The ECAIDGDT 2027 Advisory Board brings together senior leaders whose expertise reflects the strategic, operational, regulatory, and trust-related priorities of enterprise AI adoption. The board supports the congress through perspectives spanning governance frameworks, data stewardship, risk and compliance, cyber resilience, responsible innovation, digital assurance, and leadership readiness, helping shape a programme that is relevant to executive decision-makers managing AI at scale.
AI ethics • Digital trust • Responsible innovation
Professor at ETH Zurich, Switzerland, recognised for work at the intersection of technology, ethics, governance, and public trust. Contributes high-level perspective on responsible AI, policy alignment, and human-centred oversight.
AI governance • Data ethics • Policy strategy
Internationally recognised thought leader in digital ethics and AI governance with strong influence across policy, enterprise decision-making, and governance strategy. Adds depth in accountability frameworks and executive-level governance thinking.
Digital innovation • Data-enabled care • Implementation
Senior European academic leader with experience in digitally enabled systems, translational implementation, and innovation governance. Brings perspective on adoption pathways and organisation-wide operational readiness.
Responsible technology • Governance design • Public values
Dutch scholar and governance expert known for responsible innovation and ethics-by-design. Supports the board with insights into value-sensitive governance, institutional accountability, and trust-oriented implementation of intelligent systems.
Cyber resilience • Digital risk • Enterprise controls
Senior advisor in digital governance and cyber resilience with experience in cross-border regulatory risk, enterprise controls, and governance assurance. Adds a practical perspective on resilience, control environments, and executive oversight.
Data strategy • Precision systems • Evidence-driven innovation
Senior Japanese leader with experience in data-intensive innovation, strategic use of digital systems, and evidence-led decision models. Contributes broader developed-Asia perspective on data governance and responsible innovation leadership.
Innovation leadership • Translational systems • Trust in technology
Internationally recognised innovation leader from the United Kingdom whose work sits at the interface of science, technology translation, and real-world application. Adds perspective on leadership readiness, adoption discipline, and responsible scaling.
Enterprise transformation • Governance execution • Strategy
Experienced senior industry leader from the United States with strong background in innovation governance, operational transformation, and translating complex strategy into disciplined execution. Adds an enterprise implementation perspective to the board.
AI systems • Data science • Computational governance
Research and innovation leader from Japan with strengths in data-driven systems, computational modelling, and operationally relevant digital interpretation. Supports the board with developed-Asia perspective on scaling intelligent systems responsibly.
Alongside the named advisory profiles above, the board structure reflects the broader areas shaping enterprise AI deployment. This helps ensure balanced attention across governance maturity, operational controls, regulatory expectations, digital trust, organisational readiness, and the realities of implementing intelligent systems in complex environments.
Coverage of governance operating models, accountability structures, executive oversight, policy alignment, and decision rights needed to guide responsible AI across the enterprise.
Perspective on data quality, stewardship, governance roles, access controls, lineage, and the strategic use of data to support resilient and trusted AI adoption.
Focus on risk governance, policy readiness, documentation discipline, compliance interpretation, audit preparedness, and the assurance practices needed in regulated settings.
Input around security-by-design, vendor risk, model risk exposure, operational resilience, incident readiness, and enterprise control environments supporting safe deployment.
Attention to transparency, fairness, ethics, human oversight, stakeholder confidence, and executive responsibilities in building trust around intelligent systems.
Consideration of business integration, control checkpoints, capability development, adoption governance, and the operational realities of moving from ambition to deployment.
Helps ensure the congress remains aligned with the current priorities of AI governance, enterprise data strategy, risk leadership, and trust-based digital transformation.
Strengthens the congress by reflecting expertise across governance, compliance, cyber resilience, data stewardship, and responsible innovation.
Encourages high-value discussions connecting policy leaders, enterprise executives, governance specialists, technology strategists, and implementation-focused teams.
Supports a practical view of how AI moves through governance design, control structures, data foundations, security assurance, and organisation-wide implementation.