Well, thanks so much. It's really great to be here. My name is Bill Anderson. I'm based in Leverkusen now, but I grew up in a small town in South Texas. And I tell people the town I grew up in was sort of the Texas version of Leverkusen. So, I feel very much at home in Germany. Last 3 years, my wife and I have been here. Beautiful country, wonderful people, and so great to have an opportunity to be with you today. We're talking about change, we're talking about innovation, disruption. In my life, if I think about it, I've lived through several of these. I remember when I was about 10 years old, my dad showed up with a Commodore computer. It was like a keyboard. You plugged it into a little television set. And he said, 'It's a personal computer.' And I said, 'Great, Dad. What do you do with it?' He said, 'I don't know. You know, I'm too old to figure that out, but you'll figure it out.' Okay. And the personal computer was born. I remember in around 1993, I think it was, I was a grad student at MIT and I was working late in one of the computer labs and one of the guys there said, 'Hey, come look at this.' And I said, 'What is it?' He said, 'It's the internet.' And I was like, 'What is that?' And he's like, 'Well, look, you can ask questions and you can get answers.' And so, you know, wow. I thought that was pretty cool. I remember I think it was 2007. I was working in the Bay Area and my company was actually one of the first companies to have this new thing called the iPhone. I got it. I used it for about an hour. I got home that night and I said to my wife, I think we should buy Apple stock. Of course, we didn't do it. I wish we had, but I think I'm a better manager than I am investor. Now, we're talking about maybe the biggest innovation of our lifetimes. AI has the potential to have a bigger positive impact, but also perhaps be more disruptive than any of those things. And so, my job here this morning is to share a few thoughts about AI and the future of work. So, let me just dig right in. First thought is AI is not going to fit in your org chart. Okay, we have an organizational model that is industrial age. The current organizational model that 99% of large companies use was developed for, you know, railroad companies and ship builders in the 1800s. And it features hierarchies and hyperspecialization. You know, let's say you're going to develop a new prototype. You've got maybe an engineer, you've got a purchasing person, you've got some production person, maybe a marketing person, maybe a lawyer, who knows a few other things. They're all organized in departments with managers, multiple levels, right? AI is going to cut right across that stuff. Some of you have used these tools. I've used some of these tools. It just blows up org charts. It's not going to fit in those boxes. So what is that new organization going to look like? I mean, what does that mean? Let me share just a little background. When I arrived at Bayer 3 years ago, we had 15,000 managers and about 100,000 people. Okay, 15,000 managers, 100,000 people. That's pretty normal. Actually, that's even fewer managers than a lot of companies that size would have. Today, we have about 88,000 people. We have 5,000 managers. Okay, we took out two-thirds of management roles. We went from the typical manager managing five, six, seven people to many people are managing 20, 30, 50, 100 people. All right. What does that mean? If you're managing 100 people, you're not doing the same thing you were doing when you were managing five. Your job is not to tell them what to do, not to tell them how much resources they can use. Your job is to make sure that they have the ability to coordinate amongst themselves and figure it out. Okay? You get rid of all those organizational boundaries. People are operating in teams. They're getting it done. 95% of decisions are taken by the people doing the work. Not nowhere in the management hierarchy. We took out half of the management hierarchy. I met in January this year, had a long sit-down discussion with the CEO of one of the largest tech companies in the world. You all know them. I won't say who it was but they wanted to know about our organizational model and I explained the organization model and when I finished he was kind of visibly shaken and I said, you know, what are you thinking? And he said, you've put in place the model you need to rapidly adopt AI at your company. We haven't done that yet. You know, we're not nearly as ready to do this as you are. Even though we're a tech company because adoption of AI is not a technological problem. It's not. Those of you who are in it, you know what I'm talking about. It's an organizational problem. How do you do this right? How does it fit with the organization? You need a very flexible, adaptable organization and you need one where the decisions are made at the bottom because the adoption is at the bottom. It's not some senior manager, you know, explaining AI. That's kind of a joke, isn't it? So AI is not going to fit in your org chart. Second, we need creation, not regulation. And I won't say a whole lot of this because I think I'm probably preaching to the choir, but pioneering is hard work, right? You got technical risk, you've got financial challenges, you've got commercial risk. What about the competition? You don't need another set of problems. And that's what regulation is. And by the way, I think the AI Act, this attempt by the EU to regulate innovation in AI is a disaster. Okay? Because how can you regulate something that isn't there yet? You don't know what you're regulating. You got to press forward and then once you figure out what it is, then you got decades to regulate it. It reminds me of a quote from Ronald Reagan. That's showing my age. Ronald Reagan said that the government's approach to the economy is three rules. If it moves, tax it. If it keeps moving, regulate it. If it stops moving, subsidize it. That's not the right way to deal with AI. We got to go fast as we can with AI and we'll, you know, why? Because we have the opportunity to do things like two examples. I was in India last week. Okay, we have 30 million small farmers that we're supporting in India. Okay, we have 5,000 total employees there. How can 5,000 people, by the way, 5,000, probably only 2,000 are working with farmers. How can 2,000 people support 30 million farmers? AI, right? We have apps that the farmers can get advice on diseases that are affecting their plants, on insects. They can call up a drone operator to come and cover their field in 15 minutes. That would take them a day hand-spraying, right? This is technology. This is AI-enabled. In the West, we have applications now. You've seen AI reading radiology images, right? Well, we do the same thing with satellite images of fields. We can spot a disease outbreak with an AI read of an image from the satellite and go and send a fungicide to hit the disease before it spreads so that we minimize the use of the chemicals. Okay, this is what we need to be doing, not fighting regulation. Third, leaders, and this is probably the hardest part. Okay, leaders need to have a moral perspective on work. And now that may sound kind of strange. What do I mean by that? I had a conversation, I had lunch a few weeks ago in China with the founder of one of the world's largest, another one of the world's largest tech companies. Okay. And we had a little debate at our table between this gentleman and me about how disruptive AI is going to be. And he said, you know, look, we had the automobile, we had the personal computer. You know, people figured it out. Everyone thought when the automobile comes, it's going to cause unemployment because, you know, all the people who take care of the horses aren't going to have jobs. But that didn't really happen. And I said, I like the analogy, but if we're realistic, the automobile took five decades to go from zero to something like full penetration in countries like Germany. All right. Do we think it's going to take five decades for AI to penetrate the market? Anyone? Five decades. How about three decades? Anybody? Two decades, one decade, one decade. Yeah. Five years. Yeah. Interesting. I don't know. I don't think anybody knows, but it's not five decades. So, if there's massive disruption, we need something to rally around. Right now, we have a model that we are demonstrating today in Berlin is broken. You know what I'm talking about? We have a model of the economy that's sort of like, oh, the capitalists, the capitalists see work as a way to make money. The socialists think work is a way to make jobs, right? And then we have this kind of fight and there's some sort of balance between jobs and money. That's not working. Okay, that's not working. That's a failing system. I mentioned I've spent time so far this year quite a bit of time in the US, India, China. They're, you know, the cities are not shut down because of strikes. They are moving forward really fast. We better figure this out. And for this, by the way, I'm not blaming one side or the other. We got to have something to rally around. Let me share a story. Before I came to Bayer, people said, 'Well, you better talk to the workers and figure out what the workers want.' And I said, 'Yeah, believe me, I think that's really important.' So, when I interviewed with the head of the Betriebsrat, you know, I talked to them and said, 'Look, I have some weird ideas about management. First off, I have some things you're going to like. I think 95% of decision-making should be at the bottom of the organization.' And they said, 'Yeah, we like that.' Okay. I said, 'But this model of a balance of interests between the capitalists and the social view, it's never going to work. It might have worked for a time, but that's not what we need. This is what I believe is correct. The mission has to come first. The company exists for the mission. What is the mission? The customer, the value we're going to bring to the world, the lives we can change. That's the mission. Comes first. Employees come second. Shareholders come third. Senior management comes fourth. That's the order. If we can agree on that, we're going to have a great partnership. If you don't agree with this, please don't hire me because it won't work, okay? Because this is very important to me that we have this set of values.' And basically they said, 'Yeah, let's do this.' And we have a great partnership and we're transforming Bayer from a beautiful company with noble goals but a very stiff, slow operating system to a very fast, nimble company. Things that took 2 to 3 years or never are now taking 6 to 12 months. Product launches, tech transfers, new product updates. These things are going faster than ever because we have an alignment around the mission view of work with the disruption of AI and it's going to be big. You got to have something to rally around that we can all agree on and so we got to go fast. I don't know. Is it going to be mostly adding value, creating new markets? You know, that's the optimistic view. Is it going to wipe out jobs? That's the pessimistic view. I think there's going to be some of both. But we got to have as leaders a compelling vision for how do we decide those things? How do we decide what's right? And how do we work together to do this? So, fasten your seat belts. AI is coming whether we're ready or not. And it's not going to fit in your org chart. We need creation, not regulation. And we need leaders to have a powerful mission view of work. And I think we can do this. So thank you.
