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Seminar

AI in practice: applications in industrial OT environments

Onderwerp
Industrial automation

1:00 PM – 2:00 PM

During the AI & Machine Learning seminar, we dive into the world of reliable and responsible AI applications within the industry. Experts and end-users guide you through current trends and challenges, including the risks of hallucinations, data breaches, and compliance regarding the use of Generative AI and Large Language Models. An end-user shares a practical case study on how AI is tested and deployed within an industrial organization, from knowledge sharing to failure analysis. Additionally, you will learn where AI actually adds value to work processes and how to manage risks related to erroneous output and cybersecurity. This session is essential for anyone who wants to get started with AI responsibly and effectively within their organization. 

Slot 1, 13:00 – 13:20:

Growing without hiring: AI agents do your repetitive work 

AI agents changing the way companies work. Not tomorrow, now. No chatbots, but digital colleagues who reason, act, and learn. Fully autonomous, within your existing systems. They take over the repetitive work that needs to be done but gives no one energy: drafting quotes, processing orders, invoicing, planning. This way, you grow without hiring extra people, creating space again to truly do business. In this keynote leave Merwin de Jongh shows with concrete SME case studies what AI agents delivers results today, and how you take the first step yourself.

 

Speaker: Merwin de Jongh, Founder Repetitive.ai  

 

Slot 2, 13:20 – 13:40

Responsible AI Needs Reliable Access to Company Knowledge (SCARY)

This seminar explores a core requirement for responsible AI adoption in industry: reliable access to the right company knowledge. In practice, the quality of AI outcomes often depends less on the model alone and more on whether information is accurate, current, traceable, and available in the right context. For industrial organizations, this raises important questions around data quality, source transparency, access rights, governance, and human oversight. The session will show why these foundations are essential for trustworthy AI in engineering, manufacturing, and operational settings. Rather than treating AI as a standalone technology, it offers a practical view of AI as part of a broader knowledge and process landscape. Attendees will gain a framework for understanding how better knowledge access improves reliability, reduces risk, and supports more responsible use of AI in real business environments. 

 

Presenter: Bastian maiworm, Co-founder Amberroad AI 

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