How AI Is Helping Retail Companies in Israel Cut Costs and Improve Efficiency

Israel's retail sector is ripe for AI: home to hundreds of startups and a National AI Program backed with 1 billion NIS, the country's AI scene now fuels everything from edge vision chips to generative marketing that can shave inventory, staffing and content costs.

Roughly a quarter to a third of Israeli tech startups focus on AI and - according to market analysis - these firms attract nearly half of venture funding, a concentration that accelerates practical retail wins like smarter demand forecasting, in-store computer-vision shrink reduction and automated conversational commerce.

For retailers in Israel aiming to cut costs quickly, the playbook is clear: pair local AI talent and solutions with disciplined data strategy and start small experiments to capture operational savings and faster customer service improvements (see analysis on Israel's AI market and how generative AI transforms retail).

“Retailers should start experimenting now because this technology has the potential for a serious uptick in customer engagement and revenue.” - Sudip Mazumder

Computer vision is turning Israeli aisles into quiet, efficient machines: ceiling-mounted cameras and machine‑vision algorithms - like those developed by Tel Aviv's Trigo Vision - can identify every item a shopper picks up, feed real‑time inventory signals and even help stop shoplifting while eliminating the checkout queue, a model tested by global grocers such as Tesco and rolled out locally when Shufersal opened Israel's first autonomous store in 2022; shoppers simply scan a membership card, walk the store, and the final bill is sent to their account.

These camera‑first approaches (also used by providers catalogued in the Top 15 Checkout Free Stores roundup) offer fast shrink reduction and labor savings, but they also push retailers to balance privacy, integration costs and customer experience - think seamless exits instead of barcode battles at the till.

For Israeli retailers, the immediate “so what” is clear: smarter shelves and vision systems can free staff for service roles while shaving operational costs.

Trigo Vision cashier-less checkout system tested with Tesco: Ceiling‑mounted cameras, cashier‑less billing; partnered to open Shufersal autonomous store (2022)
Overview of global checkout-free solution providers and use cases: Catalogs global vendors and use cases for camera‑based, app and membership entry models

Demand forecasting and inventory optimization are among the fastest ways Israeli retailers can cut costs and avoid stock headaches: local solutions like Predictoos AI inventory management solution bring AI-powered, store- and SKU-level forecasts to the market, while global-style engines such as ForecastSmart retail demand planning software show how ML can boost accuracy and on-shelf availability across hierarchies.

Models that fold in unstructured signals - social chatter, weather, promotions and mobility data - deliver the real advantage, sometimes improving forecast performance by as much as 10–20 percentage points and turning reactive emergency shipments into predictable replenishment cycles, which translates into metrics like 5–20% higher forecast accuracy, 20%+ fewer lost sales and 99%+ on‑shelf availability in vendor claims.

For Israeli chains juggling hundreds of SKUs and tight margins, that means fewer clearance piles, less rush shipping and staff time freed for customer service instead of stock counts; to get there, combine these AI engines with clean channel-level data and quick pilots to prove ROI before scaling.

“Demand is typically the most important piece of input that goes into the operations of a company.” - Rupal Deshmukh, Partner, Kearney

Lowering compute and energy bills starts at the hardware level - and Israel's own Hailo is a leading example of how edge AI can cut costs for retailers by keeping heavy inference off the cloud and on tiny, efficient devices.

Tel Aviv‑based Hailo's new Hailo‑10H brings generative AI and vision‑language models to the point of sale, enabling real‑time personalization, cashier‑less checkout and shrink detection without constant cloud calls, while HP's selection of a Hailo‑10H‑powered M.2 AI Accelerator shows how these chips plug straight into POS and kiosk hardware to save bandwidth and subscription fees (HP selects Hailo's next‑gen AI accelerator to transform retail and hospitality operations).

With on‑device processing that can run 4K video analytics, deliver first‑token latency under 1 second and operate in the ~2.5W range, stores can swap costly cloud compute for low‑power edge boxes that keep PII local and free staff from routine tasks - the “so what” is simple: real‑time insight at the edge turns surveillance cameras and tills into continuous cost‑cutters (Hailo announces general availability of the Hailo‑10H edge AI accelerator with generative AI capabilities).

“With the Hailo‑10H now available for order, we're taking another major step toward our mission of making AI accessible to all. This is the first discrete AI processor to bring real generative AI performance to the edge, combining high efficiency, cost‑effectiveness, and a robust software ecosystem.” - Orr Danon, CEO and Co‑Founder of Hailo

Generative media and marketing automation are becoming practical levers for Israeli retailers aiming to cut creative and operating costs: Harvard Business School research shows LLMs can even stand in for human participants in early-stage market research, making rapid concept testing far cheaper and faster (Harvard Business School research: Generative AI for early-stage market research), while industry playbooks map clear, revenue‑focused use cases from automated content creation to conversational shopping assistants.

Publicis Sapient's rundown of the top generative-AI retail use cases underlines the same point - personalization, automated content supply chains, virtual B2B knowledge helpers and dynamic pricing are all routes to measurable savings, provided retailers invest first in clean customer data and micro‑experiments (Publicis Sapient: Top Generative AI Retail Use Cases in 2025).

Local Israeli digital teams are already turning these ideas into campaigns and case studies that prove out quicker A/B cycles and lower agency hours, so the immediate so what is tangible: imagine hundreds of bespoke product emails and images rolling off an automated pipeline overnight, freeing budget for better in‑store experiences and smarter media buys - the trick is starting small, testing fast, and keeping customer data central (Israeli digital marketing case studies on AI-driven campaigns).

Israeli retailers and payments players can cut fraud-related costs and speed post-purchase workflows by adopting behavioral biometrics that read subtle signals - typing rhythm, swipe pressure, device fingerprints - turning thousands of tiny data points into real‑time risk decisions; Tel Aviv‑based BioCatch, for example, collects more than 3,000 anonymized interaction signals to detect mule accounts, account takeover and social‑engineering scams and has helped prevent billions in losses (BioCatch behavioral biometrics solution).

By surfacing intent at the moment of checkout, apps and merchant portals can automate manual review queues, flag suspicious returns or chargebacks faster, and keep friction low for legitimate buyers - an operational uplift that scales as adoption grows (see growth and Tel Aviv presence in BioCatch press release on ARR growth and Tel Aviv presence).

The practical payoff is straightforward: fewer manual investigations, lower loss rates, and a smoother post‑purchase experience that protects both margins and customer trust.

“We help them recognize opportunities for operational efficiency driven by a commitment to consumer trust, simplicity, and protection.” - BioCatch

Logistics and last‑mile operations in Israel are ripe for practical AI wins: local platforms like Herzliya‑based PrettyDamnQuick (PDQ) give small merchants a turnkey way to run deliveries, while AI-driven route optimization, predictive analytics and dynamic scheduling shave fuel, time and failed‑delivery costs across urban corridors and beyond.

Israeli retailers can pair PDQ‑style orchestration with proven AI tactics - real‑time routing that adapts for traffic and weather, predictive exception detection to prevent missed drops, and customer‑facing ETAs that slash “where's my order” calls - to turn delivery from a loss leader into a service differentiator (see how FarEye maps route optimization and predictive analytics for last‑mile efficiency).

Beyond cost savings, AI helps harden operations against theft and errors and supports future automation (drones and autonomous vehicles) where regulations allow; in real tests, smarter tracking cut customer service calls dramatically, proving the “so what”: fewer returns, fewer repeat trips, and more time for staff to focus on store experience rather than chasing parcels.

For Israeli chains, starting with targeted pilots - local route AI plus merchant platforms - delivers measurable wins fast.

"AI can support last-mile delivery by optimizing truck routes and predicting errors before they occur."

Scaling AI across Israel's retail sector depends as much on money and infrastructure as on startups and use‑case focus: the 2021 National AI Program promised NIS 5.26B but by 2025 only about NIS 1B - roughly 20% - had been released, leaving headline projects like a national GPU cluster largely unbuilt even as Nebius won a NIS 140M tender for a supercomputer (see the Israel National AI Program status update: Israel National AI Program status update); at the same time, targeted public moves such as a new NIS 44M funding call aim to open high‑quality sector datasets that retailers can plug into for demand forecasting and personalization (Israel AI data infrastructure funding announcement: Israel AI data infrastructure funding announcement).

The ecosystem still offers strong private pathways - dense startup activity, specialized edge‑AI chips and marketing tools - so the practical scaling recipe for retailers is pragmatic: pair pilots with local AI vendors, negotiate data‑access deals tied to the new public datasets, and plan for compute gaps rather than assuming immediate national subsidies (analysis of Israel's AI revolution and startup ecosystem: analysis of Israel's AI revolution and startup ecosystem).

Picture a promised national supercomputer on the horizon while shop floors run lean pilots today - get the data right, and the rest scales faster.

“Data is the raw material for training artificial intelligence models that create groundbreaking solutions in many fields.” - Dror Bin, CEO of the Innovation Authority

For Israeli retailers just starting with AI, a pragmatic, low‑risk roadmap beats chasing every shiny tool: begin by defining clear business aims (reduce stockouts, cut support calls, or automate product emails), assess and clean the specific store- and SKU-level data you already have, then run one‑store or single‑category pilots to validate ROI quickly - this staged approach mirrors best practices from enterprise playbooks and helps overcome the knowledge and relevance gaps IDI found (only 28% of businesses reported AI use in the past six months).

Pair small pilots with fast, high-impact GenAI and automation wins - automated customer‑service chatbots and order-ETA messages, templated creative for product pages, or simple demand‑forecasting tests - which private companies can scale without huge upfront spend.

Invest in basic upskilling for staff so AI complements roles rather than replaces them, and lock governance around data and IP from day one. For practical guidance on building an AI plan, see Databricks' stepwise strategy guide, and review Israel's retail tech innovators (like Predictoos and delivery orchestration firms) to find local partners that shorten implementation time.

“Private companies don't need massive scale to get GenAI right.” - Tony Dinola, Grant Thornton

The future of AI in Israel's retail scene looks pragmatic rather than magical: wins will come to retailers who pair disciplined cost management with focused pilots, measurable ROI and staff skills - not to those who chase every shiny model.

Global studies warn that AI brings heavy capital and operating bills and a looming ROI reckoning, so build finance controls and TBM/FinOps practices early (see Apptio analysis on AI costs and ROI).

At the same time, real-world retail evidence shows promise - three‑quarters of gen‑AI retail leaders report ROI on at least one production use case - so start with one high‑impact experiment (see Google Cloud generative AI retail findings).

Practical next steps for Israeli chains: run single‑store pilots that lock in data, measure end‑to‑end savings, and reinvest proven gains into upskilling; short, targeted training such as Nucamp's AI Essentials for Work bootcamp helps teams write better prompts and operate AI tools without a deep technical background (register at AI Essentials for Work bootcamp registration).

The clearest takeaway: treat AI like a capital program - small, measurable bets, strong cost governance, and fast people training - so pilot successes become repeatable, margin‑boosting operations across Israel.