This commentary delivers the key insights shared by the Data and AI Leaders Master Class at the CDOIQ Nordic Symposium 2025. Through insightful discussions led by experienced data leaders, the master class highlighted how organizations should redesign team structures, align data and AI initiatives with strategic goals, and empower business leadership to deliver better value for their business. Rather than summarizing the entire discussion, the commentary delivers the most interesting practical reminders for data leaders on the critical success factors for transformative data leadership.

Modelling Organizational and Team Topologies for Data Products and AI Agents

Henrik Göthberg, founder of the professional crowdsourcing alliance Dairdux, presented a compelling critique of current organizational models in data and AI. Drawing on his experience at Vattenfall and Scania, Göthberg emphasized the limitations of the so-called ”unicorn” role—expecting a single individual to master all aspects of data management. This unrealistic expectation, echoed in John Bottega’s keynote on the evolution of Chief Data Officers (CDOs), contributes to short tenures and limited organizational impact.

Göthberg argued for a shift from individual-centric and administrative approaches to organizational structures that foster collective capability. He highlighted the need for integrated knowledge communities and team topologies that align with shared business objectives. Many organizations, he noted, suffer from misaligned agency structures, resulting in fragmented governance and siloed optimization efforts.

A key critique was directed at traditional data governance approaches, which often function as administrative overlays without linking them to business value. Instead, Göthberg advocated for collaborative, cross-functional teams—comprising business, data, and AI professionals—working toward unified goals. This approach promotes natural agency, aligns governance with strategic business priorities, and enhances the effectiveness of data investments. The message aligns with contemporary trends such as data mesh and data product thinking, which similarly emphasize decentralization, domain ownership, and value-driven data practices.

Key Lesson for Data Leaders
To achieve sustainable value from data and AI, organizations must restructure governance and team topologies to support integrated, business-aligned operations. This requires moving beyond tool-centric or administrative governance approaches and fostering cohesive, goal-oriented collaboration based on business agency.

StratOps: A Data and AI Portfolio for Smart Investments and Effective Adoption

Nicolas Averseng introduced the concept of StratOps—a strategic operations framework for managing data and AI portfolios. With over two decades of experience in enterprise software, Averseng founded YOOI, a SaaS platform designed to help large enterprises align practical execution with business strategy and optimize the value and costs of data and AI initiatives.

In his presentation, Averseng addressed a central challenge for data leaders: selecting and managing initiatives that are not only technically sound but also valuable for business, compliant against regulations, and evolving across times. YOOI platform supports this by consolidating organizational and project-level data, enabling risk assessment, value tracking, and collaborative planning to help large enterprises manage their evolving data and AI investments.

Averseng emphasized the importance of managing the entire lifecycle of data and AI initiatives—from planning to phase-out. He advocated for a shift from fragmented planning documentation and technical lineage to business value management—linking business contributions, development efforts, and organizational assets. This approach ensures that strategic business intent is translated into measurable outcomes.

Key Lesson for Data Leaders
Effective data and AI leadership requires a business-oriented, target-state-driven, and systematically operationalized approach. StratOps by YOOI provides a framework for aligning investments with strategic goals and fostering cross-functional collaboration throughout the lifecycle of data and AI initiatives.

Overcoming Organizational Disconnect: From Governance to Value-Driven Transformation

This panel brought together leaders from diverse industries—automotive, financial services, and mining—to discuss on the challenging disconnect between data governance and business value realization. Jan Guhres (Scania/Traton), Helena Hörnebrant (Traton Financial Services), and Weynand Deysel (Boliden) shared insights on how organizations can overcome structural and cultural barriers to transformation.

Echoing themes from Göthberg and Averseng, the panelists emphasized that business leadership must drive data and AI initiatives. However, they emphasized that meaningful transformation begins when business leaders are empowered to take ownership of their data initiatives. In this context, the Chief Data Officer plays a pivotal role—not only as a strategist, but also as a facilitator who enables business leaders to become successful change agents for data-driven initiatives. The key lies in building strong alliances with these business leaders by actively supporting and elevating their role as successful business directors within the organization.

A central focus of the discussion was how to establish effective data governance across the organization. The panelists emphasized that for business leaders to drive meaningful change, they must understand both the opportunities and the risks associated with data. They noted that tools alone are insufficient; instead, training, inspiration, and clear communication are essential to engage those who are not early adopters. Many business leaders and employees remain unaware of the strategic value of data, making education a critical component of any successful enterprise transformation effort.

The conversation also addressed structural challenges that continue to impede progress. The panelists emphasized the importance of involving data leaders throughout the entire business value chain and ensuring they have a comprehensive understanding of the broader business context. However, in practice, the panelist noted that persistent issues remain—particularly those related to cross-functional collaboration and the allocation of costs and revenues across business units—which continue to complicate effective data management. As one speaker pointed out, “Follow the money—without solving funding, the CDO will fail,” underscoring the financial dimension of successful data leadership. Business leaders hold the keys to funding and influence, and by enabling them to become data-driven superstars, CDOs can build the momentum needed to tackle deeper challenges—such as improving data interoperability and quality across business value chains.

Key Lesson for Data Leaders
Transformative data leadership requires empowering business ownership, ensuring financial commitment, and facilitating cross-functional collaboration. Tools alone are insufficient; education, communication, and empowerment are essential to drive meaningful change.

Advancing Data Leadership for Business and Society

The CDOIQ Nordic Symposium forms part of the international CDOIQ Program, originally founded at MIT, and now extended to the Nordic region through collaboration with Aalto University Executive Education and Professional Development and a network of community partners, such as DAMA Finland and DAMA Norway.

An overall summary of the entire event, including speaker highlights and thematic insights, is available here: Link to the CDOIQ Nordic Symposium Post-Event Summary.

For inquiries regarding CDOIQ communities and activities, please reach out to the appropriate regional organizers here: Link to the global CDOIQ Society website. Sami Laine serves as the contact for the Nordic region.

Sami Laine is a Senior Advisor at Aalto EE, where he is spearheading the mission to bring the world-renowned CDOIQ Symposium to the Nordics, and a Senior Data Advisor at Tietoevry Tech Services. During his over 20 years career, he has worked in data management practitioner, consultant, researcher, and teacher roles in several business sectors. Throughout his career, Sami has been an active advocate for promoting quality and ethical perspectives in data management and business decision-making, as recognized by his nomination for the DAIR Awards in 2022. He has been a long-time president and board member of the DAMA Finland ry and a program committee member of the MIT CDOIQ Symposium.