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About

AI Technology Leader at the Israel National Digital Agency. Former CTO. Former Chief Data Scientist for the TIMNA healthcare AI platform.

Moshe started in data and business, moved into applied healthcare AI and national health data platforms through TIMNA, then into private-sector CTO roles, and today works on government-wide AI adoption at the Israel National Digital Agency.

This path shaped his view that AI is not just a demo layer or a productivity tool, but an operating capability that requires strategy, infrastructure, governance, product thinking, and organizational change.

His current work focuses on AI operating models, agentic systems, governance, infrastructure, and complex organizations, areas where AI's promise meets the reality of implementation.

Career Journey

Healthcare AI and National Data Platforms

Earlier in his career, he led data science work for TIMNA, Israel's national health research platform, where he worked on applied machine learning, NLP, computer vision, anonymization, and national-scale health data infrastructure.

Projects included unplanned cesarean delivery prediction, longitudinal HbA1c trends, pediatric development screening, medical free-text classification, pathology document processing, entity extraction, anonymization, and clinical image analysis.

Private-Sector AI and Product Execution

He later served as CTO at Stat-Market and co-founder and CTO at umAI, working on AI products, cloud architectures, enterprise delivery, and ROI-oriented execution.

In these roles, Moshe established a discipline of extreme operational efficiency and high-velocity product execution. Operating within highly dynamic startup constraints, he directed the full lifecycle of AI product incubation, bridging the gap between raw research, rapid MVP prototyping, market positioning, and continuous user-driven feedback. He structured lean, cross-functional teams to translate emerging technologies into immediate, adaptable capabilities.

This experience shaped a practical view of AI: good models are not enough. AI needs to connect to products, workflows, users, business value, cost discipline, and implementation constraints.

Government AI Transformation

Today, his work focuses on the harder part of AI adoption: not the demo, but the operating layer. Strategy, governance, cloud and data infrastructure, permissions, product thinking, and organizational change all need to come together before AI becomes a real capability.

At the Israel National Digital Agency, he works on GOVAI, the AI Expertise Center, cross-government AI adoption, infrastructure thinking, and governance frameworks.

Focus Areas

Moshe writes about AI operating models, agentic systems, AI infrastructure, AI governance, healthcare AI, public-sector transformation, and national AI strategy.

AI Operating Models

How organizations move from pilots and tools to repeatable AI capabilities.

Agentic Systems

How AI agents, orchestration, permissions, and workflows change organizational work.

AI Infrastructure and Governance

The platforms, cloud environments, data layers, and guardrails needed to scale AI responsibly.

AI Strategy for Complex Organizations

Lessons from healthcare, enterprise, and government on adopting AI where complexity is real.

Writing & Thinking

Moshe writes about AI operating models, agentic systems, AI infrastructure, AI governance, healthcare AI, public-sector transformation, and national AI strategy. He is a co-author of a Lawfare article on global AI governance through a layered framework.

Executive Advisory

Looking for a leader to guide your enterprise through the transition to agentic AI? Let's discuss strategy, governance, and building high-performance AI organizations.