Scale AI with purpose—align your tech, teams, and product design with trust

Drive responsible AI adoption across your organization with strategic governance, risk management, and regulatory readiness. This track empowers leaders to build trustworthy AI products by aligning innovation with oversight and long-term value.

AI Strategy & Governance

Learn from Industry Leaders about:

  • Designing scalable AI strategies that balance innovation with accountability.
  • Navigating global AI regulations and embedding compliance into the development process.
  • Applying ethical design principles for transparency, fairness, and user safety.
  • Building audit-ready governance frameworks for model approval and lifecycle tracking.
  • Aligning product development with responsible AI delivery and business impact.

Frequently Asked Questions

What is the focus of the AI Strategy & Governance track?

This track provides a blueprint for aligning AI innovation with ethical principles, risk controls, and regulatory compliance. It’s built for decision-makers, architects, and product leaders looking to deploy AI at scale—safely and responsibly.

Why is AI governance essential in modern organizations?

AI systems impact users, policies, and reputations. This track helps organizations implement structured oversight—ensuring that AI outputs are explainable, auditable, and aligned with both business and societal expectations.

How do global regulations influence AI design?

From the EU AI Act to industry-specific compliance mandates, AI governance must consider legal frameworks. This track covers how to operationalize those frameworks within your data pipelines, models, and deployment workflows.

What is responsible AI and how can it be implemented?

Responsible AI means designing systems that prioritize fairness, transparency, safety, and accountability. Learn how to incorporate these values into your models and product roadmaps through design reviews, checklists, and governance metrics.

What tools and frameworks support AI governance?

Attendees will explore model documentation standards, decision traceability tools, and risk management protocols that support enterprise AI oversight—from ideation to post-deployment monitoring.

Track Speakers London 2025

Track Speakers San Diego 2025

San Diego's program will go live soon! Until then, please take a look at

New York's 2024 Program!

Track Speakers Munich 2025

Track Speakers Berlin 2025

Track Speakers New York 2025

Track Program London 2025

Track Speakers San Diego 2025

TRACK PROGRAM MUNICH 2025

Track Program New York 2025

Track Program Berlin 2025

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Nov 
11, 
2022
Product thinking is a well-known and frequently discussed approach for developing software products. The prospect of using the same approach with data, though, is new. "Data as a product" is the key phrase and one of the four pillars of the data mesh architecture concept. But what does that actually mean? How can a company develop data products for both internal and external clients? What can we learn about this from relevant SW projects? And how do agility, warehouses, and...
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Bernd Fondermann
Bernd Fondermann
Bernd Fondermann
bernd fondermann brainlounge
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Sep 
15, 
2022
Welcome:MLCON Berlin 2022 starts with a full programme on several tracks. We would like to welcome you, share important information about the conference schedule and take a look at the highlights of the day. Opening Keynote:Incorporating Machine Learning into a business strategy opens up fascinating new possibilities, but is anything but simple. We have seen far too many failed ML projects or prototypes that had no impact on the business. At the same time, if ML projects are approached the...
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Christoph Henkelmann
Christoph Henkelmann
Sebastian Meyen
Sebastian Meyen
Sebastian Meyen
Software & Support Media
Christoph Windheuser
Christoph Windheuser
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Aug 
18, 
2022
Biomedical Data classification with machine learning for healthcare In this study we used Biomedical data/information that relates to human health. We acquired such data for monitoring specific pathological /physiological states for the purposes of diagnosis and evaluating therapy. The data were used for decoding and eventual modeling of specific biological systems. The acquisition of the study results from the Instrumentation at the molecular/cell level, or a systemic or organ level, Medical Imaging – Mobile/portable/wearable devices – Electronic health record. Automated...
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Zoha Rahman
Dr. Zoha Rahman
Dr. Zoha Rahman
Centre For Big Data & Machine Learning
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Aug 
12, 
2022
Many companies are already using machine learning and artificial intelligence algorithms. However, winning a Kaggle competition is not enough, the decisive factors are not only to train the best fitting model. The time to market of the models are crucial. To improve the time to market consistently, an end-to-end MLOps process that are required to train, test, deploy, run, and monitor ML models is essential for a company’s success. Building such a MLOps pipeline is a complex journey as the...
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Prof. Dr. René Brunner
Prof. Dr. René Brunner
Prof. Dr. René Brunner
Datamics / Professor an der Hochschule Macromedia
Eric Joachim Liese
Eric Joachim Liese
Eric Joachim Liese
BSH Home Appliances Group
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Aug 
10, 
2022
Machine learning is often hyped, but how does it work? In this workshop, Dr. Pieter Buteneers will show you hands-on how you can build your own machine learning models. We will cover basic machine learning concepts such as regression, classification, over-fitting, cross-validation, and many more. After the workshop, you will go home with the basics of machine learning so you can start off on your own projects.
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Aug 
3, 
2022
The ML Con Strategy Day provides a unique opportunity to learn from experts what steps must be taken to build successful ML products. It provides an in-depth overview of the approaches ML pioneers and thought leaders use to develop amazing Machine Learning implementations: which know-how is needed, which methodologies are helpful, what technology choices must be made, and how to manage ML in production. Incorporating Machine Learning into a business strategy opens up fascinating new possibilities, but is anything but...
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Christoph Henkelmann
Christoph Henkelmann
Alex Honchar
Alex Honchar
Alex Honchar
Neurons Lab
Arif Wider
Arif Wider
Arif Wider
Thoughtworks Deutschland / HTW Berlin
Christoph Windheuser
Christoph Windheuser

Behind the Tracks