Amrop Germany: How do you see the future of AI tools in your organization and across industries? Do you expect it to have any disruptive effects for your organization, and how do you intend to address or to prevent those?

Daniel Boese: That's a broad question but let me begin by explaining how we've shaped our vision regarding our aspirations and AI ambition. We've humorously stated that we want to use AI as seamlessly as we use Excel today, despite relying too heavily on Excel instead of more professional tools. The key message is the desire for AI usage to be as natural and widespread as Excel within our organization. We envision AI impacting and being applicable across all processes, both internally and in our market offerings, in various forms. Specifically, with Generative AI, there are many applications for ordinary white-collar tasks. For example, if an assistant needs to summarize documents, they can simply pass them to an AI, which then handles most of the task, leaving only the final 20% for manual review. This process doesn't require specialized knowledge and functions as a straightforward tool, presenting numerous potential use cases. Observing young people today illustrates this point well. For instance, my eldest son uses AI so naturally—it’s as ingrained as googling something. He understands both its capabilities and limitations. Just as using the internet enhances efficiency without solving every problem, young people are already integrating AI into their routines naturally, and I believe this trend will permeate the entire white-collar workforce.

Amrop Germany: But on an organizational level progressing towards it won’t be so organic, so to speak.

Daniel Boese: You need to train people on how to use AI effectively, understanding both its capabilities and limitations. While AI will make people more efficient, the improvements may be gradual rather than a huge leap forward, progressively enhancing company efficiency. I am confident that many major IT platforms will integrate AI into their tools. For example, Salesforce has already integrated an AI called Einstein into its CRM system, which aids in analyzing marketing automation data. We can expect more tools to integrate AI seamlessly, so training employees to utilize these features will be crucial. For more complex tasks, companies may need to purchase specific tools or develop solutions in-house. In production, for instance, AI can assist in quality inspection to quickly identify defective parts and correlate issues with production parameters or improve forecasting. This approach will likely involve a combination of off-the-shelf solutions and custom developments. Although this is not rocket-science, it requires significant effort to achieve impactful results. While developing a proof of concept (POC) for AI applications can be straightforward, fully implementing and automating processes is more challenging and could take years. However, if done correctly, AI implementation can lead to the automation of certain tasks and significantly enhance efficiency.

Amrop Germany: But would you expect that it will transform your entire business?

Daniel Boese: No, I don't think we're in that type of business. On the external side, we are integrating AI into our market offerings, but we're focusing on transitioning from a product-based business to a more solutions-oriented one. This is a significant transformation, and AI will play a larger role than before. However, these changes aren't solely driven by the advent of AI. If we take a step back and compare it to industries like media, where AI can radically transform content generation, our business is different. We still produce fans or integrated solutions, and while certain aspects of our industry will evolve, it won't be a radical overhaul of the entire sector.

Amrop Germany: Industries like the media are clearly massively affected.

Daniel Boese: That doesn't mean certain aspects won't change significantly for us too. Take software development, for example. AI can substantially increase efficiency through auto-coding, but it doesn’t change the fundamental need for strategic thinking before writing software. Looking back 20 years, developers coded everything manually, with some libraries available for specific functions. Fast forward to five years ago, Python and other programming languages had vast resources available on platforms like GitHub, allowing developers to integrate existing code rather than write everything from scratch. However, significant thought was still required. Now, we’re advancing even further, shifting more of the 'how' to tools and AI. This evolution emphasizes the importance of understanding what you want to achieve, while AI and other tools handle more of the implementation details.

Amrop Germany: In your view, what leadership competencies, skills do you need or miss in your current leadership team when it comes to AI?

Daniel Boese: That's a good question. I'm not entirely sure whether AI is the big game changer here. Let me try to illustrate my point, and then perhaps approach it from another angle. I believe the key is for leadership teams to be open to whatever technology emerges—embracing it, experimenting with it, and understanding its potential. For example, in the automotive industry, if you dismiss electric vehicles as uninteresting, you risk damaging your business quickly. We've seen instances where industry leaders ignored potential innovations and suffered as a result. This highlights the importance of maintaining an intrinsic mindset open to new possibilities. I'm speaking from an industry perspective, not addressing dramatic changes like those occurring in the media sector. The essence is openness to new ideas and thinking creatively about potential changes. So, my answer would suggest that AI is another aspect of the hype cycle—perhaps a significant one—but it's essential to recognize that many technologies can change industries.

Amrop Germany: But then the question is whether AI is really only another technology on the hype cycle?

Daniel Boese: I believe you could argue that the degree of change AI will bring is more significant than what we're typically accustomed to. This is due to its potential impact on how we work and how business models are structured. In this sense, there is a need for a more comprehensive openness to change, including radical change. Do you need technical capabilities to fully understand what AI is doing? It depends on your leadership level. At the highest levels, maybe one person needs a deeper understanding, but you don't need to be a tech expert to grasp the basics. However, roles like the head of AI or CIO require more in-depth knowledge. The change needed isn't purely technical. To effectively drive and deploy AI initiatives, you must understand the implications on data, systems, and processes. If you’re detached from these foundational aspects of business, you might miss the bigger picture. It's easy to do a proof of concept (POC) and feel modern, but if you look back a year later and nothing has changed, it's likely because the necessary connections weren't made to initiate real change. In summary, you need openness to new technologies, a broad understanding of your business—including data and processes—and strong change-leadership skills. Without these, navigating the future will be challenging.

Amrop Germany: Have you considered hiring a commercial member of the management team who is able to sell AI solutions?

Daniel Boese: To some extent, yes. The management team at lower levels needs to focus on building an organization that sells solutions, which is different from our current approach to selling products. In our case, this is a journey we are already undertaking. It's not just about AI; you could replace 'AI' with 'digital' and the same answer would apply.

Amrop Germany: So, you need somebody on each level, who can take care of that?

Daniel Boese: If it’s selling to the market, then, of course, you’ll need people on the sales side doing that.

Amrop Germany: And when it’s about “selling” within the organization?

Daniel Boese: Well, I think that's what you have a Chief Technology Officer (CTO) for. Of course, you can't do it alone; management is a team sport. Everyone needs to understand and contribute. However, if you're looking for a driving force, it's typically the CTO who would lead these initiatives. Having a CEO who is very vocal about embracing digital and AI makes a big difference compared to not having that support. If you’re too vague or too careful about this, then the organization doesn’t really move.

Amrop Germany: Is your CTO AI-savvy and supporting the AI strategy?

Daniel Boese: Yes. He is new to the company, having joined last December, and he is deeply invested in digital and AI. He fully understands these areas, which is why we hired him—to drive transformation on the product and technology side towards digital and AI. He's a strong ally in this endeavor. 

Amrop Germany: Does your organization use AI tools internally?

Daniel Boese: We're starting to move in that direction with initial pilot programs. Are these fully in production? No. For instance, we have a tool designed to forecast our sales for the next couple of quarters. However, its accuracy can still be questioned, and it takes too long to deliver results because the data organization isn't optimal. Additionally, it doesn't cover the entire world yet. Will we get there? Yes, we're just beginning our journey with AI, so while we are making strides, we're still at the early stages.

Amrop Germany: Have you integrated AI in customer solutions?

Daniel Boese: No, we’re working on it.

Amrop Germany: Have you selected or tested the AI tools? Who is buying/dealing with them? In your opinion, what profiles and experience should these people have?

Daniel Boese: I think it's important to differentiate between two aspects. On the one hand, you have the typical involvement of IT, as they are responsible for procuring tools and developing big platforms further. For example, Microsoft offers Copilot, which is yet another tool within the Microsoft ecosystem. IT departments usually handle the procurement of such tools, and they are frequently bombarded with suggestions on what to purchase. On the other hand, you have the business side, where people are exploring interesting opportunities. To address both aspects, we're establishing an AI Competence Center. This center will oversee certain aspects and collaborate with IT to make joint decisions on what to deploy and develop. As to the kind of profile or experience these people should have, well, it depends. For us, it's IT professionals who need to understand the business aspects as well. While they might not handle every detail themselves, it's essential they collaborate with people who do and have a basic understanding of AI. Additionally, they should be connected to the community to discern whether they're procuring cutting-edge technology or outdated solutions that have already been on the market for a few months (laughs). The speed there is mind boggling.