The Complete Guide to Using AI in the Retail Industry in Chile in 2025

Chile's retail landscape in 2025 is prime for AI-driven reinvention: the national market sits at about USD 27.16B while regional demand for smarter stores - personalized recommendations, inventory optimization and cashier-less experiences - is accelerating fast, with the Latin America AI-in-retail market at roughly USD 497.74M in 2024 and a projected 29.85% CAGR (Credence Research), and Chile accounting for about 12% of that regional AI spend; see the Credence Research Latin America AI in Retail Market report and the Chile Retail Market Report (ResearchAndMarkets) for details.

Local adoption is driven by e‑commerce and omnichannel growth but held back by skills, privacy and upfront costs, so pilots that prove ROI quickly are essential - imagine shelves that signal restock before an item sells out - and practical reskilling (for example, Nucamp's AI Essentials for Work bootcamp - Nucamp registration) is a fast way to prepare teams for real pilots and compliance needs.

AI matters for Chilean retail because it turns fast-moving trends - rising e‑commerce, demand for seamless omnichannel experiences and mobile payments - into concrete, profitable actions: personalized recommendations, AI-powered chatbots and predictive analytics that tighten inventory and cut waste, and computer-vision driven solutions that enable cashier‑less checkout and automated product scanning.

Credence Research projects the Latin America AI‑in‑retail market to expand rapidly (driven by personalization, IoT integrations and predictive demand forecasting), and Chile already represents roughly 12% of regional AI spend, so local retailers who pilot focused use cases can win measurable gains in service and margin.

The hurdles are real - privacy, upfront costs and skill gaps mean pilots must prove ROI quickly and pair technology with staff reskilling - follow a practical implementation roadmap for Chilean stores that emphasizes quick wins and vendor selection to avoid costly missteps; see the Credence Research analysis and a Chile‑specific implementation roadmap for retailers for next-step guidance.

Walmart Chile's “Al Carro de Líder” rollout shows how a focused pilot can push AI from novelty to everyday convenience: a detachable, clip‑on Shopic device with two cameras turns any trolley into a smart cart that recognizes thousands of SKUs with over 95% accuracy and gives shoppers real‑time totals, tailored discounts and the option to bag items as they go - so instead of queuing for nine minutes at a cashier, many shoppers can finish on‑cart payment in under a minute and simply detach the device on the way to the car.

The rollout to five Lider Express stores across Santiago's Metropolitan Region builds on Shopic's global deployments and highlights measurable front‑end benefits (in some markets, in‑cart promotions have lifted conversion by as much as 36.8%); see Shopic's official announcement about the smart cart rollout and independent coverage by RetailTech Innovation Hub for details on the technology and store list.

“At Walmart Chile, we are committed to helping our customers save money and live better. Implementing new technologies that save time for our customers is one of the ways we bring this mission to life. We are happy to expand into five new districts in the Metropolitan Region, bringing innovation closer to more people, enhancing their shopping experience, and putting a smile on our customers' faces with every visit.” - Frank Eckert, Central Operations Manager at Walmart Chile

Under the hood in Chilean stores, AI combines a lightweight clip‑on device and real‑time computer vision so a standard trolley becomes a data engine: the Shopic unit uses two cameras and on‑device algorithms to recognize thousands of SKUs (Shopic reports >95% visual recognition accuracy) and detects adds/removes nearly instantly - so shoppers see a running total, tailored discounts and can pay on the cart in under a minute instead of queuing for nine, while retailers gain heat maps and inventory signals for quicker restocks; read more in Shopic knowledge hub: smart cart technology and the local Walmart Chile AI smart cart rollout with Shopic.

This “micro‑vision” approach (camera focused on the cart rather than wall‑to‑wall surveillance) reduces store upheaval and privacy exposure, trains on new items via a simple barcode scan, and runs efficiently at the edge - so when a loaf is tossed into a moving cart and the screen instantly updates, the effect is almost tangible: faster trips, fewer stockouts, and richer front‑end analytics for Chilean retailers looking for quick pilots with measurable ROI.

“We need to differentiate between thousands of items, some of which are very similar to one another in an environment with many edge cases. The system is incredibly accurate and user-friendly – it kind of feels like magic. Our algorithms recognize the item itself based on its visual features; all shoppers have to do is place them in the cart as they usually would.” - Eran Kravitz, Shopic CTO and co‑founder

Measuring impact in Chile pilots means picking a short list of practical KPIs, instrumenting them from day one, and validating with real store-level data: start with footfall and conversion rate, then layer in average basket value, items per basket, sales per m², inventory turn and shrinkage (stock loss), plus employee productivity and CAC to balance top-line gains with cost.

Use video counters, POS and smart‑cart/trolley telemetry where available to triangulate results so a reported uptick in conversion is backed by matching footfall and basket data; AI can compress what used to take months into near real‑time signals, letting teams iterate faster and spot issues before they become

empty-shelf

complaints.

Benchmark early pilots against short windows (daily/weekly) and business KPIs (monthly sales per m², inventory turns) and validate with A/B or phased rollouts.

Local analytics firms and specialist tools can accelerate this - see the roundup of Chile vendors for partners and practical expertise, and the Veesion guide for ten essential store KPIs; for why AI helps make these metrics timely and trustworthy, consult the EY analysis on AI and KPI measurement.

Implementation checklist for Chile retailers: start by mapping every AI touchpoint (smart carts, recommendation engines, shelf‑vision, chatbots) and classify each system under Chile's four‑tier risk framework so obligations are proportionate - see the Chile AI Law project framework (Chile AI Law project framework (Janus)); next, run a regulatory gap analysis that documents data lineage, retention, explainability and human‑in‑the‑loop controls, and prepare the documentation, testing and transparency measures required for high‑risk systems per Chile's AI regulation guidance (Chile AI regulation guidance (Nemko)); embed clear vendor due‑diligence and supply‑chain checks (conformity assessments for third‑party models), and design user disclosures for limited‑risk tools like chatbots so customers know when they're interacting with AI. From an ops perspective, treat deployments as production services: implement SLOs/SLIs, observability, incident runbooks, role‑based access and secret management before scaling (follow production‑readiness practices for monitoring, testing and rollback) - roll pilots out phased/A‑B style, instrument KPIs (footfall, conversion, basket size, shrinkage) from day one, and keep human oversight and retrain/validation cycles in place so models don't drift.

The pragmatic path is incremental: small pilots that deliver measurable ROI, rigorous documentation to satisfy auditors, and a scalable GRC/ethics channel to evolve into full governance as AI use grows.

Data governance, privacy and liability are now central constraints and enablers for Chilean retailers adopting AI: the country's draft AI Bill borrows the EU's risk‑based taxonomy but - critically - coexists with a modernized Personal Data Protection Law (Law 21.719) that tightens ARCO rights, mandates DPIAs for high‑risk processing, and creates a national Data Protection Agency with new breach‑reporting and sanction powers, so any smart‑store pilot that ingests customer data or runs automated decisioning must be inventoried, risk‑rated and documented end‑to‑end (see the Chile AI Law project risk framework (Janus) and a practical Chile new data protection law summary).

Gaps remain: commentators warn the AI Bill as drafted leans heavily on a European blueprint and leaves unclear who bears liability when AI causes harm - developer, vendor or operator - while older privacy rules didn't address automated decision‑making, a shortfall the new PDPL tries to fix (analysis at Ius Laboris analysis of Chile AI Bill).

The practical takeaway for retailers: treat AI systems as regulated products - classify risk early, run DPIAs, document data lineage and retention, prepare incident reports and be ready for steep fines or a five‑year entry in Chile's sanctions registry if controls fail - because in Chile in 2025, governance is as important as accuracy for any pilot that wants to scale safely.

Navigating Chile's AI Bill means treating any smart‑store pilot as a regulated product: the draft law adopts an EU‑style, risk‑based taxonomy that can ban “unacceptable” uses, impose strict controls on “high‑risk” systems, and layer in documentation, testing and human‑in‑the‑loop obligations that retailers must prove in audits.

Practical steps include early risk classification, DPIAs for systems that process customer data, and robust documentation of model testing and monitoring - the Nemko guide to Chilean AI regulation lays out these core compliance hooks.

Oversight will sit with new national bodies (a Data Protection Agency and AI authorities) and authorisation processes are expected before market entry - some proposals flag a formal review window (roughly 60 days) for registrations and technical files - so be ready to show a complete risk file before a pilot scales.

The Bill also raises open questions on who bears liability when AI harms people, a point emphasised by Ius Laboris, and penalties can be severe; the safest path for retailers is conservative risk ratings, airtight data lineage, vendor due diligence and a sandboxed rollout that keeps human oversight front and center.

Balancing innovation and regulation in Chilean retail means pushing smart experiments - private‑label expansion, targeted AI pilots like shelf‑vision or cart telemetry, and nimble promotional tests - while reading the hard lessons from product regulation: Chile's retailers have leaned into private labels as a margin and loyalty play (private label revolution in Chile), and the country's strict Food Labelling and Advertising Law has already nudged manufacturers to reformulate products across many categories (BMC Medicine analysis of nutrient changes in Chile), yet those healthier reformulations did not translate into higher consumer prices in early evaluations, a reminder that regulation can steer healthier offerings without killing affordability (Global Food Research detailed findings on Chile food reformulation).

The practical tradeoff for Chilean retailers is tactical: treat pilots as regulatory experiments as well as technical ones - design A/B rollouts that measure reformulation effects, price perception and shelf availability together, and pair any AI rollout with clear consumer disclosures and rapid KPI feedback so innovation earns public trust while staying inside evolving rules (Chile-focused implementation roadmap for retailers).

“A common argument we hear from industry is that regulations like this are too costly and hurt consumers and the economy. We see here that Chile's law did not lead to more expensive prices on healthier options, and we've seen in previous studies that there was no impact on employment or wages.” - Barry Popkin

Voices from store managers, tech vendors and regulators all point to the same pragmatic ending: start small, measure fast and train people to run the new systems - Chile's demos (notably Walmart Chile's Lider Express pilots across the Metropolitan Region) prove it's possible to turn a nine‑minute checkout wait into a sub‑one‑minute exit with a clip‑on smart cart, but scaling safely means DPIAs, phased A/B rollouts, tight vendor due diligence and clear consumer disclosures.

For retailers ready to act this quarter, pick a single high‑impact use case (shelf monitoring or in‑cart telemetry), instrument core KPIs from day one, and use practical playbooks like Nucamp's implementation roadmap for Chilean stores and the Computer Vision Shelf Monitoring prompts to cut shrink and improve availability; for teams that need hands‑on reskilling, the AI Essentials for Work pathway offers a focused 15‑week curriculum to teach prompts, business use cases and operational controls before you expand a pilot.

Treat pilots as both technical and regulatory experiments - document everything, keep humans in the loop, and remember the payoff: faster trips, fewer stockouts and real, auditable ROI that wins both regulators' trust and shoppers' loyalty.

“At Walmart Chile, we are committed to helping our customers save money and live better. Implementing new technologies that save time for our customers is one of the ways we bring this mission to life. We are happy to expand into five new districts in the Metropolitan Region, bringing innovation closer to more people, enhancing their shopping experience, and putting a smile on our customers' faces with every visit.” - Frank Eckert, Central Operations Manager at Walmart Chile