AI’s impact: Transforming industries and empowering humans
“The combination of human expertise and the right technology has always been the key to success in manufacturing,” says Dominik Wee, Corporate Vice President (CVP) of Industry Solutions Engineering at Microsoft who is today’s guest of AI at Scale podcast hosted by Gosia Gorska.
Dominik shares his experience in transforming large organizations in the digital age, discussing the integration of hardware and software. Furthermore, he talks about the profound influence of AI on various industries and the democratization of technology.
The Microsoft CVP explains how AI is revolutionizing sectors like automotive, manufacturing, and customer service. Moreover, he talks about the critical role AI tools play in augmenting human capabilities rather than replacing them.
Dominik Wee emphasizes the importance of human-machine collaboration in complex, high-skill environments and shares fascinating examples of generative AI’s transformative power.
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Transcript
Gosia Gorska:
Welcome back to the AI at Scale Podcast. My name is Gosia Gorska, and today I am hosting Dominik Wee from Microsoft. He is an experienced global business leader focused on transforming large organizations in the digital age. The key theme for him is bringing together two formerly separate hardware and software, digital and analog, scale and agility. Having lived and worked in Silicon Valley as well as in several cities across Europe, he has gained an appreciation for these fields. Dominik combines his passion for technology and background in computer science with many years of experience in driving change in large, complex organizations with over a century of heritage. So, what are these organizations? He spent 16 years at McKinsey, where he built McKinsey’s digital practice for automotive and industrial clients. He spent four years at Google as Managing Director, Global Automotive, Manufacturing, and Energy. For the last two years, he was leading the manufacturing and mobility organization at Microsoft and is currently the CVP of Industry Solutions Engineering. Welcome, Dominik.
Dominik Wee:
Thanks so much for having me, Gosia.
The Role of AI in Democratizing Technology
Gosia:
And congratulations on your successful career with Microsoft. Last time we met at Hannover, you were the CVP for Manufacturing and Mobility, and as we meet today, you’ve been appointed as the CVP of Industry Solutions Engineering. My first question is looking back at your experience and impressive career: can you walk us through how the industry was changing along axes like hardware versus software, digital versus analog, and how AI influenced this journey?
Dominik:
Great question, thank you, Gosia. I think the biggest change overall is how we are seeing access to complicated technology getting easier. Sometimes we talk about democratizing technology. When I started out my career, I did industrial engineering work as a consultant in semiconductor fabs. We worked on these extremely expensive lithography machines, which are some of the most sophisticated pieces of equipment for making cutting-edge semiconductor chips. Back then, it took a lot of highly specialized expertise to do this work, getting data out and drawing any insights. That has dramatically changed in the 20 years since. A lot of technology has become much easier to use. There’s also some work we’ll talk about later, between Schneider and Microsoft, where I think a lot of things that required PhD-level expertise in the past can now be done by technically savvy people. We’re still in the middle of that journey, and now with generative AI, we’re going to see a lot more of these systems becoming much easier to access.
But I think at the same time, there are also some things that haven’t changed at all. I recall back then, being in the semiconductor fab, one of the key factors for getting real results for the business—usually getting more chips out or improving quality or reducing costs—was getting the technology to work and having the people work with the technology.
Gosia:
Right.
Dominik:
It was always the combination of the two. You could have the greatest system, the most sophisticated algorithms, but you wouldn’t see any change on the shop floor unless the people actually used them. If you’re working with capable people but don’t give them the right technology, it’s also inefficient. So, it’s always been about the combination of the two—the human and the machine working together. And that hasn’t changed until today. That’s why Microsoft uses the term “copilot,” not autopilot.
Gosia:
Okay.
Dominik:
Because we strongly believe that AI doesn’t replace humans; it augments the human experience. It’s a tool in the same way that tools have always augmented the way humans work.
Generative AI Revolutionizing Customer Interactions
Gosia:
Yes, that’s a very nice observation. And it makes me think about other areas, like you mentioned in industry and manufacturing. We also say similar things about composing music. In the past, it was only possible for composers, but now, with generative AI tools, anyone can easily create a song. So if this works the same way with Copilot for the usage of technology, it will indeed become much easier and more democratized. Looking back, some of our podcast guests have already explained how AI can greatly optimize various processes. I was wondering, looking at your experience in McKinsey, Google, and Microsoft, could you share some examples that impressed you the most? Whether due to their unexpected outcomes or particularly innovative approaches?
Dominik:
Right now, the piece that is really mind-blowing is how generative AI can improve customer interactions. I think this is mainly for businesses in the B2C space, but it’s also extending into B2B. For example, we’re working with an airline that’s built a chatbot to talk to their customers and enable them to book flights. We’ve all had those clunky chatbot experiences in the past, right? They’ve been very unsatisfying. But now, things have dramatically changed. The experience is now similar to a ChatGPT conversation, with the ability to actually interact with the airline and access their booking engine. These experiences are incredibly easy to build now. We have this tool at Microsoft called Copilot Studio, which lets you create chatbots just by clicking on a user interface and using natural language. This makes it very easy for companies to improve their customer interface, increasing customer satisfaction while also reducing costs. We’re also working with Lufthansa on the backend, processing claims from customers in their call center. This is one area where AI is having a natural impact.
Gosia:
I wanted to comment that this is probably why we’re seeing such great adoption of these tools. Compared to other platforms and tools in the past, we never witnessed such fast adoption within the first days and weeks of ChatGPT, for example, because it’s so easy to use for everyone. And now that we can access data from machines and software through the same natural language interface, this is truly a great experience for employees and makes everything much easier, right?
Dominik:
Totally. And I think it’s fascinating. We now have the ability to create chatbots using natural language. You use natural language to create natural language chatbots. We also now use large language models (LLMs) to quality control new models. So, it’s AI building AI. All of this is making things a lot easier. We’re also seeing these changes. We’re working on complex engineered systems with companies like yours—providing complex electrical systems to customers. We see this with car design and even with fighter jets. These products take years to develop because of the complexity and regulation involved. If you’re designing a car, for example, you have to meet dozens of different regulations. Now, imagine feeding all those requirements into an LLM and having it handle regulatory compliance checking. That’s a use case we see in the pharma industry too—medical compliance checking. It’s a similar situation for complex industrial goods that might be subject to export controls.
Gosia:
Right.
Dominik:
Depending on the product and the country, if you’re making sophisticated machinery, you might not be able to export the same product due to export controls. These are all use cases where we can now use LLMs to significantly accelerate the development process.
Gosia:
Yes, and speaking of ease of use, you mentioned PLC code generation and Copilot, a solution showcased at Hannover MSA 2024. It assists software developers in writing code for industrial computers. It helps to write code in a shorter time, and because it’s based on our internal documentation, the code can be trusted. But what really struck me about this solution is the educational element, which I hadn’t considered. Along with code suggestions, the developer gets the source of information and can understand why the code is changing a particular machine setting. From your perspective, how crucial is AI-assisted learning for manufacturing companies?
Dominik:
I’m really excited about the work we’re doing with the PLC code generation Copilot because it takes the capability of writing mainstream software in Python or C and applies it to the very specific domain of PLC programming, which has a limited number of experts globally. Now, all of a sudden, everyone with a technical understanding can program a PLC. The learning aspect is really what blows my mind. I remember learning programming years ago, and it was difficult—it required a lot of dedication, heavy textbooks, and trial and error. But now, my daughter came to me and said, “I learned programming by making a game in Roblox using ChatGPT.” This same capability is now available in the PLC code generation Copilot. It doesn’t just tell you what to do—it explains what it does. And if you make a mistake, it tells you what the mistake was and how to do it better. It’s like having the perfect teacher, infinitely patient, and you never have to feel embarrassed asking questions.
Challenges that can be solved with AI
Gosia:
Right, and it also addresses the challenge we hear from our customers about the lack of a skilled workforce. They don’t have enough software developers to reprogram PLCs based on changing customer demands. Do you see other challenges like this that are important and could also be solved with AI?
Dominik:
Yes, I think the labor shortage topic is huge and quite universal now, especially in places like Japan, where a large portion of the workforce is over 60 years old. We’re running out of labor, and in some domains, we’re running out of educated labor or highly skilled workers. There are certain industries where humans prefer not to work, like on oil rigs or in mines. These jobs are very harsh and dangerous for people. I believe AI can make a real difference in these environments, enabling more people to do more without requiring years of specialized training.
Future of intelligent manufacturing
Gosia:
It’s hard to imagine that people aren’t interested in these types of jobs. I recently attended a conference where one of the directors for a services company mentioned they opened a position, and for an entire month, nobody applied. That really shows the workforce and skills gap many companies are struggling to fill. But let’s focus on the positive: How do you envision the future of connected and intelligent manufacturing, and how is Microsoft shaping this vision?
Dominik:
I think we are just at the beginning of that journey. There is still a lot of room for traditional AI, like classic machine learning. I visited an auto plant recently, and they’ve made a lot of progress in training machine vision models to do quality control on the shop floor. They started with spotting one type of mistake in one part of the manufacturing process, and now they have cameras all over the place. But there’s still a lot of runway for improvement. As we move into generative AI, we’re really just seeing the tip of the iceberg. The systems we’re building today are essentially wrapping around the current way a company works, making it more accessible. But if you fundamentally rethink how a company operates, especially using technology like generative AI, that’s going to change everything. That’s why the transformation is going to take some time.
Gosia:
Right.
Dominik:
The pace of technology development is insane. It’s impossible to keep up with it. But bringing it into action in a large company, with hundreds of factories around the world, there’s only so fast you can roll out technology. Humans also need time to adopt it and feel comfortable using it. We shouldn’t underestimate that part.
Gosia:
In the end, it’s the old truth that digital transformation never ends. It’s a journey, not something you can do once and then forget about. It looks like it’s a continuous journey for all companies. As you said, some investment has already been made, and we see many of our customers already sorting out the data elements necessary to use AI. In the future, as you mentioned, we may see entire processes changing, including how customers interact with companies. Perhaps customer expectations will speed up the pace of change within businesses.
Dominik:
Yes, for sure. It’s going to put pressure on the competition. I think that’s definitely going to happen, and a lot of the competitive differentiation will depend on how well companies can make use of this technology.
Usage of AI as a CVP
Gosia:
Okay, I wanted to ask you two questions about your current role as CVP of Industry Solutions Engineering. How do you plan to apply AI in this role?
Dominik:
You mean for myself or for the company?
Gosia:
For yourself or the company.
Dominik:
We are a software development organization, so we should be at the cutting edge of what’s happening in the tech space. Software development has really been the proving ground for generative AI technology. For example, GitHub Copilot was the first generative AI product, probably with a two-year lead before ChatGPT came out. It’s the mother of all use cases for generative AI—writing software code. We are now in preview with GitHub Copilot Workspaces, where AI supports the entire end-to-end software engineering process, not just the coding part. And I think this same concept will come to PLC engineering as well—getting AI support for the entire engineering lifecycle, not just coding. This is hugely impacting our own organization. We’re undergoing one of the deepest transformations we’ve seen in a long time. We have our own change management to do, using this technology and adjusting the way we work.
How to stay ahead of innovations in AI and technology ?
Gosia:
That’s really amazing. In the face of such big change, how do you personally stay ahead of innovations in AI and technology?
Dominik:
I like to ask that question too, and I haven’t found a satisfactory answer yet. The way I’ve found to stay on top of things is by carving out time to learn more than I did in the past. I get tutoring to stay updated. But even with that, there’s no way to keep up with everything, so I rely on people around me. That’s why we operate as teams. People specialize in different parts of the technology, and it really comes down to building a strong team around you.
Gosia:
Right?
Dominik:
And then everything else will come.
Gosia:
Yes, exactly. And I think that’s the point. Even though you studied computer science, the technology available back then is no longer the same as it is today. It’s changing at such a fast pace. I also carve out time for learning, reading, and following people who talk about the newest advancements. What’s amazing is that we’re living in a time when a lot of AI researchers are still alive and active on social media. You can follow them, ask questions, and feel involved in shaping the future of technology. As you mentioned, Microsoft views AI as a copilot, not an autopilot. This is an important message for anyone who is maybe intimidated by the rapid changes ahead. Now is the best time to engage, learn about it, and start shaping it.
Dominik:
I fully agree. It’s exciting to be part of all this as it plays out in real time. It’s like a good movie—except we’re right in the middle of it.
Wrap up
Gosia:
Yes, exactly. Thank you so much for your time today, Dominik. I really appreciate you answering all the questions and spending time with our listeners.
Dominik:
Thank you, Gosia, for having me. It’s been a pleasure talking with you.
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