Scientific Tracks • Applied Research • Policy & Industry Relevance
Themes & Topics
ECAIDGDT 2027 is structured around high-impact scientific, policy, and professional themes across artificial intelligence, enterprise data governance, model oversight, compliance, cyber resilience, and digital trust. The framework below reflects the core topic areas shaping the Zurich programme and abstract review process.
How We Structure Themes
The ECAIDGDT 2027 program is built to create value for senior decision-makers responsible for enterprise AI, data governance, assurance, risk, compliance, security, and trust outcomes. We intentionally balance strategy, governance, implementation, and measurable business impact.
Formats may include keynote lectures, oral presentations, expert panels, research and policy roundtables, poster sessions, applied case studies, and abstract-led sessions designed to support research exchange, professional discussion, and practical implementation.
Track A — Enterprise AI Strategy & Operating Model
Strategic alignment of AI initiatives with business priorities, governance accountability, and scalable operating models.
- AI leadership and enterprise roadmaps
- Operating model design and accountability
- Portfolio prioritisation and value realisation
- Organisational sponsorship and transformation alignment
Track B — Data Governance & Data Products
Ownership, stewardship, quality, lineage, policy controls, and enterprise data design for trusted AI and analytics.
- Data ownership, stewardship, and governance councils
- Quality, lineage, metadata, and catalogue strategy
- Data products and data operating models
- Interoperability and enterprise data architecture
Track C — Model Governance & Lifecycle Controls
Governance frameworks for AI and model risk across development, deployment, monitoring, and incident response.
- Model documentation and approval workflows
- Drift monitoring and performance oversight
- Change control, rollback, and escalation pathways
- Controls for generative and predictive systems
Track D — Risk, Compliance & Assurance
Auditability, regulatory readiness, assurance frameworks, and evidence-based governance for enterprise trust.
- Regulatory mapping and compliance readiness
- Assurance frameworks and audit evidence
- Third-party AI and vendor risk
- Control testing and governance reporting
Track E — Privacy, Security & Cyber Resilience
Security-by-design, privacy governance, secure data pipelines, and resilience strategies for trusted digital systems.
- Privacy-by-design and data minimisation
- Identity, access, and secure governance models
- Cyber resilience for AI-enabled environments
- Incident readiness and response governance
Track F — Digital Trust, Adoption & Future Outlook
Adoption at scale, stakeholder trust, responsible deployment, and organisational planning for the next phase of AI governance.
- Trust signals, provenance, and explainability
- Adoption barriers and change management
- Cross-functional governance collaboration
- Future outlook for AI regulation and operating models
Common Topic Clusters
These clusters help frame abstracts, panels, roundtables, research presentations, and professional discussions for ECAIDGDT 2027. They are broad enough to support strategic, technical, legal, compliance, and operating model perspectives.
Governance structures, accountable AI, organisational oversight, and policy operating models.
Data ownership, lineage, quality, stewardship, and business-aligned data products.
Regulatory readiness, model risk, policy controls, auditability, and assurance.
Security controls, access governance, resilience, third-party risk, and operational protection.
Digital trust, identity, provenance, transparency, confidence, and stakeholder adoption.
Transformation leadership, culture, decision rights, change adoption, and organisational alignment.
Tip for abstract submissions: Include your preferred session format (keynote / panel / roundtable / case study), the intended audience (research / governance / technical / policy / risk / compliance), and 3–5 practical learning outcomes.
Submit an Abstract
Researchers, professionals, academics, policymakers, students, and industry contributors are invited to submit abstracts aligned with the ECAIDGDT 2027 themes. Abstract submission closes on 31 October 2026. Submit a short summary with your intended format and relevance to AI governance, data strategy, or digital trust.