As digital transformation accelerates, the convergence of AI, data governance, and ecosystem thinking is reshaping how organizations create strategic value, build competitiveness, and sustain innovation advantage. Digital and data ecosystems are increasingly complex, spanning cloud, edge, and decentralized architectures such as data meshes and lakehouses, raising critical questions of trustworthiness, responsibility, and sustainability in AI integration.
This AMCIS2026 mini-track (by Association of Information Systems (AIS)) explores how AI, including increasingly agentic systems, acts as both a strategic enabler and active participant in digital and data ecosystems, enhancing governance, augmenting and automating decision-making, and transforming how organizations create value, while raising important governance, ethical, and human-agency considerations. We invite research examining how these ecosystems can remain responsible, resilient, and sustainable, while enhancing organizational agility, competitiveness, and long-term strategic performance across sectors such as government, healthcare, finance, manufacturing, and education.
The track bridges perspectives from information systems, data science, AI governance, and sustainability research to understand how the strategic and responsible design and management of AI-driven data ecosystems can support long-term value creation, competitiveness, and societal transformation. We invite interdisciplinary contributions from fields such as computer science, management science, data science, process science, decision science, organizational design, policy-making, complexity, behavioral economics, and the social sciences. Submissions may include conceptual, design science, empirical, theoretical, or case-based studies, including literature reviews.
Topics of interest include but are not limited to:
- AI for governance, accountability, and trustworthiness in digital and data ecosystems;
- human–AI collaboration and delegation, human-in-the-loop and hybrid governance;
- responsible, sustainable, and strategically aligned management of AI-augmented data ecosystems, including Green AI;
- governance and data management in emerging architectures (e.g., data mesh, data lakehouse), including data quality, transparency, and explainability;
- transition from centralized to decentralized data architectures – organizational and design challenges;
- ethical, interoperable, observable, and explainable AI in connected and cross-sectoral data ecosystems;
- co-evolution of digital and data ecosystem components;
- coopetition between digital and data ecosystems;
- resilience, sustainability, and long-term governance of digital infrastructures;
- socio-technical, organizational, and policy approaches to trustworthy and responsible data ecosystems;
- emerging technologies (e.g., blockchain, edge computing, generative AI, digital twins, IoT, AR/VR) shaping responsible, sustainable, and energy- or resource-efficient strategic ecosystem innovation;
- empirical studies and sectoral case analyses (e.g., healthcare, finance, government, education) on evolving AI-driven ecosystems;
- design science, conceptual, and interdisciplinary frameworks for responsible, sustainable, and strategically effective data ecosystem innovation.
This mini-track will serve as a platform for interdisciplinary dialogue on the critical role of responsible, sustainable, and strategically oriented digital and data ecosystems in driving competitive and societal innovation. Researchers and practitioners are invited to share insights, theoretical perspectives, and empirical findings in this rapidly evolving domain.
📌 Submission Deadline: March 1, 2026
📍 Venue: AMCIS 2026 — Reno, Nevada (August 20–22)
Mini-Track Chairs
Anastasija Nikiforova – University of Tartu, Estonia
Daniel Staegemann – Otto von Guericke University Magdeburg, Germany
Asif Gill – University of Technology Sydney, Australia
Martin Lnenicka – University of Hradec Králové, Czech Republic
George Marakas – Florida International University, USA
Anastasija Nikiforova, PhD 