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A Blueprint for Reliable AI, by Tim Biedenkapp with Inga Glotzbach

Writer: Mark MillerMark Miller

Updated: 5 days ago



Artificial (Un)Intelligence Conference, with Tim Biedenkapp
Tim Biedenkapp

As the Director of Information and AI at adorsys, Tim brings a visionary approach to enterprise architecture and data governance. His expertise lies in designing strategic frameworks that enable organizations to unlock the full potential of their data assets. Tim’s leadership is rooted in a deep understanding of the symbiotic relationship between information and innovation.


Tim is presenting his session, streaming live from Frankfurt Rhine, Germany during the 24 hour Artificial (Un)Intelligence Conference.


Session Description, A Blueprint for Reliable AI


AI is transforming the enterprise landscape, but its power and precision all come down to one key ingredient: information. Just as fertile soil is essential for agriculture, high-quality data fuels AI, enabling innovation, automation, and smarter decision-making. Yet, many organizations struggle to harness and refine this resource, resulting in biased models, unreliable insights, and missed opportunities. 


This session dives into the evolution of AI’s data ecosystem, the challenges of maintaining data integrity, and the roadmap to building resilient, trustworthy AI. By treating information as the bedrock of AI success, we’ll explore strategies for developing reliable, ethical, and high-performing AI solutions that drive real business impact.


Ingal Glotzbach will be presenting with Tim.


Together, Inga and Tim co-host the popular podcast Tapas & Pretzels. Through engaging conversations, they explore the nuances of digital transformation with a spotlight on API and AI technologies. Their combined expertise and storytelling flair make complex concepts accessible and actionable for a diverse audience.


Takeaways from this Session


1. Reliable AI requires more than just good data

High-quality data alone is not enough—organizations need structured processes that ensure data transparency, accuracy, and compliance with AI regulations like the EU AI Act.


2. Structured data governance ensures trust and accuracy

Data must be correct, traceable, and securely managed to maintain consistency and reliability. Only with robust data governance can AI deliver trustworthy and unbiased results.


3. Data privacy and AI compliance are non-negotiable

Organizations must ensure their AI models are not only powerful but also compliant with data and AI protection regulations. A structured data management approach prevents flawed or biased outcomes and strengthens trust in AI.





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