Preparing for an AI transformation: A conversation with Bettina Dietsche, Chief People and Culture Officer at Allianz Group

Katharina Hesse: Hello, I'm Katharina Hesse, a partner in Heidrick and Struggles Zurich office, and a member of our Financial Services Practice. I co-lead our insurance sector, and today I'm joined by Bettina Dietsche, chief people and culture officer at Allianz Group. Allianz is one of the world's leading insurers and asset managers, with offices and operations spanning more than almost 70 countries. Bettina has more than 25 years of international leadership experience, spanning across insurance, financial services, technology, and operations, and today she's driving Allianz's people and culture agenda. At a time when AI is rapidly changing how organizations operate, Bettina is closely involved in preparing Allianz's workforce and leadership team for that transformation, and she has a particular focus on skills, culture, and responsible adaptation of AI. Bettina, welcome. It's a great pleasure to have you here today. 

Bettina Dietsche: Thanks, Katharina. It's my pleasure to be here. Look forward to our joint dialogue. 

Katharina Hesse: Fantastic. Let's move right into the first part about AI and the changing workforce. Bettina, AI is moving very quickly from experimentation into everyday work and from your perspective, how fundamentally will AI change the workforce? 

Bettina Dietsche: A very broad question. Let me nuance it a bit of how I look at it. I think it will shape or reshape almost every function drastically. Some more, some less, but there's hardly a talent segment that I'm not seeing would be transformed or adopted or augmented, assisted, however you want to call it. And I explicitly see this in the financial services industry. I think we're really one of the industries where it's all about data ultimately, right? We don't sell fancy cars or fancy products. We sell data with the promise that in the moment when things go south, that you can rely on your insurer to get the best service, the best help you need. And I think this combination of having technological data-driven thinking, together with this human touch when things go south—you want to have a person who cares, who helps, who shows empathy. That's actually the combination I believe shapes our business model and the way we operate most and the fastest way. That's why, for me, this is clearly not a hype, not a thing that comes and goes. I think it's really shaping fundamentally how we operate every day, and we see this today already. 

Katharina Hesse: That's a very good word that you're using, ‘hype’. I was asking myself, how do you evaluate what is truly transformative and what is AI hype? 

Bettina Dietsche: Yes, I find that difficult to answer. I believe, in what's happening and also what we see here, we have experimented a lot. We have more than 700 use cases. They came up like mushrooms, which is very great because you can see that people take it, learn with it, generate ideas, bring up ideas [for] how to use it. Which I believe in the time where people still need to learn what is AI, what is it good for, what can I not trust? Right? How do I need to be critically thinking about whether this is a good outcome? I believe this experimentation and that it's everywhere and everyone talks about it, is healthy. 

I believe now we're at the turning point, though, that besides the fact that there are so many use cases, you need to funnel them to really say what are the big bets? What is it that we aim for achieving at scale? And you said it in the beginning. For us, I look after 156,000 people, right. And they’re all over the world. So I want to get solutions which scale fast, and I believe that's where we are at the moment. From experimentation, a lot of use cases, to really funnel and get it out fast. Because what's different this time compared to many digital transformations, at least I've seen and I've been in, is mostly its speed. Speed matters, given that every two weeks there's a new language model, every two weeks there's a new way of how you can do it. So speed matters at this time. 

Katharina Hesse: Thank you so much, and we'll get back to the scale when we talk a bit about the structure, about the organization. One additional question I had was: Allianz has already been investing significantly, and you talked about the amount of use cases, which is impressive. So you have invested in building AI capabilities across the organization. What major changes have you already seen in the workforce, the roles, the way of working, the organizational structure, and what is to come? What comes next? 

Bettina Dietsche: Yes, let me probably start with what I've not seen yet. 

Katharina Hesse: Okay. 

Bettina Dietsche: I've not seen yet that the organizational setup has fundamentally changed. I think we see at Allianz a lot of enterprise agility, you know, in the sense of how we approach topics in an agile way. And I've not seen yet that there is [just] one new operating model out there, which now will be just simply the next step. I’m actually discussing this quite intensively with colleagues outside of our industry, but also here. I'm not even sure if there will be ever a new operating model, or whether the new thing is clearly that you need to be able to reflect your design principles every quarter to really make sure you're ready for what's coming next. Staying adaptable, staying flexible, I think that's more the new operating setup, rather than having this new target operating model, which people might have in mind when you [look at] the last 20 years. 

So I think that is something I'm not seeing yet. But what I see is that the adoption and the trust of people using AI has really levelled up. Right? We asked our people in early January of this year: Do you trust AI and what's your adoption? And the numbers we got back globally—59% of people said they trust—were already quite good. I was quite impressed. If I compare it with global benchmarks, we’re even better. But I would expect now if we run a new employee survey in two weeks, that the same question hopefully achieves even higher feedback already. Because for me, this is the most important KPI. 

I keep saying to everyone, if you wake me up at three o'clock in the morning [and ask] if there's one KPI I measure this year, it's do people have trust in AI. Because it's a nice correlation, if people have high trust, they have high adoption, and adoption is what you need in order to actually apply it, use it, live with it, learn it, you know, redo things, innovate new. So this is why I want to focus on this piece, and that's clearly what we see.

Katharina Hesse: Bettina, previously I've heard you say that AI should not replace human judgement, but should enable people to make better decisions. And as AI becomes more capable, how do you decide where technology should lead and where human judgement must remain central? 

Bettina Dietsche: I truly believe that it's not AI that makes the difference, it's the human who makes the difference. And the difference is that we use AI smartly where it helps us to become better, faster, more customer-focused, more driving really what customers need in the future—but ultimately the decision is a human one. And I think the humans, what makes us unique is our emotions, the way we look, the way we judge, the way we discuss things, the way we react, the way we treat things fairly—I really believe that's the difference. And that's where I want to make sure that going forward; even though we use AI, we can always make sure that we do things in a fair, human way of making the judgments. And I believe explicitly with the ethical discussion, right? What's ethical? That comes into the game more than ever. I mean I think we need to always ask ourselves, is this what we would want to see happening to ourselves? And that's where I believe that ethical AI is a new dimension. 

I'm very glad that we have introduced the Ethical Board, so we do discuss [things] like what are new technologies, new tools, and how far do we want to take it? And it's, to be honest, also very fair to say in the beginning we thought AI is biased. And yes, it is, but humans are as well, right? And maybe the technology is less biased than we are. But I think the touch and the decision making and this human differentiation, that is what makes us unique, and this should stay unique. 

Katharina Hesse: I would like to talk about building an AI-ready organization, and we've talked a little bit about it before. You've already had quite a bit of use cases and adoption, and Allianz has undertaken up-skilling at a significant scale, including through your global AI run. What have you learnt about building AI literacy across such a massive and diverse global workforce? 

Bettina Dietsche: Yes, you're right. Actually, I'm very proud of our lifelong learning DNA, I would call it. And if I compare only the last three years, I mean we started with the AI, first AI run, even two and a half years back already. So even when it was just around the corner, and obviously the magic is that you constantly challenge the things you trained and learnt, the people are still the best way of bringing it closer. 

And I can clearly tell you, our first AI run was [to] get everyone to understand how to prompt and, you know, do the basic things, and we have refined that to what matters most in the time you're in. So, for instance, last year it was a lot about tools. This year, it's not at all about a tool anymore. I couldn't care less whether it's Claude or Copilot or ChatGPT. It's not the tool. It's actually how you use it. So the secret I find is that you constantly adapt your learning and the way you want to see people take skills up by offering what matters most. 

So the first AI run was, you know, to everyone. Now we have more moved in to learn, apply, learn, apply, learn, apply. Because we understood that learning is one thing, but you need to have the room and the time to apply it and then learn again. So these principles and this way of how we operate has changed. In addition, just months ago we started to discuss [that] we want to see people learn together in the [same] room because we clearly see that you learn the most when you sit together, you share the same screen, you look at the same things. So this interaction is even more beneficial at these days than it was when we started with the whole journey. 

So what I'm saying, I guess, is learning per se is the most important thing for us. I'm very proud of how we levelled up. We spend more than 120 million for learning. We have more than 65 learning hours per person per year. So it's really massive. But you can learn until the cows come home, but if you cannot apply it? So it's more about finding the moments where people have time to apply it and then learn again, and that's the secret [for] how we try to take it forward. So I'm very much sure if you ask me in half a year, I can tell you already what worked well this year, but might not be the right thing for continuation. 

So it's the constant adaption, and that's for me maybe the one thing if you asked me what has changed, it's staying adaptable in every way. That's for me the secret sauce in every function and also for our function, where we offer the learnings. You need to stay and understand what matters now and you cannot say well, but I've planned it last year and now we’ll do what we planned last year. Its speed, it doesn't allow you to do that. You need to be constantly on your forefoot to respond to what matters most to the people. 

Katharina Hesse: And maybe you've already answered now my next question because this is around skills, you mentioned skills. How do you identify which skills become more valuable over the time that you adopt to AI? And how do you help people transition today's skills [over] to tomorrow? 

Bettina Dietsche: Yes, skills for me are really the new oil. It's the currency, I have to say, because we hired in the past and we train people for something backward-thinking. Right? I keep making the joke. When you go on LinkedIn, you find all rock stars out there, right. But you might hire someone who was a rock star in the past, [and] might not be the rock star of the future. 

Katharina Hesse: Yes. 

Bettina Dietsche: So I think continuously challenge what skill you need to be successful with customers for your business, to actually be capable to manage the resilience topics. That's for me something which we have learnt also. 

So I can tell you how it evolved. We have always been putting a lot of focus on EQ, IQ. So it's always both, right. It's the technological skills, the business and the functional skills, but it's [also] the human skills, like how do we collaborate? How do we communicate? How do we interact? All these EQ and IQ principles were very strong [for] us, but now we have [added] the past years’ skills to it. And we're just putting a huge focus on, we call it AQ now, which is really having AI [skills], but also the adaptability on the human side. 

And we're just discussing what we want to bring forward to our leaders, for instance, you need to show the critical thinking; you need to be able to do scenario planning more than you needed to do in the past. You need to have an ethical judgement and governance judgement on AI. So we identify modules which we really bring into the organization, where we want our leaders explicitly to learn, to understand, because they are the role models for the teams. So these modules are all centred around what matters most now and AQ is not a technological skill. It's a human skill, staying adaptable, putting more focus on empathy, putting more focus on business judgement. Right? You get a lot of people in [who] use AI, but if the outcome is wrong, you need to have this judgement to say can that really be true? 

So these modules [are what] we put focus on, and they are constantly evolving. So what matters now might be different next year, but we try to have the skills in place where we train our people for what matters for them to stay not just employable, but to really learn for their life actually going forward. 

Katharina Hesse: You mentioned trust and you mentioned tempo before, and one of the challenges with AI is that adoption sometimes moves faster than people's confidence in it. What concerns are you hearing? 

Bettina Dietsche: Yes, I'm actually glad that I heard that concern because when we asked that one question in January, ‘do you trust AI,’ we also asked the question, ‘and if you don't trust, why is that?’ And the feedback, I was very pleased to hear from my people because they said I'm not trusting because of data, data privacy, or any other reasoning. The most reason which came out is that they said I don't trust because I'm not sure if the outcome is right yet, which I was glad to hear, because obviously what we don't want to have is that people just stupidly use AI because it gives you such nice feedback or such a nice statement but unfortunately, it's wrong. 

So, this critical thinking, analytical thinking, giving business judgement to it, that's what I believe is—I'm glad that our people are reflective enough to say I'm not just blindly accepting whatever comes back. And that's why I feel as long as this is something we can help them to train, to get better, to make really get these capabilities to judge it, I feel very comfortable that we have really positioned AI as a tool which is here to help and to make us better, but not as it’s just there; we take whatever comes out and we make our business judgement based on this solely. It's really the human judgement which comes into play. 

Katharina Hesse: And is there a regular process to find out what the concerns are and to address the concerns? 

Bettina Dietsche: Absolutely. We have a very rigid way of how we look through the year when we ask our people what do you see? What's missing? What are you telling us, and how can we apply and learn from it? And we do this with pulse check-ins twice a year, and we do a lengthy employee engagement survey where we ask explicitly these questions So with these check-ins, we can make sure that we listen to what our people tell us; the good things, but also the things where they say I expect more, or I would hope we can do more. And then we can have actions centred around this to really like, in the sense of I like the word of we listen, we act. Right? So for me, that really walks the talk. That we are not just asking them are you happy, but much rather, if you're not happy, tell us what we can do better, so that we can walk and really improve things. And that's the mechanism which serves us very well to continuously improve what our people tell us [so] we [can] become [an] even better place to work. 

Katharina Hesse: I would like to move into the third section, third part of our conversation, and that is about leadership and culture in the age of AI. You've just mentioned before, and you've made the point in previous conversations that AI itself doesn't create a high-performance culture. People do. 

Bettina Dietsche: Yes. 

Katharina Hesse: So, what does leadership need to look like in an AI-enabled organization to ensure technology actually improves performance? 

Bettina Dietsche: Yes, for me it's most instrumental. I keep saying as a leader, if you're not authentic and you cannot walk the talk yourself, how do you expect that your people do?

Katharina Hesse: Yes. 

Bettina Dietsche: And that has nothing to do with AI, to be fair. But I think in the speed of AI now, the adoption of how a leader embraces it and can also learn and grow with it makes a big difference if your people will follow you, because people watch you. Right? I mean it would be the same if I say to people, please go out and learn and do all these things—if I ask someone else to do it, I better be the first one who has done it myself. So I feel every leader needs to be equipped, needs to understand, needs to also be open for sharing the concerns. Right? Because I think it's a lot we ask from leaders these days, in this volatile world there's drama everywhere, you know, there is speed which comes in, there's change which comes in. And as with every employee, not every leader feels equipped. But helping the leaders to be equipped and then also act as the role model, for me is the most important thing. And we see when leaders are walking the talk and are equipped and learning with the people in the room, the adoption and the trust again goes up. So that's why for me it's all about having leaders who can really be the role models. 

Katharina Hesse: Yes, it's a big topic. And one additional question I have is how are you creating that type of environment where a leader feels vulnerable enough to actually do that, to learn with their people and not be the person at the very top who knows everything and has all the answers? 

Bettina Dietsche: Yes, I think that's a very '90s way of looking [it]. I think it's nothing you can create because that's a cultural element, and culture is shaped by everyone. Right? And I believe culture comes from having more and more leaders who dare to say hey, I'm not the expert in the room, nor do I know everything actually, others know it a lot better. So having a culture where you have leadership who demonstrates that they trust, that they empower, that they encourage people also to fail, learn from failures, innovate, [and] are more of a coach than they are a leader in the traditional old thinking. That's what we try to influence when we hire leaders. 

For me, I care less about the content because if I hire a person, it's obvious that the person knows something about the job. I want to see the person and how he or she talks about culture, about how [they] make people grow. To me, that's a leader, and the more we have them, and luckily I can say we have them, you can see that the whole organization is moving to a tipping point where this psychological safety of speaking up, feeling safe to say hey, I'm lost, I have no clue, or I need help, that's to me a healthy setup because that's what I believe the future will be more and more about. Right? Not everyone knows everything, but you want to have a leader who gives the trust in others to grow and help them if they struggle. 

And that's why for me that is the culture. And I keep saying for me, culture is as I said, you cannot impose a culture. It's what everyone does every day, and it's a nice way of describing that culture is how you behave when no one watches you. Right? Not when the boss is in the room or tells you, and then everyone is friendly, nodding, leaving the room, and then they act differently. 

So I think you can see it. You can see it if you really get this feeling that people, you know, behave no matter who's in the room, they will always go for the right thing. And that's why I think we can see it now luckily, that we do have people who speak up to say like I need help or I'm not convinced or I feel differently. That's the culture which nourishes exactly this kind of change and speed. We have a different way of looking at the problems of today, and we’re not answering it with how we [did] it 20 years back. 

Katharina Hesse: Thank you. And at the very end, maybe a bit of a broader question once more. Insurance, as we said before, has always depended on data, judgement, and trust, and as AI becomes embedded across the industry, where do you see the greatest opportunity to improve how insurers more broadly work in the future? 

Bettina Dietsche: Well, I think in many dimensions, because obviously the customers of the future are the ones who use technology differently than we have used it in my generation, so I believe if we respond to the demand of a customer of the future, not with our old processes, just doing it a little bit more digitally, but really rethinking, re-imagining how a customer wants to work and operate with us, that's the foundation of getting the speed and the technology kicking in. 

And then again, I think what will not go away and what really allows us to make a difference is the human way. In the moment when yo/pst] tell me your policy number and then I'll process you through. But rather say, are you safe? Can I do something? Is your family safe? How can I help you? Because that's the moment when you're in stress. That's where we can make even more a difference, and that's again where I believe technology can help us to be fast. But this human way can make a difference for really caring about the customer in the moment when he or she needs it the most, and that's for me a nice way of how we can grow. 

Katharina Hesse: Yes. 

Bettina Dietsche: Right, it's a grow scenario. I like to think that it's not just about productivity and becoming faster, but how can you grow a business where new opportunities come in, where the world is changing, where new customer demands kick in. So for me it's really win, win, win if you steer it right. 

Katharina Hesse: Amazing. Thank you so much. Bettina, thank you very much for being here with us today. This was such an interesting conversation. 

Bettina Dietsche: Aw, thanks, Katharina. Always a pleasure. Thank you for having me. 

Thanks for listening to The Heidrick and Struggles Leadership Podcast. To make sure you don't miss the next conversation, please subscribe to our channel on your preferred podcast app, and if you're listening via LinkedIn or YouTube, why not share this with your connections? Until next time. 

About the Interviewer

Katharina Hesse (khesse@heidrick.com) is a partner and global co-lead of the Insurance Sector; she is based in the Zurich office.