically, build AI around what makes work meaningful — purpose, skill development, human contribution — rather than building jobs around what AI happens to be capable of. A clear why, communicated behaviorally (what will it feel like to work here?), is what CEOs are currently failing to provide.

What is the "firefly teams" concept that came out of Davos sessions?

Firefly teams refers to the emerging pattern of cross-functional teams that self-form rapidly around a specific problem, collaborate intensively, and then dissolve — enabled by AI breaking down the data silos that previously made cross-functional work slow and fragmented. When AI can pull together information from across an organization in real time, teams no longer need to be permanent structures to be effective. The implication for org design is significant: the assumption that teams require stable, permanent structures may need to be rethought entirely.

How should CHROs think about the role of AI in team dynamics and feedback?

Allison Pinkham points to an underused application: integrating AI as a neutral observer within teams, with permission to surface behavioral observations and provide individual coaching on team dynamics. The reason this works is that it removes the defensiveness that almost always accompanies peer-to-peer or manager-to-employee feedback. An AI observing the observable behavior in a room and delivering that feedback one-on-one is structurally different from a colleague or manager doing the same thing — and most organizations have barely begun to explore this capability.

What is the "degree for life" concept and why does it matter for HR leaders?

The degree for life is a model for lifelong learning in which individuals maintain an ongoing contract with a degree-granting institution — returning every few years for weeks or months of structured learning rather than a single multi-year degree at the start of a career. As the pace of AI-driven change makes point-in-time credentials obsolete faster, this model offers a structural response. For HR leaders, it points toward a broader responsibility: not just building L&D programs inside their organizations, but actively feeding insights from the working world back into educational institutions to help them prepare graduates for jobs that may not yet exist.

Arriving at Davos — First Impressions and the Mood on the Ground

Anand Chopra-McGowan: Hello everyone. My name is Anand Chopra-McGowan. I'm part of the leadership team at Valence. I'm joined today by a terrific cast of guests: Holly Tyson, Chief People Officer of Cushman & Wakefield; Allison Pinkham, recently CHRO of Galderma and about to take a big new job yet to be announced; and Diane Gherson, former CHRO of IBM, now board member at Kraft Heinz, lecturer at Harvard Business School among other things, and most importantly advisory board member at Valence. Thank you for being here. We want to have a conversation about what CHROs should keep in mind coming out of Davos. We've been here all week, we've been in so many sessions, heard so many themes and big ideas. Not everybody gets to come here. Not everyone gets to be part of these conversations. So the question I want to ask is: what are some of the things you've heard that you think the HR function and the HR community should know about and plan for as CEOs and board directors get back to the office next week? Let's start with a sense of how your Davos has gone. Holly, we can start with you.

Holly Tyson: If I were to describe my experience here, it's been a beautiful collision of brilliant minds and chaos and curiosity. I've been really inspired by the potential and the possibilities that seem so evident when you gather so many people who know they don't have the answers, but know they want to ask the right questions. That's been the thread of all the sessions and conversations and lunches and dinners — the curiosity about what the future holds. And AI is at the center of every single discussion.

Anand Chopra-McGowan: Allison, how about for you?

Allison Pinkham: Optimism is the word that comes to mind. One of the sessions I had the opportunity to speak at was very enlightening — about the future of healthcare and reinstilling trust in the system. I was participating as a CHRO alongside amazing colleagues from the business and marketing side, and it was a joint effort on how we collectively, from the pharmaceutical world, can reinstill trust in the pharmaceutical and healthcare industry. It was a great opportunity to bring together a collective sense of thought regardless of which role you play — because everyone at some point has had something affecting them or a loved one medically. It was a great opportunity to bring like-mindedness to really reinstilling trust in an amazing industry that needs to continue to move forward.

Anand Chopra-McGowan: Diane, how about for you?

Diane Gherson: For me, the thread was uncertainty. I went to a NASDAQ session which was fascinating because people were starting to process the fact that the global corporation would no longer exist as it is today. For most of our professional lives, that was something we just took for granted. We built it — because digitization allowed us to build it — and now it's being dismantled because of tariffs but also because of a need to build coalitions of economic strength. And then on the AI side, the uncertainty is: what is it going to do to unemployment? What is it going to do to society? Some voices — mostly the purveyors of AI — were very optimistic: we'll find them new jobs, it'll be higher level, that kind of thing. But others, notably Dario Amodei from Anthropic and Dan Schulman, were quite clear: we're going to have serious unemployment in three to five years, and we're going to need to figure this out because it's going to affect all of us.

Job Displacement — Planning for What Is Coming

Is AI-driven job displacement inevitable — and what is the CHRO's role in responding?

Anand Chopra-McGowan: Diane, you touched on the job losses that really are coming. I was in a session with Dario Amodei from Anthropic and also Demis Hassabis from Google DeepMind — very much at the forefront of building these AI models. Both were quite blunt about this: they absolutely believe job losses are coming. That is something the HR community needs to be thinking about and planning for. I want to see if there are other thoughts — positive, uncertain, negative, whatever — that the HR function should really be thinking about. We actually debated this last night at a dinner with Valence and the FT — the question of job losses as a given, with operating expense going straight to the bottom line and shareholders benefiting but the overall organization maybe not. I was on the other side — the view that companies should use this as a portfolio optimization strategy rather than just eliminating positions, reallocating them for growth. There will be certain roles where you don't need as much human cost and structure to create efficiency. But the hope is that we eliminate those positions to free up capacity to be reallocated — to do more differently, not just more with less.

Diane Gherson: We can't make the same mistake we made when we went into factories. And I'm hearing discussions that sound a lot like white collar will become a white collar factory — with standardization. How does that feel? And there's another version: content will be created, entire work processes will be run by AI, and we'll just be monitoring them like hall monitors. Well, we didn't go to college for that. Another version I've heard is: jobs that require empathy — those are what humans will get. But the ones involving analytics — those will go to AI. Believe it or not, there are some very brilliant people who were born to be great scientists, great analysts, great in every one of those fields. Are we going to deprive them of a career? The HR function needs to think through how to build purpose and meaning into the jobs we create. Instead of building jobs around what AI can do, build AI around the principles of what a meaningful job looks like — an opportunity to grow your skills, a sense of contribution. The other thing we're really concerned about is entry level. Where are future leaders going to come from if we don't have entry-level jobs? At some point, no one will have done the work to know how to oversee it. The decay of foundational skills is a real risk.

Allison Pinkham: There seem to be differing schools of thought — not just here at Davos but in IMD research and elsewhere. Some people are saying the front line is going away — it used to be a pyramid, then a triangle, now it'll be a tiny triangle because it's AI agent to AI agent. Others are saying org design will look and feel differently but it'll be a different skill set people are doing. As CHROs, our job is to equip people for future skills — not just for productivity enhancement in their current jobs, but being crystal clear on what you're going to use AI for in your company. That's really important, because AI just becomes a shiny object that everyone starts chasing around — but it may not be the differentiator you need. It always needs to start with the why. What is the business strategy, and what do we as a company want to use AI for? Then you build your org design, skills, and capabilities based on that. Yes, everybody should be using AI to increase productivity. But that's not the endgame.

Diane Gherson: It's almost like a triangle: the why, the what, and the how. The what is really clear — that's AI, what it can do. The why is your point: saying it's for EPS or productivity is not inspiring and not very helpful. But if you can say we need to get to market faster to beat our competitors at X, we need better net promoter scores or we're going to lose market share — something that drives people, makes them understand and excited — that's what CEOs are falling apart on. CHROs have to help them with that. Behaviorally, what is it going to feel like to work in this organization? Give people a vision of that. That's part of the why. And then there's the how — where HR has to come in and say: here are the design principles, the ethics guidelines, the guardrails, the displacement philosophy around people losing their jobs. Are they going to be offered upskilling? Under what conditions? Are we going to keep them for a period of time? Having a clear set of design principles builds the psychological safety to move forward together. And the other critical element is participating in the design — particularly for the people whose roles are going to change.

Physical Work, Emotional Skills, and What AI Can't Replace

Which kinds of human work will AI impact least — and which might actually rise in value?

Holly Tyson: AI is going to be impacting intellectually based roles — white collar positions. At Cushman & Wakefield, where we differentiate ourselves based on relationships and skilled trades, it's curious to me: if you dissect humanity into intellectual skills, emotional skills, and physical skills — with the potential democratization of intellectual capabilities — my hypothesis is that it may actually raise the cache and importance of physical roles and the emotional, relationship-building roles that humans do. I'll put that as my prediction and my hope. We as a humanity do a whole bunch of different things, and AI is on the intellectual side of it, but there's a lot of other things we add value to in the global economy.

Anand Chopra-McGowan: When you say physical roles, what kinds of things are you talking about?

Holly Tyson: Skilled trades. We have 40,000 employees who do everything from building out buildings, to changing light bulbs, to scrubbing toilets. I'm not saying humanoids aren't going to be able to do that at some point in the future, but that is going to be a longer path. The physical piece of human work is going to continue to have a pretty important role for a while.

Anand Chopra-McGowan: There is data showing that roles like plumbers and electricians have high demand and not enough supply, and we are seeing rises in those wages. Demis Hassabis from Google DeepMind does predict we're only a few years away from the humanoid debate becoming real — but these things are fast-evolving.

Deploying AI at the Team Level

Why does AI need to be deployed at the team level — not just the individual level?

Anand Chopra-McGowan: One of the themes I heard a lot at Davos is this notion that we need to be thinking about how we deploy and embed AI at the team level, not just the individual level. I wonder if anyone would like to comment on how that might play out.

Allison Pinkham: One of the beauties of AI — starting with the why, what are you trying to solve within the team environment — is that you can integrate AI into your team environment to be the coach or the feedback channel for your team. When others give feedback, whether peer-to-peer or manager to employee, there's always a quick sense of defensiveness. Maybe they're biased. Maybe it's this. When you have AI observing how the team dynamics work and give it permission to say "here's what I observed" — and it can do one-on-one coaching with the individual and share those observations on how to strengthen the team — it automatically takes away that defensiveness, because it's AI. It's observing observable behavior that is in the room. A lot of people are hesitant to give feedback. It goes against human nature, and as much as we try to encourage constructive feedback, there's always this hesitation and it holds teams back. AI is a great opportunity to leverage technology to enhance team dynamics and bring teams closer together.

Holly Tyson: I'll double down on what Diane was saying earlier — setting up the guiding principles for how to structure work and teams, and the participation of people whose roles are going to change, will be absolutely critical. We need to break our eye a little bit in terms of not assuming that AI agents are going to fit into the current structure companies have. We should really change that paradigm and open it up to: how should work get done in general, versus slotting AI into our given assumptions about how work happens today? I heard a great phrase at a previous session: we need a new science for knowledge work. The thoughtfulness we put into the individual tasks is so important.

Diane Gherson: The firefly teams phenomenon is already happening. What AI does is facilitate it — because before, data was isolated in silos, and even if it was sitting in a data lake there were all kinds of controls around who could get at it. Now AI can just go through, sift it, pull it together — and that makes self-forming cross-functional teams so much easier, because they're all accessing the same data and information. The idea that we've got a permanent structure — you really don't need that anymore, because you can solve problems on a cross-disciplinary basis with AI.

Education, Foundational Skills, and the CHRO's Obligation to Society

What responsibility do CHROs have for reshaping education — beyond their own organizations?

Anand Chopra-McGowan: The first concept I want to name is the "degree for life." As the pace of change continues to roll, one idea is that we stop thinking about education as this thing that happens once at a point in time and then you go to work — and instead create an infrastructure for lifelong learning where you literally create a contract with a degree-granting institution that you go back to every few years for maybe a few weeks or months to continue to learn. Another is the notion of an AI board member — at a dinner co-hosted with the FT, someone from a big bank mentioned a bank in Asia where there is an AI board member and it has a vote. What does that mean for corporate governance? And the third is firefly teams — cross-functional teams forming more quickly, bringing more cross-functional skills, collaborating effectively with the forming pace that AI allows. What were your reactions to some of these concepts?

Allison Pinkham: There's been fascinating conversation about overhauling the entire education system. When you think about how people were educated up until now, it worked in the working world — but now the working world has changed. The education system needs to change and adapt and evolve as well. As CHROs, we have an opportunity to contribute thoughts and insights from the working world back to educators — from grade school through university — on how to teach for the future. Because if the education system doesn't evolve as dramatically as how work evolves, it contributes directly to this unemployment crisis when people are graduating. There's an opportunity not just around lifelong learning inside companies, but around having a contribution back to society and the insights back to the education system to help prepare our societies for the future.

Holly Tyson: I have a different view on education — maybe I'm being a little too controversial. The degree for life: my point of view is twofold. First, I think we have to be really concerned about the decay of foundational skills. It's like the calculator: we can all use a calculator, but we should all know our times tables. Because the more we're going to be relying on agents to do these things, the more dependent we are on something outside of our control. The next generation of workers needs to learn using the tools but also know the basics those tools are built on. Second, my hypothesis is that learning in general is going to be more like performance support — getting the information you need when you need it at that point in time, versus necessarily going to school. I believe in a foundational set of skills, but if somebody asks me to quote some random Victorian novel, I'm going to Google it. There's something about having foundational skills but being able to find out how to do what you need to do at that moment.

Diane Gherson: I really agree on the foundational point. A lot of people say we don't need handwriting anymore — and that's true, nobody derives purpose from handwriting. But something like calculating: what if we're cyber-attacked and none of us can use our calculators or our phones — what happens to our economy? We need to draw the distinction between what are the foundational skills and what we can look up. The second thing: when we talk about this idea of the new academy, what people are generally talking about is coding. And what you took — psychology and English — is actually very grounded. It gives you ways to look at the world, enables you to think creatively. What we're going to see is less value in studying computer science that is out of date in two years. I was talking with the CTO of one of the companies I'm on the board of, and he said none of the computer scientists coming out of college have learned how to code — they now know how to train LLMs. And when I asked what the difference was in what they're capable of doing, he said: they don't know how to break apart problems.

Holly Tyson: Well — that's a foundational skill.

Diane Gherson: Spot on.

Anand Chopra-McGowan: A very good example of a foundational skill. Thank you all for listening. Thank you to Diane, Allison, and Holly for all of your time and insight. Hopefully this has been helpful as you think about some of the takeaways from Davos and the many themes and ideas discussed here — and the role for the HR function in really planning for and designing for the way that we actually survive and thrive in a world of AI.