What exactly do you do with generative AI at Capgemini?

Jeroen: “Marijn is managing data scientist, I’m managing machine learning engineer. Simply put, Marijn thinks in terms of problems and possible solutions and I think in terms of the platform: how will the client be working with the solution once it’s in place? Together, we make sure that the client is ready to implement the latest technologies and philosophies, and thereby to offer personalised experiences to customers, automate tasks and help take better decisions.”

How do you convince clients of the power of generative AI?

Jeroen: “We don’t really have to do that, actually. Clients read about what’s possible with AI in the news every day, or they experience AI functionality themselves as consumers. Everybody understands what a chatbot is, and the capabilities of ChatGPT. That makes it easy to talk to clients about these things.”

“Completion, however, is a whole different story and requires many competencies, so it’s great that we have them all in-house here at Capgemini. From people who lay the foundations – systems, architecture, software – to people who see to it that the front end looks attractive and is user friendly. And let’s not forget the people who understand the ethics; know how far we can go and what, perhaps, is better to be avoided. Our service is truly end-to-end.”

How do you make the business opportunities generative AI holds clear?

Marijn: “With tangible examples. Our teams build cool demos that we can take to the client and say, ‘Look, this thing writes code itself and then analyses the data for you. Want to give it a go? Ask it a question.’ After that, it’s just a matter of discussing how their company would change if they had such a thing.”

Jeroen: “A good example is the automated business analyst for a fictitious health-care centre. To produce a report, they would need a business analyst who might spend hours, or sometimes even days, going through the database. Using the demo, a staff member simply uses a chat interface to ask how many patients with allergies doctors have seen in the past month. The platform subsequently generates a query to retrieve the relevant data and executes it. What actually goes on at the back is extraordinary. Unstructured data – from notes taken during patient consultations to call-centre transcripts – are automatically structured and organised into the correct answer. That’s truly groundbreaking.”

Marijn: “We also tell clients about FARM, a collection of projects in which we put generative AI to work for smallholder farmers all over the world. Many of these farmers live in poverty, but together they account for a third of global food production. We help them improve harvests through technology, such as an app with which farmers can identify plant diseases by simply taking a photograph. The app subsequently offers advice on how to combat the disease and warns other farmers in the area of its presence.”

“Through the development of demos, we help our clients forward and keep ourselves on our toes. Sure, courses are a good thing for an AI specialist to do, but I like to encourage my teams to simply start building and see what happens. How hot does the CPU get with this solution? How much can the cloud handle? What are the consequences in terms of privacy? You’ll never actually know until you try things out.’

In addition to the advantages of generative AI, you also read in the news about dilemmas relating to matters such as privacy. What are you doing to address such concerns?

Jeroen: “We’re very switched on to all the relevant ethical considerations and we actively discuss them with clients right from the very beginning of the development phase. Everybody at Capgemini is fully aware of just how important these issues are and they are a regular topic of critical debate among colleagues throughout the organisation, always centred around the question: How do we ensure that what we’re doing is right? It’s an honour for me to be able to contribute to an ethical way of working with AI.”

What is it about Capgemini that makes it interesting for you to do this work here as opposed to elsewhere?

Marijn: “The variety. To begin with, I’m always working on something new. One minute I’ll be analysing burnouts and the next a chatbot. And there’s a constant stream of new projects in all kinds of different sectors – from public to private, from retail to NGO. That keeps things exciting.”

“Also, there are data specialists here with very different backgrounds. Mathematicians, psychologists, astronomers – people with unique perspectives who when they put their heads together come up with better solutions. That is the key strength of Capgemini, and one of the reasons I like working here so much.”

Jeroen: “In addition to data experts, Capgemini employs myriad other specialists. I work in the back end, but if a client comes along with an enquiry about, say, a graphical interface at the front end, then I’ll always know just the right colleague to look into the matter. When I visit clients, therefore, I bring with me much more than just my own expertise.”

“Finally, the whole way of working here teaches me a lot. Our learning community consists of peers with whom I exchange experiences on the one hand, and on the other I learn tremendously from all the specialists in their respective disciplines. Capgemini enables me to exceed myself as an AI specialist.”

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