Introduction

Good evening. My name is Renan Grandu. I'm very glad to be with you today.

I am a Senior Manager of Global Artificial Intelligence Partnerships at Linde. I have been working several countries along 10 years of my career.

I'm originally from Brazil, but I've also been studying England, Germany, Sweden, Portugal, Thailand as well, actually. And I have started working at Linde since 2018 in Munich, Germany, which is one of our headquarters.

And two years ago, I moved to Lisbon to set up a new office, which is part of our global AI hub.

So far, we have 12 people as part of this team. And we're also expanding other locations, other countries.

Overview of Linde and AI Integration

Today, I'm going to talk to you about how AI and global talents are redefining life and business. And to start with, let me talk about Linde first.

So Linde is a leading, I'll actually make this mix of the words also, so a leading industrial gas and engineering company. It's a 65,000 people worldwide. We have had last year a revenue of 30 billion US dollars.

And we are basically everywhere, right? In the invisible gases, all the way from freezing the pizza or the shrimp you buy in the supermarkets to welding the metals that manufacture your cars, or adding the bubbles to your carbonated drinks, the sodas, or even propelling rockets to space. So it's pretty wide applications and markets that we have, even though it's an invisible product.

AI in Linde's Operations

But what AI has to do with this, and how are we applying AI at Linde? We apply AI along the entire value chain, so all the way from the production plants that we have, our air separation units, for example, where we extract atmospheric gas and produce these gases to deliver, also in our distribution, and also all the way to the customer.

We have, as I said, in this part of global AI hubs, a global talent pool, and we are capable to develop end-to-end AI products. We are about 50 to 60 people now worldwide.

However, we also are able to partner with cutting-edge technology providers in order to make sure we don't reinvent the wheel, right? So we take advantage of all of these types of developments.

We always start small, agile, and then once the product is ready and it's valuable, we scale up to other countries.

Innovative AI Products

So let me show you a few products that we are developing today in the AI space. First of all, I'm talking about Power Optimizer.

Here's one thing we've developed. We have huge industrial plants, and one of our major cost drivers is definitely electricity or energy. 1And what Power Optimizer does, it optimizes the energy consumption of our industrial plants.

So it basically leverages the plant flexibility, how it can turn on, also looks into different market prices for energy, and makes sure that we buy it more affordable, and also our customers have also the supply in a reliable manner.

This is also a very good potential strategy that we have to leverage energy sources that are not provided in a consistent way. So renewable energy sources, for example, like wind and solar, we don't have a consistent supply for them. And in this case, we are able to make it reliable when the energy of these sources is abundant and available.

Another project that we have, I'm talking about production, I'm talking about distribution, is Driver Companion. So Driver Companion measures, evaluates the driver and their behavior, looks at fuel consumption, environmental factors, and other conditions, actually gamification in a way, because the driver has an app to evaluate his or her own score.

And it increases the safety because it looks at also the journey, the route that this driver takes. It looks at environmental conditions, as I mentioned, but also the fuel consumption.

So we reduce our costs and increase the safety of our drivers. So this is in the distribution side.

A last example that I would like to share with you is in the home care operations here in Portugal. We have a significant home care business. It's very strong here by the SNS, which is the local public health care provider.

patients at home with sleep disorders, specifically apnea, sleep apnea. And what we do here is that some of the patients, they fall out of compliance for diverse reasons, right? So maybe the mask is uncomfortable when they're breathing. Maybe they just don't like the smell of the cables. Maybe they're just not used to it.

And what we do is that with also an AI model, we're able to predict when a patient is going to fall out of compliance based on historic behavior and also other profiles that we get for the patient. In this way, we are able to intervene a little bit earlier before this patient actually falls out.

And this has already proven, we've done some tests in France, it has improved the compliance rate of our patients. It improves the life condition for the patient, for the treatment, because they're going to be sticking to that. Also, it's good for us as a business because it increases the usage as the patient sticks to therapy.

The Impact of AI on Work and Skills

So, I've been talking about all of these examples, but let me go back a little bit and talk about how the global talent and AI actually shaping business, not only business like us, because we're not the only one transformative and transforming our solution, but also everyday life everywhere. So far, we have been working 40 hours jobs, right? Four-year degrees we've been studying, and also we have had four decades careers to then retire.

pretty much standard after the industrial era, and we have seen so much transforming, most likely in the last years due to COVID and other factors, but I am a big believer that AI is definitely also boosting that reality and that change. AI is definitely reshaping the nature of our work, also the lifespan of our skills and how we learn and also prepare to our careers.

It's definitely beyond the hype, right? We have had, I mean, skills are being demanded up. If you look for LinkedIn in the past years, 50% to 60% of AI skills are increasing, even though the job loads are not very clear. Sometimes even us, as recruiters, we don't know exactly what actually we're looking for. And sometimes we're just looking for a profession that has different skills.

And I'm going to talk about that in a second. But it's definitely beyond the hype. If you think about it, we've never had computing power costing so low.

We have never had so much sensors, also costing so low, an IoT sensor where you can gather this data. The access to AI is very democratized. Anyone, you have just seen now, Sony images of someone that can just, an architect that can use it also in different ways.

And... We definitely think this is transforming the way we collaborate, we work, and the way we live, right?

The thing is, this technical knowledge, this technical expertise is not enough. 1It needs to be scalable, and we do need collaborative skills, especially like a company like Linde, 65,000 people. We have footprint worldwide. So we need to be very collaborative in order for AI to make sure to stay relevant across markets.

It also relates to empowering productivity of us as individuals, right? And because of that, of all that I'm saying, I think that we are just entering a kind of new rules of engagement. The rules of the game is changing. The way we work changes, as I said.

New Rules of Engagement

And let me talk about what I mean by new rules of engagement. So this teams of teams term, I'm not sure if any of you has heard of that, was coined by General McChrystal. In the context of military operations in the US, it's a book he has written.

It's basically shifting from traditional command structures, which is very good for industry with steady supply, with very predictable production lines, but does struggle to adapt when things are a bit changing or you need to implement new decisions. As we have had digital technologies or agile methodologies came into place, we've had lots of cross-functional teams coming into place, which is also the reality today, mostly.

In most of the companies, we have this exchange between different teams. But as we need even more this need for adaptability, as the world is changing fast, also skills are changing very fast, the tech stacks that some of you guys are learning, also are changing depending on the decade, depending on the big tech that is on top. We will be needing these teams of teams more and more.

Let me give you an example. Think about a hospital, right? When a patient arrives seeking urgent or emergency care, the whole team, there's a doctor, there's a nurse, there's technicians who are going to be around this patient. There's no time to just ask the director of the hospital whether or not they're going to perform a procedure, right? So think about that.

That's the direction large organizations are going, specifically also in digital AI setup, but also in more traditional setups. We're going to be able to make decisions much faster in teams that are completely interconnected. I talk to my colleagues in India, in Australia, in Brazil, in the US all the time, every day. And this is how we are deciding things.

There is no time. sometimes even to think about things. We just have to take action, and we have to be very empowered to take this action forward.

So this is my thesis for, and I really endorse what Mac Christer has written. However, not all of this makes sense.

AI as a Tool for Borderless Collaboration

The teams of teams structure doesn't make sense without the global talent in it, right? So that's where I'm going to also talk about AI as a tool for borderless collaboration.

At Linde, we do this by collaborating with different teams in different countries. Again, in order to stay relevant, adaptability is also a key issue.

You're going to see that this is one of the major concerns of companies today when they are looking for a talent, that the talent should be adaptable for these changes that are happening, specifically also in the AI domain. There are too many things happening all the time.

Some colleagues here mentioned the EU AI Act. That's also a big part of this.

Some organizations don't know how Navigate through these compliance and governance structures, but we can we can also talk about that about a moment There are different business needs across landscape so business relationships in Brazil where I'm from or in Japan Europe they're completely different so when we're applying a product definitely the needs of the user will be different and even the way we talk to them and like the conversational comments, which also, I believe, is going to be a big shift.

You mentioned this also in one of your examples. I think the next decade, everything's going to be shifting towards conversational comments, right?

We are more and more talking in the chats or the LLMs that are part just to do everything, right? This is something that any kind of trade will take advantage of.

Most likely, you're going to have an Amazon. You're going to only have chats and talking through it instead of having all the of the front end of the website.

So that's also what I believe. And in this context of adaptation, if you think of a customer relationship in Japan, which needs a much more formality, while in the US, it's a very more direct way.

And you also have to adapt when you're thinking about developing and implementing these AI tools, which is not only for talent, but how the business can Change is definitely not one size fits all. Even though we are global talents, people are all across the world, we have to be aware of the local reality, but also thinking about global trends.

Cutting edge technologies are coming everywhere from different locations, depending on the expertise of the country and the region. And we have to be aware of that so we don't fall out for the competition or for other companies coming.

Maker versus buyer strategy is also super important. Again, we do not need to reinvent the wheel, right?

So sometimes we have teams in-house that we have to develop everything. Also startups, probably some of you are part of here.

But the big techs, dominate the market, right? Google, Applied AI, Microsoft, they are the big players.

Often they cannot compete. However, it is excellence, true excellence, does come from these core teams that we have set up.

From known tech companies, for example, right? Those core teams, they understand the business problem much better, and they can take advantage of the technologies in a much more efficient way.

And sometimes, The latest tech, the latest AI model would not be solving the biggest pain of the company.

Most likely you know that. Yeah, an example, I think I've also given that in contract management in different, depends on if it's in Brazil, if you're looking, analyzing contracts, the model, and the ways you relate to customer will be different in talking about Europe, for example.

Advice for Job Seekers

So advice for employees, job seekers, I've been interviewing I think hundreds, maybe 500, 1,000 people in the last year.

So, yeah, I don't know if, actually, all the time, sometimes job seekers, in a few years, we always think about something. So, as I said, be adaptable, top five demand skills for 69% of hiring managers.

We also have to be aware of the short shelf life of technical knowledge. These two, three years, as I said, tech stacks are changing, even job roles are changing. Now we have no prompt engineers. This hasn't been a reality five years ago.

And something else also, embrace business strategy thinking. This data, 90% of organizations to shift the mentors, a fluid understand of business technology. Again, core business, right? Only understand technology is not enough.

Often we ask the candidates in interviews, right? What would you think AI, how do you think AI is applied in our industry, right? Sometimes the candidate might be an excellent technical student, but they don't understand the nature of our problem. This is a problem, right? Because this is elementary, what are we trying to solve? So you have to embrace the strategic think of the business, so then we stay ahead and you think like the company.

Presentation skills really matter. As these themes of themes become more of a reality, even technical resources will become more empowered to talk to stakeholders.

You have to know how to communicate with people that have no clue and were born in 1950. I don't know which in the case of my industry, we have lots of engineers, very senior, and we have to talk to them in their language for them to understand what's going on, right? So presentation skills really matter for us to convince people that are senior and that are in the non-tech field or not even from the non-tech era. So this age gap is also pretty important.

And join leading non-tech organizations. Most of the talent, they always look like Google, Microsoft, OpenAI, whatever. But there are so much great work in completely non-tech industries like mine, which is a 140-year-old companies, incumbent company doing industrial gas.

So it's not that we're going to innovate or adding a new element in the periodic table or discovering with AI. This is probably going to be pretty difficult. But we do develop very exciting projects and products to improve the efficiency of the company, right? So embrace that and think that these companies also have needs in terms of AI teams.

Ethical Implications of AI

Again, we cannot talk about AI without talking about the ethical implications of it. 85% of AI leaders also agree that this ethics is a top concern, so we always address that.

There are different governance styles across the world. So in the US, you see a more permissionless innovation. They kind of punish the bad actors, while here in Europe with the UAI Act, they're very restrictive compliance rules, especially if you are under the high-risk category. So we need to also adapt to these different styles of governance.

And it's definitely beyond tech. All of this talk is about a system that benefits everyone. That's why the regulations are in place. And we think also they are important for us.

Conclusion

Last but not least, as we navigate this intersection, AI, global talent, and innovation, we should remember that while AI can process a huge amount of information, of data, and mimic human behavior, human cognition, it still cannot fully capture the complexity of our behavior or emotions, right? That's why even as AI is reshaping industries and jobs, the human element, our adaptability, motivations, actually even fears and anxieties is what makes us human and most likely is what makes we, AI actually works for us and not the other way around, right?

So thank you very much.

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