Top 10 AI Prompts and Use Cases and in the Government Industry in Israel

AI matters for government in Israel because a world-class private sector and bold national projects are creating rare leverage: over 2,000 AI companies and a 173% rise in active AI firms since 2014 signal deep talent and commercial capacity, while the National AI Program is rolling out infrastructure like a proposed national supercomputer (~16,000 petaflops) to cut training costs and scale public-sector pilots fast - details tracked in Startup Nation Central's analysis and the Nebius supercomputer announcement.

That combination makes AI a practical lever for faster diagnostics, climate modelling, smart infrastructure and fraud detection across ministries, but the 2025 status report also flags an urgent need to speed government readiness.

For public servants and managers who want action-oriented skills, bite-sized courses such as the AI Essentials for Work bootcamp offer a 15‑week path to learn prompts and tools, while agency leaders should follow the national program and supercomputer rollout to design secure, high-impact pilots (Startup Nation Central report on Israel's AI ecosystem, Science|Business article on the Nebius national supercomputer).

“AI plays a significant role in healthcare, with diverse applications in areas such as medical imaging, electronic health records, robotics, drug discovery, and clinical trials. While these applications hold immense promise for improving healthcare outcomes and efficiency, there are several challenges that need to be addressed for successful adoption, including data privacy concerns, data scarcity, business model complexities, long development cycles in drug discovery, and navigating the regulatory landscape,” notes Kimberly Powell, VP of Healthcare at NVIDIA.

Methodology - selected prompts and use cases were chosen with Israel's public sector realities in mind: a risk‑based filter (flagging high‑impact services such as healthcare, taxation and transport) borrowed from the EU AI Act approach; lifecycle coverage to ensure design, verification, deployment and retirement controls (following ISO/IEC 42001 guidance); and operational checks for data quality, MLOps and continuous monitoring so pilots scale safely.

Emphasis was placed on practical governance artifacts - documented model cards, registries and AI impact assessments - because, as practitioners warn, treating AI like legacy IT “doesn't work” (models change constantly and need end‑to‑end controls).

The shortlist balanced (a) regulatory risk and public‑service impact, (b) feasibility under Israeli procurement and cloud plans, and (c) governance maturity (data lineage, role‑based access, audit trails) highlighted in modern guides.

For readers who want the frameworks behind this screening, see broader governance principles at Dataiku and practical lifecycle rules in AWS's ISO/IEC 42001 guidance, plus MineOS's operational checklist for policies and audits.

“Boards are racing to harness AI's potential, but they must also uphold company values and safeguard the hard‑earned trust of their customers, partners, and employees,” says Dale Waterman, Principal Solution Designer, at Diligent.

The Ministry of Innovation, Science and Technology (MIST) is the engine behind Israel's national AI strategy, tasked by Government Decision No. 212 to knit together strategy, infrastructure and an operating environment that prioritizes talent development, sandboxes and shared assets for public‑sector pilots; the ministry's National AI Program frames this work as: Israel National AI Program (MIST).

Rather than a single AI law, MIST advocates a soft, sector‑specific, risk‑based regulatory path - coordinating with the Ministry of Justice and the Privacy Protection Authority and tracking international norms - as described in the White & Case regulatory review of Israel's approach (White & Case: Israel AI regulatory tracker).

Key milestones include Government Decision 212's initial 550 million NIS allocation and Decision 173's further authorization (up to 500 million NIS) to accelerate research, supercomputing assets and public‑sector pilots, while proposals for a central knowledge center and TELEM sandboxes promise practical governance - though staffing and full funding remain work in progress (TechPolicy: Israel's New AI Policy Primer).

Shaping Israel's AI future

Tel Aviv‑Yafo can unlock faster permit processing, 24/7 citizen support and smarter routing of municipal services with AI chatbots and back‑office automation, but the local legal backdrop makes design choices decisive: public bodies must follow Israel's Privacy Protection Law (PPL) and the Israel Privacy Authority's guidance - including new rules under Amendment 13 that impose stronger security, registration and DPO duties for public entities - see the DLA Piper overview of Israel data protection laws and Israel Privacy Authority guidance for details.

Practical steps for municipal pilots include classifying data by sensitivity, registering city databases when required, running privacy impact assessments for high‑risk flows, and using TELEM sandboxes or staged pilots so conversational assistants learn on synthetic or minimised data before touching resident records; practical sandboxing and predictive analytics approaches are outlined in local rollout guides (TELEM sandbox guidance for secure municipal AI pilots).

A vivid reminder: Israeli municipalities have faced fines for security lapses (Yeruham was fined 10,000 NIS), so treating citizen chatbots as small experiments is risky unless governance, breach reporting and transfer rules are baked in from day one.

“The thing I learned from Joe Rogan is that people want you to take something very complicated and just ask basic questions.” - Abed Abu Shehadeh

AI can sharpen diagnostics, triage and resource allocation in Israel's health system by powering digital diagnostics, clinical decision‑support and remote monitoring while predicting staffing and bed needs, but deployment depends on a tightly regulated pathway: AI/ML health tools are treated under the Medical Devices Law and MOH oversight, clinical validation is pivotal, and privacy rules plus the new Medical Information Mobilization Law limit secondary uses of HMO data (HMOs hold most health records and may only use them for treatment, public health or research).

Practical rollout steps for ministries and hospitals include following MOH guidance on ML in medical technologies, meeting ISO information‑security expectations, and building interoperability (FHIR) into pilots so models can learn from anonymised, standardised records rather than raw patient files.

For programme owners, the “so what?” is simple - the technology's promise to cut diagnostics time and optimise scarce ICU capacity will only translate into safer, scalable services if clinicians, regulators and privacy authorities sign off on clinical evidence, data governance and security (see the ICLG Digital Health Laws chapter and recent White & Case tracking of Israel's sectoral AI policy, plus MOH guidance on AI‑driven trials for operational validation).

“The vision of the digital health strategy as published by the Ministry of Health is to enable a leap in the healthcare system so that it will be a sustainable, advanced, innovative, renewable and constantly improving health system, by leveraging the best available information and communication technologies.”

The Israel Tax Authority's recent probe into Tim International Transport - accused of smuggling, under‑reporting prices, filing false customs declarations and evading VAT on Alibaba/AliExpress imports that were routed through leased, concealed warehouses and then distributed without proper invoices - underscores how sophisticated cross‑border chains and fake invoices can siphon millions from the treasury (Ynet coverage: Israel probes major tax fraud tied to Alibaba and AliExpress).

That case, and long‑running concerns about bogus invoice networks and MTIC‑style schemes, makes a strong operational case for data‑driven tools: e‑invoicing and reverse‑charge reforms create richer transaction streams that can feed anomaly detection, automated invoice‑matching and risk‑scoring models to prioritise audits and customs inspections.

Digital VAT refinements and apps that digitise refund flows also promise big‑data insights for fraud protection, so pilots in TELEM sandboxes and predictive operational analytics can safely test alerts, linkage of shipment-to-invoice records, and clustering of suspicious actors before scaling agency-wide deployments (Israel21c article on ReFundit app for digital VAT refunds and analytics).

A vivid reminder from the Ynet coverage: consolidated shipments and hidden warehouses cut costs and delivery times - but also mask the paper trail investigators need.

“What began with a great flourish will end with a faint sound.”

Israel's Ministry of Education has stepped from pilots into scale with a first‑of‑its‑kind regulatory sandbox - backed by an initial 10 million shekels - that lets local EdTech firms build, test and deploy AI‑driven, personalized learning tools directly in public classrooms, targeting thorny problems like teacher shortages, inequality and overcrowded rooms (AI sandbox for public education).

The ministry's approach pairs real‑world pilots with regulatory flexibility so adaptive platforms can prove they boost engagement and learning efficiency; early figures already show more than 110,000 teachers trained and hundreds of thousands of students exposed to smart learning tools.

On the ground, home‑grown systems such as AMIT's LMS demonstrate what personalization looks like in practice - interactive modules (a lesson on Yona that opens with a digital map and music), AI chatbots for out‑of‑hours practice, mentor dashboards and one‑to‑fifteen mentoring ratios - so the promise becomes tangible, not theoretical, for classrooms across Israel.

“This is just the tip of the iceberg,” said Education Minister Yoav Kisch.

Israel's Ministry of Transportation can turn AI from promise into pavement-level gains by pairing modern signal‑timing science with the country's sandboxing and data plans: traffic signal synchronisation and corridor‑wide optimisation methods (a Rolling Horizon approach with adaptive large neighbourhood search) have been shown to boost throughput and adapt to changing demand in recent ITS research (IEEE ITSC 2024 corridor configuration optimisation methodology), while broader reviews of traffic‑signal control highlight how microsimulation, reinforcement learning and metaheuristics help minimise delay, queue lengths and emissions across intersections (ETRR review of traffic-signal control methods: microsimulation, RL and metaheuristics).

Practically, pilots should stitch together real‑time feeds (including future V2X streams), microsimulation validation and staged TELEM sandboxes so corridors can be tuned safely - imagine offsets and green times calibrated so a morning convoy glides through five signals with far fewer stops, cutting idling and emissions.

That mix of optimisation algorithms, simulation validation and controlled pilots gives planners a credible path from lab models to smoother, safer Israeli streets.

Israel's Privacy Protection Authority is signaling that AI projects in government must be built with privacy baked in: the draft guidance makes clear that the Privacy Protection Law applies across an AI system's lifecycle and demands a lawful basis for processing, elevated disclosure (including telling people when they're dealing with a bot), robust accountability (DPIAs, a designated privacy officer and privacy‑by‑design), and specific technical safeguards against AI risks such as inference attacks.

Practical consequences for ministries and pilots are concrete - update consent notices, limit training data and vendor use, map all AI flows, and treat web scraping as high‑risk (unauthorised scraping can be deemed a “severe security incident” that must be reported), because what starts as a research scrape can quickly become a regulatory breach.

For a plain‑English read of the draft see Pearl Cohen's briefing on the PPA's approach and Gornitzky's helpful implementation checklist for organisations preparing DPIAs and generative‑AI policies.

“The draft outlines how key privacy law principles apply to AI, such as requiring a legal basis for processing personal data, transparency and disclosures.”

Home Front Command's edge in emergency response depends on stitching together streams - satellite imagery, drones, thermal cameras, weather feeds, traffic sensors and social posts - so commanders see a single, actionable picture when minutes matter; information fusion techniques used in natural disaster management can turn noisy, siloed inputs into near‑real‑time assessments that prioritise evacuations and resource staging (information fusion techniques for natural disaster management).

Practical tools - real‑time situational awareness dashboards that ingest radar, traffic and IoT sensors - help EOCs brief teams, track field units and anticipate needs as an incident evolves (real-time situational awareness dashboards for emergency operations).

Commercial solutions that marry alerts, continuity plans and automated workflows compress the response‑to‑recovery loop so officials can activate assistance, map affected populations and begin recovery faster (FusionRM situational awareness approach for business continuity and crisis management).

The upshot for Israel: fused geospatial and multimodal analytics don't just speed decisions - they create the kind of granular, time‑sensitive visibility that can mean getting medical teams to a cut‑off neighborhood before roads fail, turning data into saved lives rather than delayed reports.

Israel's military intelligence blends old‑school signals craft with cutting‑edge AI: Unit 8200 - the Military Intelligence Directorate's main information‑gathering arm - develops and fields tools that feed real‑time analysis to commanders and, in some recent conflicts, machine‑assisted systems such as Lavender, Gospel and Where's Daddy that flag and locate suspected militants for targeting; the scale is striking (reports say Lavender flagged roughly 37,000 potential targets, and early sampling showed high but imperfect accuracy), which is why the IDF's emphasis on fast human verification is so consequential when seconds count (IDF Military Intelligence Directorate (Unit 8200) overview).

That same pipeline - intense selection, rapid technical training and close ties to industry - explains why 8200 alumni power Israel's cyber‑startup scene, but it also sharpens ethical and legal questions about automation in life‑and‑death decisions; independent reporting and analysis trace both the operational gains and the controversies around precision, oversight and civil‑liberties risks (Investigative reporting on Lavender, Gospel, and targeting practices, Unit 8200 history and cyber pipeline transcript (Darknet Diaries)).

The bottom line: human–machine teams can magnify reach and speed, but even a small percentage of misclassification at scale turns into large, real‑world harm - a vivid reminder that verification, transparency and legal safeguards must travel as fast as the signals do.

“Human bottleneck for both identifying new targets and making decisions to approve them.”

For the Ministry of Justice the clearest early wins lie in administrative automation - smarter e‑filing, searchable digital case files, metadata extraction and AI‑assisted legal drafting that speed routine workflows without touching judges' core decisions - lessons drawn from Europe stress starting small and practical rather than chasing headline projects.

Marco Fabri's review of European e‑Justice shows repeated success when courts automate repetitive, high‑volume tasks (payment orders, small claims, case‑management) and warns against overambitious “robot judge” myths like the Estonia story; that caution pairs well with fielded pilots such as IBM's OLGA assistant, which demonstrates how automated case categorization and metadata extraction can shave time from back‑office processing while leaving verification to humans.

Israel's rollout should mirror that incremental playbook: pilot e‑filing and document‑automation in TELEM sandboxes, build interoperable registries and training for clerks and magistrates, and treat predictive tools as decision‑support - tested, transparent and reversible - so efficiency gains don't erode fairness.

For agencies mapping a path, a practical phased roadmap for Israeli deployments can help sequence governance, procurement and MLOps so pilots mature into secure, auditable services without breaking the rule‑of‑law safeguards that matter most.

“keep it simple” is still a mantra in ICT development.

Ready to start? For beginners in Israel the smartest path is small, practical and compliant: study the draft Privacy Protection Authority rules and the 2023 Responsible Innovation policy so pilots respect elevated disclosure and data‑minimisation requirements (see the PPA-focused overview at AI Regulation Israel: PPA draft & Responsible Innovation overview), align projects with the Israel National AI Program official website priorities and TELEM sandbox guidance, and run simple risk checks (DPIAs, role‑based access, and clear vendor rules) before any real data touches a model.

Treat early experiments as staged TELEM pilots - use synthetic or minimised data, log decisions, and plan human‑in‑the‑loop reviews so what begins as a research scrape never becomes a reportable incident.

At the same time, build practical skills: a focused course like the AI Essentials for Work bootcamp (15-week Nucamp course) teaches promptcraft, tool use and workplace applications in 15 weeks, which helps teams move from concept to governed pilot faster.

Start with one use case, document assumptions, involve legal/privacy officers early, and iterate - Israel's sectoral, risk‑based approach rewards careful, well‑documented pilots that can scale safely.