Industrial AI Conference
Around 200 participants came to Frankfurt on January 22 to find out about current developments in the field of AI in industry. The Industrial AI conference kicked off with a keynote speech by Rich Walker, CEO of the Shadow Robot Company, who presented a robotic hand that manages to imitate the kinematics and dexterity of the human hand as accurately as possible.
Industrial AI Conference
BUSINESS – ENGINEERING – DEEP TECH
Speakers 2025
Speakers
In product management for the TwinCAT automation solution, Dr. Fabian Bause deals with the integration of machine learning processes into industrial automation. This includes infrastructure components in hardware and software that allow AI to be integrated into the PLC environment, components for the distribution and management of AI models on machine controllers and LLMs to support machine programmers in their daily work.
Tom Cadera studied industrial design at the Braunschweig University of Art. Even during his studies, he worked for companies in the medical technology and mechanical engineering sectors. In 1992, he founded CaderaDesign and specialized in the interface between people and highly complex technology. CaderaDesign was one of the first design agencies to conceive and design software interfaces, thus doing pioneering work in the field of user interface design.
Today, CaderaDesign GmbH is a leader in the field of user experience design for mechanical engineering and industry. An important focus is on the overall user experience of products, combining HMI design and industrial design.
With numerous projects, Tom and his team are also pioneers in IIoT topics for digitalization projects in the production environment. Particularly in industry and especially in critical areas (e.g. healthcare), they have been working for some time on using Explainable AI (XAI) to create the necessary transparency to build long-term trust in the technology. The focus is always on the human being.
UX AND INDUSTRIAL AI
Predictive maintenance, data-driven process optimization or optical quality control – industry is already relying on AI support in many areas. The development is so rapid that more and more possibilities are emerging for optimizing processes with the help of AI. It can be assumed that the use of AI systems will expand to even more business areas in the future. In this context, it is becoming increasingly important that companies not only use AI, but are also able to understand how it works and the criteria on which its decisions are based – a requirement that will become mandatory with the upcoming EU AI Act. This is precisely where Explainable AI (XAI) comes in, with the aim of opening up black box systems and making them transparent. As user experience experts, we also come into play and have to ask ourselves the same questions as always: Who interacts with the AI? What is the technical background of the users? Which explanations do they need at which point in the system? When it comes to AI, the perspective of data analysts and AI experts alone must not be decisive – user research is also required here. A human-centered approach will be required to create lasting acceptance and build trust in the use of AI. This article aims to demonstrate the importance of XAI. With our case study, we present how qualitative feedback from experts in the fields of AI and UX was collected using a click dummy to develop initial design guidelines for XAI. The click dummy makes the new challenges of XAI tangible and enables innovative solutions to be experienced. Finally, we jointly address the question of the limits of XAI and how we can counter them. The article is intended to encourage a human-centered approach to future AI use cases from the outset, thus making a decisive contribution to the development of next-gen UX solutions.
Studied Cognitive Psychology and Sociology with a focus on statistical methods in Oldenburg and Northern Ireland to start as employee in the role of a statistician in diverse industries. Being a self-employed consultant for the usage of analytics in enterprise applications for more than ten years he integrated his former company dsquare.de into Cognizant Germany in 2013. In 2017 he entered Continental tires to build up the topic of data science. Today he is Head of Applied Analytics and AI at Continental Tires.
Title: AI in construction - tools and approaches
"Agentic Automation for mission-critical processes: how to add RELIABILITY & CONTROL?!“
Christian is founder and CEO of embraceable Technology GmbH, a European Research & Development company that is specialized in LLM-powered Agentic Systems, with a particular focus on safety and reliability of these systems. With Senior-Level IT-Management background in international Investment-Banking, he has a deep and long-standing experience in designing and operating reliable, mission-critical systems.
Deputy Head of the Institute, holder of the Chair of Cognitive Production Systems
Institute for Industrial Manufacturing and Factory Operation
Lecture title: AutoML for TimeSeries
Keynote: "Rethinking efficiency and cost savings: How GenAI chatbots increase productivity"
Coskun Islam is an expert in manufacturing engineering specializing in machining with a focus on digital transformation in the manufacturing industry. He hold a Ph.D. in Mechanical Engineering from the University of British Columbia, with a strong academic background. Currently, Coskun serves as the Head of Collective Intelligence Engineering at Sandvik Manufacturing Solutions. In this role, he collaborates with different business units to enhance digital manufacturing.
As Director Solutions Architects at German Edge Cloud / Friedhelm Loh Group, Plamen Kiradjiev is responsible for the sustainable realization of digitalization in manufacturing. Plamen's focus is on the step-by-step introduction of shop floor IT, which can lay the foundation for the next decade with technologies such as micro-services, hybrid cloud and AI. He builds on 29 years IT experience, 11 of them in manufacturing and Industry 4.0.
Magnus possesses a rare blend of sharpness in seamlessly integrating digital technology with sound business strategies and commercial acumen. This results in a unique skill set that enables him to consistently deliver results.
Magnus thrives in higher-paced environments, adept at connecting the dots to facilitate transformation and ensuring everyone involved evolves and grows throughout the journey. Today, he finds himself immersed in the exciting product space of digital transformation in manufacturing, working towards the vision of autonomous and sustainable manufacturing.
Jan R. Seyler, Director Advanced Development Analytics and Control bei Festo at Festo SE & Co. KG, is passionate about robotics and artificial intelligence. With over 7.5 years at Festo, he has significantly contributed to AI and control systems in automation. Seyler also lectures in Applied AI at HS Esslingen and IoT at DHBW Stuttgart, sharing his passion for technology and innovation. He actively contributes to the academic community e.g. by chairing the IAAI - the biggest conference for deployed AI solutions.”
Sascha Steinkrauß is the owner of the company 4S, with which he offers services relating to the CE conformity of machines. He already dealt with the Machinery Directive during his Bachelor's degree in Mechatronics / Robotics in 2009 and added trustworthy AI to his part-time Master's degree in 2021. As a part-time lecturer at FH Campus 02 and as a member of the AUVA Machinery Safety Platform in Austria, he shares his expertise on several levels.
His lecture will focus on new requirements of the Machinery Ordinance and the AI Ordinance as well as the risk assessment of AI systems in machines.
Title: Risk assessment of AI systems in machines - requirements in the EU
Industrializing AI: Building an End-to-End Platform for Agriculture and Manufacturing
Adopting AI in industrial settings like agriculture and manufacturing presents unique challenges—from selecting the right algorithms and deep learning frameworks to data collection, annotation, and deploying models on embedded hardware. In this presentation, we share our journey in tackling these issues and how we developed a comprehensive platform architecture that addresses them holistically. We'll discuss integrating model monitoring and retraining functions, managing data and model versioning, and enhancing the effectiveness of our AI engineers in executing projects. Join us to discover practical strategies for industrializing AI and optimizing your organization's AI initiatives.
Managing Director Shadow Robot Company
Titel: Developing new robots for AI to use - the outcomes of a multi-year collaboration between Shadow Robot and Google DeepMind
Zeki sprang from the need to know with absolute certainty. Co-founder Tom Hurd served in senior intelligence roles in the UK government for decades and knows firsthand the critical need for accurate data in measuring risk and opportunity. Together with his Margaux Bergen Tom founded Zeki to address the data knowledge gap that persists across deep tech—identifying the precise innovators capable of creating tomorrow’s innovation.
Depth and accuracy are hallmarks of Zeki’s proprietary data—over 10 million deep tech scientists, engineers and researchers working at more than 40,000 companies. Zeki evaluates each individual and organisation against over 20 indicators, ranks them and assigns them a Zeki score. The higher the Zeki score, the greater the innovative potential of a specific person or company.
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