India AI Impact Summit 2026

from-opportunity-to-impact-sharing-the-israeli-model-of-ai-innovation-and-governance

8 min read

TRACK:Economic Growth and Social Good
SPEAKERS
  • Brigadier General (Res.) Erez Naftali Askal, Israel Artificial Intelligence Directorate
  • Dr. Victor Alchanatis, DSc., Volcani Institute, Ministry of Agriculture
  • Dr. Victor Israel Gosalker, Horizon Line Division
  • H.E. Reuven Azar, Ministry of Foreign Affairs, Israel
  • Mr. Avner Vilan, AI21
  • Ms. Inbal Mashash, Israel Employment Service
  • Ms. Meirav Zerbib, Ministry of Education, Innovation and Technology Administration
SESSION OVERVIEW

This event will showcase Israel's national AI model — prioritizing innovation, research, and agile governance over restrictive regulation—to drive social, economic, and public-service transformation. It highlights Israel's strengths (innovation hub, elite technical talent, collaborative public-private partnerships). The session features short talks on national strategy, AI in agriculture, personalized education, future of work, and industry leadership, aiming to share best practices and forge international partnerships.

VIDEO RECORDING

From Opportunity to Impact: Sharing the Israeli Model of AI Innovation and Governance

Abstract

The session presented Israel’s national AI model, emphasizing an “innovation‑first, regulation‑second” approach that couples cutting‑edge research with agile governance. Six short talks covered the strategic agenda of the AI Directorate, concrete AI applications in agriculture, education, employment, scientific research, industry, and digital health, followed by remarks underscoring Israel–India collaboration and the “Jerusalem Declaration” on AI in education. The overarching message was that Israel’s elite technical talent, public‑private partnerships, and layered AI stack enable rapid translation of AI breakthroughs into societal impact, and the country seeks international partners—particularly India—to scale these solutions.

Detailed Summary

  • Highlighted the 30‑year diplomatic partnership between Israel and India and framed AI as the pivotal challenge and opportunity for both nations.
  • Stressed the need for accessible AI for every citizen and entrepreneur, not just a security‑focused tool.
  • Invited the audience to hear how Israeli experts are building capability and access, positioning AI as a bridge to “flourish and develop new projects” together.

Key Insight: AI is presented as a universal enabler for societal development; bilateral cooperation is essential to scale impact.

2. Strategic Core of Israel’s AI Journey – Brig. Gen. (Res.) Erez Askal, Head of AI Directorate, Prime Minister’s Office

  • Mission: Place Israel among the top‑three global AI nations and improve quality of life for Israelis and allies (including India).
  • Three Pillars of Action:
    1. Real‑life Labs – 50 vertical domains addressed through joint academia‑industry labs.
    2. Cyber‑security for AI – Secure, trustworthy foundational models and edge‑ready AI.
    3. Edge Solutions – Deploy AI locally (e.g., surgery rooms, classrooms, border drones) rather than relying on distant data‑centers.
  • Emphasized collaboration with India and other major economies as indispensable; Israel cannot achieve its goals alone.

Announcements: None specific, but a promise to showcase Israeli AI products later in the session.

Recommendations: Leverage Israel’s military‑grade cybersecurity expertise to protect AI deployments; prioritize edge‑computing to meet latency and privacy requirements.

3. AI for Sustainable Agriculture – Dr. Victor Alchanatis, Senior Research Scientist, Center of AI in Agriculture, Volcani Institute

  • Mission: Feed a growing global population while preserving the planet.
  • Challenges: Traditional sustainability (reduced inputs) conflicts with yield requirements.
  • AI‑Enabled Solutions:
    • Precision Agriculture – Use computer‑vision and deep‑learning to detect weeds, pests, and diseases early; apply herbicides/fertilizers only where needed.
    • Digital Twins & Spatial Simulations – Model field conditions to identify optimal growing parameters for each micro‑zone.
    • Genomics & Phenomics – AI analyses link genes to phenotypes, accelerating the development of climate‑resilient crop varieties.
  • Infrastructure: A national centre integrates genomics, sensors, AI algorithms, and high‑performance computing.
  • Barriers: Legal, societal, financial hurdles; crucial to gain farmer trust before large‑scale impact.

Key Data: Not quantified in the talk, but the speaker referenced a national AI‑agri centre that consolidates data pipelines and computational resources.

Recommendation: Build trusted, farmer‑centric platforms that combine AI insights with local knowledge; address regulatory and financing gaps early.

4. AI‑Enabled Personalised Education – Ms. Meirav Zerbib, Deputy Director‑General for Innovation & Technology, Ministry of Education

4.1 Vision & Strategic Pillars

  • Vision: “Flourishing at every level” – an AI‑driven education system that personalises learning for each student, teacher, and school.
  • Four Pillars (aligned with Oxford AI readiness):
    1. Human Capital – Competency taxonomy from basic AI literacy to advanced AI scientist pathways.
    2. Infrastructure – Nationwide bots (Q2 bot for grades 4+, Notebook 11 and Gemini for secondary students).
    3. Regulation – Sandbox framework for risk‑based AI governance in schools.
    4. Innovation – Ongoing pilots, hackathons, and the 720 Personalisation Project.

4.2 The 720 Personalisation Project

  • Four‑layer personalised system: Separate AI agents for students, teachers, principals, and administrators, all interconnected.
  • Student Journey Example (Maya):
    • Onboarding captures interests & learning style.
    • AI builds a dynamic learning path, adapts in real‑time, and surfaces strengths/weaknesses.
    • Educators receive holistic dashboards (attendance, progress, predictive outcomes).
  • Outcomes: Faster, data‑driven decisions; increased engagement; early intervention before challenges become entrenched.

4.3 Regulatory Sandboxes

  • Risk Framework: Multi‑stakeholder committee defines categories (technological, pedagogical, professional identity) and mitigation strategies.
  • Implementation: Experiments are co‑run with industry, local authorities, and teachers; continuous monitoring informs evidence‑based regulation.

4.4 International Collaboration – The Jerusalem Declaration

  • Adopted by 15 countries at Education 2026; calls for AI‑integrated education and global partnership.
  • The speaker invites India to become the 16th signatory, underscoring the bilateral drive for AI‑enabled learning.

Key Insight: Israel treats AI in education as a systemic, regulated ecosystem, not just a set of isolated tools.

5. AI and the Future of Work – Ms. Inbal Mashash, Director General, Israeli Employment Service

  • Framing: Israel views AI as a strategic engine rather than a disruptive threat.
  • Adoption Landscape:
    • 95 % of high‑tech employees use generative AI tools vs. 18 % in other sectors.
    • Geographic & socioeconomic peripheries lag behind, revealing human‑capital and firm‑capability gaps, not purely technological ones.
  • National Strategy – Multi‑Level Pathways:
    1. Basic AI exposure – Safe, productive use of language/image models for all workers and job‑seekers.
    2. Workflow Integration – Embedding AI into processes with governance and outcome tracking.
    3. Advanced Tools & Upskilling – Data‑science, automation, AI‑security training linked directly to job outcomes.
    4. Domain‑Specific Applications – Health, finance, public services, deployed in secure environments.
  • Labour‑Market Dynamics: Faster occupational transitions, need for modular micro‑courses, continuous skills refresh.
  • Employment Service Role: Acts as a bridge linking job‑seekers, skill frameworks, employers, and the training ecosystem.

Recommendation: Target double‑periphery regions with public‑policy‑driven AI upskilling and accessible tooling to avoid deepening inequality.

6. AI as a Co‑Scientist – Dr. Victor Gosalker, Ministry of Innovation, Science & Technology

  • Introduced the “Scientist Productivity Paradox” – despite more researchers, productivity plateaus.
  • Three Perspectives on AI & Science:
    1. Impact of AI on scientific practice (hypothesis generation, literature synthesis, experimentation).
    2. AI research driven by scientific challenges (advancing AI itself).
    3. Using AI to accelerate science (the speaker’s focus).
  • AI Tools Mentioned: Copilot, AlphaFold, large language models (LLMs).
  • Paradigm Shift: AI moves from tool to co‑scientist, akin to microscope or telescope in history.
  • Israeli Initiative: The Ministry aims to develop AI‑dedicated scientific products and seeks India‑Israel collaboration for joint discoveries.

Key Insight: The future of research is human‑AI partnership, requiring policy support for co‑creative workflows.

7. The Israeli AI Industry Stack – Mr. Avner Vilan, COO, AI21

  • Ecosystem Analogy: “It takes a village to raise a child; it takes an ecosystem to raise a global AI leader.”
  • Full‑stack Capability: Israel controls all layers of the AI stack:
LayerExampleRole
FoundationSovereign compute clusters (GPU farms)Provide research‑grade hardware for domestic innovation.
MuscleChip designers – Habana Labs, HaloBuild AI‑specific silicon.
BrainAI21 (LLMs, agent orchestration)Develop foundation models and application‑ready software.
ValueSector‑specific solutions (agri, edu, health, etc.)Deploy AI in real‑world domains.
  • Stakeholder Map: Regulators (policy), Academia (knowledge), Private sector & Public sector (deployment).
  • Industry Dynamics: Shift from exporting tech to serving the domestic market, propelling Israel toward a trillion‑dollar AI‑driven economy.
  • Multinational R&D Presence: Microsoft, Google, NVIDIA, etc., with significant AI chip work occurring in Israel (e.g., NVIDIA’s core AI chips).
  • Innovation Pipeline: Start‑ups spin out from core AI companies; 250‑person AI21 has already seeded five start‑ups.

Vision: Transform Israel from “startup nation” to “AI nation”, focusing on impact over hype and inviting global partners (India) to join the ecosystem.

8. AI‑Driven Digital Health Strategy – Mr. Yol Ben Or, Director, Digital Health Division, Ministry of Health

  • Two Core Goals: (1) Redefine health‑care delivery – AI must reshape models, not just augment them.
    (2) Growth engine – Position health sector as a catalyst for AI‑company expansion globally.

  • Three Pillars of Strategy:

    1. Data – Early digitisation (30 years) created silos; the Health Data Portability Law now standardises interoperable data for AI.
    2. Regulation – Shift from product‑centric regulation to risk‑management by health organisations; develop AI governance frameworks.
    3. Transformation – Deploy AI use‑cases; differentiate “obvious but complex” (e.g., large‑scale discharge‑summary generation) from “moonshots” (e.g., AI‑generated prescriptions).

  • Regulatory Sandbox: Ongoing work to allow high‑impact, higher‑risk AI pilots under controlled oversight.

Key Insight: Successful AI health innovation hinges on robust data pipelines, self‑regulated risk frameworks, and careful scaling of complex use cases.

9. Closing Remarks – Mr. Faris Saib, Deputy Chief of Mission, Israeli Embassy, New Delhi

  • Expressed gratitude to the AI Summit organizers, Israeli delegation, and Indian partners.
  • Re‑affirmed that Israel and India together form a powerful engine for AI‑driven humanity’s future.
  • Invited continued collaboration across government, private sector, and academia.

Key Takeaways

  • Strategic Vision: Israel aims to be among the top three global AI nations, linking innovation tightly with national security, quality of life, and international cooperation (especially with India).
  • Three‑Domain Approach (AI Directorate): Real‑life labs, cyber‑secure AI foundations, and edge‑computing deployments are the primary levers for rapid impact.
  • Sector‑Specific AI Applications:
    • Agriculture: Precision farming, digital twins, and genomics accelerate sustainable yields while reducing inputs.
    • Education: A four‑pillar framework (human capital, infrastructure, regulation, innovation) underpins the 720 Personalisation Project, delivering adaptive learning pathways.
    • Employment: High‑tech adoption is widespread, but geographic/peripheral gaps require targeted upskilling and AI exposure programs.
    • Science: AI is transitioning from a tool to a co‑scientist, reshaping hypothesis generation and experimentation.
    • Industry: Israel’s full‑stack AI ecosystem (compute → chips → models → applications) is unique and increasingly domestic‑market focused.
    • Health: Data interoperability, risk‑based self‑regulation, and sandboxed pilots are essential to embed AI in care delivery.
  • Governance Model: Israel favours agile, risk‑based sandboxes over heavy‑handed regulation, enabling fast yet safe AI deployment across sectors.
  • International Collaboration: The Jerusalem Declaration on AI in education and multiple calls for partnership signal Israel’s intent to co‑create AI solutions with India and other nations.
  • Human Capital Emphasis: From basic AI literacy for all students to advanced AI scientist tracks, Israel invests heavily in skill pipelines to sustain its AI leadership.
  • Impact‑First Mindset: Across talks, the recurring mantra is “impact over hype” – building trustworthy, locally‑deployed AI that solves real‑world problems rather than chasing buzz.

See Also:

Graph View

Backlinks