CDAO Germany schedule

During this 5-minute networking session, the aim of the game is to go and meet two people you don't already know.  Have fun! 

• Where are German enterprises genuinely succeeding with AI and where are they still stuck in pilots? 

• How are boards, regulators, and works councils reshaping the CDAO mandate? 

• Is Germany’s risk-first culture slowing innovation or protecting long-term value? 

• What separates organisations that talk about AI maturity from those delivering measurable impact? 

• What must CDAOs stop doing in 2026 to move faster? 

• Why do so many well-funded data strategies fail to change day-to-day decisions? 

• How can CDAOs connect data initiatives directly to P&L, efficiency, and growth? 

• What trade-offs must leaders make between speed, quality, and governance? 

• How do you prove value when outcomes are indirect or long-term? 

• What lessons have emerged from initiatives that didn’t work? 

• How can governance be embedded into platforms rather than enforced after the fact? 

• What does “good governance” look like in production AI systems? 

• How should German organisations balance compliance, innovation, and accountability? 

• Where are teams over-engineering controls and where are risks underestimated? 

• How do you govern AI when use cases evolve faster than regulation? 

• Where AI strategies most commonly break down between design and execution 

• Organisational, data, and governance challenges that are underestimated early on 

• Aligning ambition with real capabilities, timelines, and constraints 

• What companies wish they had known before launching their AI strategy 

Panellists: 

Maximilian Ehrlich – Director Data & Insights – Tonies 

Florian Leser, Executive Advisor/ Former Head of Data Analytics and AI - KKH 

• What had to change in processes, not just technology, to deploy AI in production? 

• How were risk, compliance, and legal teams brought along the journey? 

• Where did expectations clash with reality? 

• What trade-offs were made between accuracy, speed, and explainability? 

• What would the organisation never do again? 

• What operating models work in German enterprises? 

• How to balance autonomy with alignment across business units 

• The hidden costs of getting the model wrong 

• How operating models must evolve as AI matures 

• Signs it’s time to change your current setup 

In this interactive session, attendees explore the real challenges of building data-driven organizations. Through guided discussion and a live poll, participants will tackle barriers to scaling data initiatives, benchmark their strategies, and walk away with actionable insights. 

Discussion Topics: 

• 
  Why is a reliable data foundation still so hard to achieve at scale?
  • What does “good enough” data really mean for decision-making and AI? 
  • How can traditional enterprises overcome legacy system inertia? 
  • What role do leadership commitment and organisational culture play in long-term success? 
  • Where do data initiatives most often fail — technology, people, or governance? 

Live Poll (5 mins) 

• 
  Which barrier is most critical — data, culture, or governance?
  • Where should focus and investment be prioritised in 2026? 
  • How confident are you that your data strategy will deliver measurable impact this year? 

Florian Leser, Executive Advisor/ Former Head of Data Analytics and AI - KKH 

Dr. Katharina Behme, Director Analytics & Insights – LUXEXPERIENCE 

• Why strong platforms still fail to drive adoption and impact 

• The critical success factors behind high-performing data teams 

• Building the right competencies across technical and business roles 

• Working with shared principles instead of rigid rules 

• How to shift mindsets, not just tools 

In this interactive discussion group, participants explore the data foundations required to scale AI and analytics in complex enterprises. Through guided peer discussion and live polling, attendees will unpack where data initiatives break down, compare approaches to data management and governance, and identify what truly enables trusted, reusable, AI-ready data at scale. 

Discussion Topics: 

• Why do data foundations still struggle to scale in large, federated organisations? 

• What does “fit-for-purpose” data mean in practice for analytics and AI use cases? 

• How can organisations balance decentralisation with consistency and control? 

• Where do data quality, integration, and governance most often fail to keep pace with AI ambition? 

• What foundations must be in place before scaling AI beyond pilots? 

Live Poll (5 mins): 

• What is the biggest blocker to scalable AI today — data quality, integration, governance, or ownership? 

• Where should enterprises focus first to unlock AI value in 2026? 

• How confident are you in your organisation’s current data foundations? 

 The wind industry is on its fast way to higher automation via AI and better decision making due to market demands. Ten years ago, planning and optimizing a wind farm with many wind turbines was a rather manual task with long lead times. Today it is possible within minutes. This talk focuses on the enormous rate of change within processes as well as costs and highlights explicitly the cultural mindset change in this former traditional industry. 

• When AI informs or automates decisions, who is ultimately accountable? 

• How do organisations prevent “decision drift” between business, data, and IT? 

• What governance models clarify ownership instead of adding friction? 

• How should CDAOs work with legal, compliance, and business leaders on accountability? 

• Where have organisations already learned these lessons the hard way? 

• How AI maturity has evolved from experimentation to industrialisation 

• Where GenAI is delivering value today and where expectations are inflated 

• What agentic AI changes for governance, accountability, and risk 

• How leaders should assess readiness before scaling 

• What the next phase of enterprise AI will demand from CDAOs 

• Why do organisations have more data than ever — yet struggle to act confidently? 

• Where do dashboards help decision-making, and where do they actively slow it down? 

• Are OKRs and KPIs being misused as reporting tools rather than decision tools? 

• How can organisations design metrics that support trade-offs, not just monitoring? 

• What should leaders stop measuring altogether? 

During this 5-minute networking session, the aim of the game is to go and meet two people you don't already know.  Have fun! 

This session will explore how organisations can design and structure data teams to maximise efficiency, innovation, and strategic alignment. Key discussions will include: 

• Balancing regulatory compliance, data security, and business agility through robust governance frameworks. 

• Integrating AI and machine learning capabilities within data teams to drive innovation and maintain competitive advantage. 

• Leveraging advanced data architectures and technologies (e.g., data lakes, data warehouses, and cloud platforms) to scale operations and enable data-driven decision-making. 
• Fostering a culture of data literacy and continuous improvement, ensuring employees at all levels are empowered to leverage data effectively.

Moderator: Aleksejs Plotnikovs, Founder of chiefdata.ai, and former Lead of Data & AI Strategy at Microsoft 

Olga Ivina, Global Head of Data Science Engineering – MICROSOFT 

Jesse Rothenberg, Head of Data & Insights Unit – ABLETON 

Financial data teams operate in an environment where agility and innovation must align with strict governance and compliance requirements. Establishing the right infrastructure is essential to maximize efficiency while ensuring security and regulatory adherence. 

This talk explores how organizations can design governance frameworks that protect data assets without hindering business agility, leverage modern data architectures (data lakes, warehouses, and cloud solutions) to scale effectively, and facilitate seamless transitions from research to production. Insights will be drawn from building a quantitative investment infrastructure from the ground up, addressing key challenges such as high availability, versioning, real-time data access, and compliance. 

By examining strategies that balance security with flexibility, this session provides practical takeaways for designing IT-safe, governance-aligned setups. Additionally, the discussion will highlight how collaborative platforms, and structured workflows can enhance efficiency across infrastructure and development processes. 

Rudi Bauer, CEO –INFRAFIN 

Hendrik Steinbach, Senior Associate & Lead Data Scientist -neXDos 

Join an interactive session with a seasoned leader at the intersection of strategy, finance, data, and cybersecurity.  With extensive experience driving growth and digital transformation across sectors—including digital business, Industry 4.0, the public sector, blue chips, and scale-ups—this expert will share practical guidance on leveraging data strategically, aligning with compliance requirements, and strengthening cyber-resilience. 

Key Focus Areas: Data-driven ROI, data strategy in regulated industries, cyber-resilience, digital transformation, AI-driven innovation, and the socio-economic impact of digital business models. 

Elizabeth Press, Deputy Chief Digital Officer – Center for Hybrid Electric Systems Cottbus (CHESCO) 

AI investments must serve business goals, not the other way around, to drive growth and competitiveness. Organizations need to directly link their data strategy with business objectives to achieve sustained profitability. The presentation demonstrates how combining strategic alignment with organizational maturity enables AI profitability scaling across companies of any size, whether public or private.  

Self-service analytics can be a game-changer for product teams, helping them move faster and make better decisions without relying on data specialists. Divya Bokaria has done exactly that at ZATTOO, setting up analytics events, tools, and training to put data directly in the hands of product teams. In this session, she’ll share her experiences and key takeaways. 

🔹 Turning Data into Action – How she heled built the right setup to help teams make informed, data-driven decisions. 
🔹 Breaking Down Barriers – Making data accessible and usable without creating bottlenecks. 
🔹 From Insight to Impact – Real examples of how self-service analytics helped product teams iterate faster and drive growth. 

• How do organisations determine which datasets require governance when faced with an overwhelming volume of information? 

• What are the key hurdles in maintaining regulatory compliance during governance initiatives, and how can these be effectively managed? 

• In what ways can adaptable governance models promote tailored and secure access to data across diverse business needs? 

• What practical steps can dismantle data silos between departments to drive faster, more informed decision-making? 

• How can aligning data governance efforts with organisational culture and stakeholder priorities strengthen governance frameworks? 
  

Moderator: Stella Cabrera, Member Services – EDM Council 

Dr.-Ing. Susan Wegner, Head of Global Data and AI – ALLIANZ 

Alexander Yasnogor, VP of Data - FINN 

• How to use data analytics to optimize operations and drive cost efficiencies  

• Aligning business strategies with sustainability objectives using data insights  

•  Ethical data use, transparency, and governance in decision-making  

• Overcoming common challenges in implementing data-driven strategies in complex industries 

Moderator: Stella Cabrera, Member Services – EDM Council  

Francesco Di Costanzo, CEO – JAJA FINANCE 

Valeriy Arsentyev, Head of Data - HUMANOO 

• What strategies can organizations adopt to identify and monetize untapped data assets while maintaining compliance with GDPR and other regulations in the German market? 

• How can businesses create scalable data products or services that deliver value to external customers and internal stakeholders without compromising operational efficiency? 

• What role do emerging technologies like AI, IoT, and predictive analytics play in transforming raw data into profitable revenue streams across industries such as manufacturing and finance? 

• How can organizations balance data monetization efforts with ethical considerations and customer trust to ensure long-term commercial success? 

Moderator:Aleksejs Plotnikovs, Founder of chiefdata.ai, and former Lead of Data & AI Strategy at Microsoft 

Sebastian Schwarz, Head of Data & AI – Customer Solutions - E. ON Technology 

Tim Renner, Head of Business Analytics - KROMI Logistik GmbH  

• What are the core principles of effective data management? 

• How can robust data management practices speed up digital transformation initiatives? 

• In what ways can data management enhance decision-making and drive business innovation? 

• What strategies can overcome common challenges in data management?

Sandeep Murali, Global Director of Data Excellence and Business Analytics -MUNDIPHARMA 

Shyam Arumugaswamy, Data Engineer - UNITE