AI Governance · Responsible AI · Enterprise AI
I help global, regulated organizations operationalize AI with the governance, risk controls, and delivery discipline that executives and auditors can stand behind.
Director-level technology and product leader at the World Bank Group, with 15+ years across AI governance, enterprise transformation, and technical program leadership. Built the institution's first production AI system for operations.
About
Move AI from experimentation to governed, operational reality — managing legal, privacy, security, and operational risk alongside delivery. — Operating philosophy
Seydou Ly is a senior technology and product leader focused on helping enterprises operationalize AI in environments where legal, privacy, security, and operational risk must be managed alongside delivery. His experience spans AI governance, enterprise transformation, product strategy, and technical program leadership.
At the World Bank Group, his work has included leading modernization and AI initiatives involving production AI systems, cloud-scale information platforms, enterprise architecture, and responsible AI delivery — including helping launch the institution's first production AI system for operations, supporting audited financial-statement processing across ~3,000 global projects with 95% extraction accuracy.
Today he leads a ~38-person engineering and product organization and a $4M portfolio. His strengths include NIST AI RMF–aligned governance, familiarity with ISO/IEC 42001 expectations for enterprise AI management systems, human-in-the-loop validation, vendor evaluation, and large-scale transformation across global teams.
Selected impact
Representative work delivered in one of the world's most complex regulated, multinational institutions — where AI has to pass legal, security, and privacy review before it ships.
Built and launched the World Bank's first production AI system for operations (2021), automating audited financial-statement review across ~3,000 global projects at 95% extraction accuracy across multiple languages — earning an institutional innovation award.
Introduced governance practices aligned to NIST AI RMF and adaptable to broader enterprise expectations, with human-in-the-loop validation — enabling releases to clear legal, privacy, and security review. A validation workbench cut AI testing cycles from quarters to weeks.
Defined reusable standards for RAG, vector search, and document extraction, and launched an enterprise AI assistant and internal accelerator model — improving reuse and execution speed and reducing solution delivery time by roughly 50%.
Led migration of 80M+ documents across 41 vice presidencies to the cloud, establishing the audit-ready data foundation that downstream analytics and AI workflows now depend on — delivered with onshore/offshore teams across multiple countries.
Experience
World Bank Group · Washington, DC · Director-level scope
World Bank Group · Washington, DC
World Bank Group · Washington, DC
Delivered technical design for the World Bank Knowledge Platform and led migration of 300+ intranet sites to SharePoint Online; managed budget, staffing, security accreditation, and release processes.
American University · Washington, DC
Owned university-wide information architecture and platform lifecycle strategy across schools and departments; delivered a communications platform that let non-technical users publish and route content more efficiently.
TAG Integrated Technologies LLC · Gaithersburg, MD
Reduced annual support costs by $100K+ and expanded reporting capability by 600% through product lifecycle ownership of a commercial budgeting platform; led deployments, training, and client enablement for enterprise customers.
Expertise
Establish enterprise governance strategy, operating models, and controls — NIST AI RMF–aligned, ISO/IEC 42001–aware — that make safe, scalable AI adoption possible.
Move AI from pilots to governed operations: operating models, human-in-the-loop validation, and adoption across business units.
Lead complex programs across stakeholders, vendors, and technical teams — roadmap, portfolio execution, and delivery governance.
Translate emerging technology into scalable business capability with clear ownership, reusable patterns, and measurable outcomes.
Guide cloud, platform, and document/data modernization that establishes audit-ready foundations for analytics and AI.
Partner with legal, security, privacy, and audit so governance is built in — not bolted on — and releases pass review.
Contact
Open to Director-level roles in AI governance, responsible AI, enterprise AI transformation, and technical program leadership. Share a few details and I'll respond personally.