Gus CHIHABA

Magus Yoshiyahu Daniel Chihaba (Gus Chihaba) is a strategic data, analytics, and AI governance leader with more than 30 years of experience designing, scaling, and governing enterprise data capabilities across highly regulated industries, including financial services, healthcare, and telecommunications.

He specializes in building practical, regulator-ready data and AI governance frameworks that align data quality, risk management, compliance, and ethical AI adoption with real business outcomes. His work consistently bridges the gap between executive strategy and operational execution—embedding governance directly into applications, platforms, and engineering workflows rather than treating it as a standalone bureaucracy.

With deep expertise spanning data governance, decision intelligence, AI risk management, audit readiness, and enterprise architecture, Magus is known for helping organizations reduce silos, strengthen data integrity, and establish trust in both human and machine-driven decisions. He has led cross-functional teams of engineers, architects, compliance professionals, and business leaders to operationalize governance at scale while enabling innovation and automation.

Magus brings a values-driven approach to technology leadership. He is a strong advocate for responsible AI, transparency, accountability, and human-centered decision-making—believing that data and AI must serve people, institutions, and society with integrity. His work emphasizes stewardship over control, clarity over complexity, and long-term resilience over short-term gains.

He advises organizations on enterprise data strategy, AI governance, regulatory alignment, and operating models that prepare them for evolving global standards such as ISO 42001, the EU AI Act, and emerging AI risk frameworks. Magus is equally comfortable engaging with boards, regulators, executives, and technical teams, translating complexity into clear, actionable direction.

Above all, Magus is passionate about building data-driven cultures that are ethical, disciplined, and future-ready—where data and AI are trusted assets that support sound judgment, sustainable growth, and meaningful impact.