AI in Engineering
EVP Managing Director, Capgemini Engineering Germany / VP Technology and Innovation, Capgemini Engineering
The introduction of chat applications, known as large language models, has given the topic of artificial intelligence a dramatic boost in public perception. Topics that were previously discussed almost exclusively in technology departments are now literally being discussed around the kitchen table. No sector or industry can afford to ignore this potential. Not only is it important to emphasise the benefits of AI for the end user, but we all need to understand how advances in intelligent assistants will impact product architecture, engineering, and manufacturing.
How AI will affect our future
There is no doubt that we are at the beginning of another industrial, perhaps even social, revolution. Rapid advances in algorithms, such as the introduction of so-called transformer models in 2017, or the dramatic increase in computing power for AI tasks, which has increased by a factor of 1000 in recent years, have opened the door to new applications.
We have all seen the improvement in the quality of tasks such as machine translation, or the almost magical progress of large language models – such as the intelligent processing of text, images, diagrams or even video. This goes beyond simple summarisation and rudimentary understanding of existing information! Generative AI can be used to create new content. For example, sales, marketing, communications, and service are already using these technologies to automatically prepare information for individual customers.
A quantum leap for product developers and production managers
Although the topic of AI, or GenAI, has become a real hype, the Capgemini Group has been working on the technology, the applications and the successful implementation of machine learning, deep learning, and AI in companies for many years. In particular, Capgemini Engineering stands for the sensible use of this technology in the product itself – a core task of engineering.
We are already seeing significant impact in all areas of product development. For example, the design process is significantly accelerated by generative AI, which can not only create design variations, but also optimise them according to specific criteria. Digital engineering support systems, such as Capgemini’s AIDA technology, give engineers »superpowers« through the safe, traceable, and accurate preparation and delivery of large amounts of information such as specifications, technical guidelines, or approval regulations. Validation platforms, such as those used to validate systems for highly automated driving, benefit enormously from synthetically generated training data, which reach new levels of fidelity and scenario diversity with the help of generative AI. Capgemini is working on this today.
Silent revolution on the factory floor
The impact on factory planning and production methods is also immense. It starts with even more detailed digital twins that are able to simulate systems and processes with high precision, process large volumes of operational data to identify relevant patterns at an early stage with the help of AI and propose solutions. This enables more efficient, sustainable, and resilient production. Capgemini is at the forefront of this, with its own research and projects already implemented in the area of software-defined factories, also known as gigafactories. For Capgemini, these applications of artificial intelligence are not optional, but mandatory. If we think, for example, of the battery factories that have yet to be built in Europe, we will only be able to compete here if we can guarantee the highest levels of efficiency, quality, and sustainability. In addition to the use of digitalisation and optimisation in production, there is undoubtedly great potential in production automation.
Will intelligent robots soon take over the assembly line?
The unmanned factory – machines building machines – is a popular image. However, it is doubtful that this will be the fastest, most efficient, and therefore most desirable solution in the near future. In our view, the big advances in robotics will be driven by artificial intelligence. This means that machines will not only have vastly improved perception thanks to these technologies but will also be able to collaborate with humans in new ways. This also includes the way in which such machine helpers are trained. Instead of complex programming, we will practise and experience »social-cognitive learning«. This applies not only to classic forms of robotics, but also to more exotic designs such as humanoid robots.
From science fiction to tangible business applications
On the one hand, the possibilities of generative artificial intelligence seem promising, almost magical. And companies have no shortage of ideas for using these technologies. On the other hand, we see great difficulties in the market to implement value-adding prototypes, to improve them quickly and to industrialise their use. Some companies are simply overwhelmed by the pace of development in this area and the need to be realistic about the potential benefits of these tools. Capgemini believes that waiting is not an option. Especially for companies in mature markets, there is an urgent need to see AI not just as an add-on to product functionality, but as a key tool to make their own value chain more efficient, sustainable, and faster.
In particular, Capgemini Engineering stands for the sensible use of this technology in the product itself – a core task of engineering.
Artificial intelligence – euphoria meets doubt
Even if the focus is always on a beneficial technical application, aspects of ethics, data protection and the objectivity of AI models are extremely important components for the successful introduction of AI in companies. Europe and Germany are already setting standards with regulatory guidelines such as the AI Act – or very industry-specific laws on automated driving. This creates certainty for companies.
Capgemini’s specific approach to AI
The breadth of the Capgemini Group and the unique benefits we can offer our clients become clear when we look at the challenges and potential of AI. The Capgemini AI Framework provides a structured approach to introducing artificial intelligence into the business, identifying useful applications, and moving quickly from prototype to production. At the same time, we and the engineering team are committed to building AI capabilities into the product and into the development and production process. Whether it is accelerating the validation of highly automated driving systems using AI, identifying active ingredients for innovative medicines more efficiently, or increasing the production yield of battery cell lines: Our engineers help our clients every day. Capgemini combines traditional engineering expertise and domain knowledge with a deep understanding of edge, cloud, and data science.
