I advise and lead organizations on how artificial intelligence and data fundamentally reshape strategy, organizational design, and decision-making. My work focuses on the governance and orchestration of AI-enabled capabilities, with a particular interest in how emerging technologies transform authority structures, information flows, coordination mechanisms, and organizational resilience. Bridging computational social science, organization theory, and digital strategy, I develop evidence-based approaches to help organizations navigate complex transformations and build sustainable AI capabilities in highly regulated environments.

Alongside my academic foundation (PhD), I currently lead an AI & Data unit of 14 consultants, translating rigorous research into large-scale transformation initiatives and operational practice.

Core Areas

• Complex Systems and Modeling Methods: Studying governance and decision-making processes as complex systems. The focus is on methods for analyzing dynamics, feedback loops, and emergent effects in digital and organizational environments.

• Computational Social Science and Data Science: Applying data-driven methods to analyze social and organizational phenomena, including large-scale social media data, network and text analysis, and critical reflection on their validity.

• Organizational Network Analysis and Communication Dynamics: Analyzing structures and dynamics in communication networks, particularly conflicts on social media and within organizations, to understand how network structures shape information flow, coordination, and collaboration.

• Algorithmic Governance and Decision-Making: Investigating how algorithmically mediated systems transform decision processes in public administration, platforms, and companies, including questions of steering, accountability, and the design of digital organizations.

• AI and Equality (Fairness, Participation, and Ethics): Examining the societal and organizational impact of AI systems on equal opportunity and participation, with a focus on ethical questions, bias in data and models, and the design of fair AI governance.

• Strategic Management and Advisory in the Public Sector: Researching how strategic management and advisory practice support public-sector organizations in navigating complex transformation. The focus is on how data-driven insights inform strategic decisions, governance structures, and the implementation of digital initiatives in ministries and administrative bodies.

• Project Governance and Data-Driven Approaches to Complex Organizational Challenges: Examining how project governance structures and data-driven methods can address complex organizational problems. This includes the design of decision processes, accountability and steering mechanisms, and the use of analytical evidence to support advisory work and project delivery.