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

Peru's retail future in 2025 sits at the crossroads of big opportunity and clear guardrails: since the enactment of Law 31814 (July 2023) the country has adopted a risk‑based AI regime that demands transparency, human oversight and data governance for high‑impact systems - think credit scoring, biometric ID and automated hiring that retailers sometimes rely on - so local chains must balance innovation with compliance (Peru AI regulation overview (Law 31814)).

With implementing rules published in the Official Gazette in 2025, retailers can no longer treat AI as experimental; documented risk assessments and explainable models are business necessities (Peru AI regulation implementing rules published in the Official Gazette (2025)).

At the same time, practical AI use cases - like hyper‑local, real‑time personalization across touchpoints to boost basket size or computer‑vision loss prevention in brick‑and‑mortar stores - offer concrete cost savings and growth paths for Peruvian retailers (AI real-time personalization use cases for Peruvian retail); imagine a Lima storefront that swaps promotions by neighborhood while logging human review - small tech steps with big customer impact.

AI is non‑negotiable for Peruvian retailers in 2025 because the technology has moved from experimental to mission‑critical: global forecasts show the AI‑in‑retail market climbing sharply (about USD 11.61B in 2024 to roughly USD 14.49B in 2025), which drives vendor focus and competitive pressure on local chains (Global AI in Retail Market Outlook - Grand View Research); concurrently, adoption is accelerating - estimates suggest retailers using AI could jump from roughly 40% to as high as 80% by late 2025 - delivering concrete benefits like inventory accuracy, dynamic pricing and personalization that translate into measurable savings and revenue uplifts (AI in Retail Adoption and ROI Data - StartUs Insights).

For Peru, those macro trends have local teeth: region‑aware personalization (Lima, Arequipa, Iquitos) and computer‑vision loss prevention are practical, proven levers that raise basket size and cut shrink - so a tienda that swaps banners and prices by neighborhood or flags suspicious returns in real time stops leakages and wins customers; this is why, beyond regulatory compliance, AI is now a strategic cost‑saver and growth engine rather than a nice‑to‑have (Peru-Specific AI Retail Use Cases and Prompts).

Peru's national AI strategy is built around Law 31814 - a clear, government‑led push to make AI safe, transparent and socially beneficial while still encouraging innovation: the law (and its 2025 implementing rules) set a risk‑based framework with prohibited uses, high‑risk classifications, mandatory human oversight, strengthened data governance and centralized oversight under the Secretariat of Government and Digital Transformation (SGTD) attached to the Presidency of the Council of Ministers; see the Peru AI Law 31814 overview and key provisions for the basics (Peru AI Law 31814 overview and key provisions).

The regulations published in the Official Gazette in September 2025 operationalize those principles and add practical tools - a national AI sandbox, a National Centre for Digital and AI Innovation (CNIDIA), labelling and explainability duties, and phased sectoral timelines - so firms in finance and health face one‑year compliance horizons while commerce and labour have two years to adapt, giving a Lima retailer a predictable 24 months to certify dynamic‑pricing or cashier‑less systems before stricter oversight applies (Peru AI regulation published in the Official Gazette Sept 9 2025; Supreme Decree No. 115-2025-PCM summary of Peru AI regulations).

The strategy balances promotion (sandboxes, public cloud, training and R&D) with enforcement (risk assessments, documentation, traceability and, where relevant, verification/certification), so retailers can plan concrete, compliant AI deployments rather than guessing where the rules will land.

The Peru draft regulation - circulated by the Secretariat of Government and Digital Transformation (SGTD) for public consultation in 2024 - turns Law 31814's broad, risk‑based mandate into practical rules that matter for retailers: the May–June 2024 consultation and follow‑up rounds set out a clear classification ladder (unacceptable, high, medium, low), specific prohibitions (think subliminal manipulation, certain real‑time biometric uses) and operational duties such as lifecycle security measures, algorithmic audits, incident reporting and enhanced transparency for automated decisions (Peru AI draft regulation public consultation May–June 2024); these provisions mirror the law's intent to balance innovation with rights protections and track regional trends toward EU‑style risk rules (Overview of Peru Law 31814 AI risk-based framework).

For retailers that plan to deploy dynamic pricing, cashier‑less kiosks or computer‑vision loss prevention, the upshot is concrete: document risk assessments, embed human oversight and be ready to prove explainability and security before moving from pilot to production, because the draft also contemplates verification, certification and sanctions that would make noncompliant deployments costly and hard to scale.

Peru's retail and fintech operators must navigate a tightly woven regulatory overlay where payments, AML and consumer protection meet the new AI rulebook: the Central Reserve Bank of Peru (BCRP) drives payment‑system rules - interoperability, card payment agreements, e‑money and even the CBDC pilot - while the Superintendencia de Banca, Seguros y AFP (SBS) supervises banking conduct, authorisations and the fintech sandbox that limits which players can pilot regulated services (Peru fintech regulatory guide 2025 (Chambers Practice Guides)).

At the same time UIF‑Perú enforces AML/CFT obligations (suspicious‑activity reporting, KYC) and INDECOPI polices consumer protection and pricing transparency for digital lenders and marketplaces, with the Autoridad de Protección de Datos Personales (APDP) overseeing personal data rules.

Layered on top is Law 31814's risk‑based AI framework - mandatory risk assessments, human oversight and explainability for high‑impact systems such as credit scoring or fraud detection - so a Lima tienda that rolls out dynamic pricing or a cashier‑less checkout must not only plug into BCRP‑regulated rails and AML checks, but also document explainability and data governance to avoid sanctions (Peru Law 31814 AI regulation overview (Nemko)).

The practical point: map regulatory touchpoints early - payments registration, UIF reporting, clear consumer disclosures and APDP compliance should be part of any AI deployment plan, not an afterthought - because technical wins can quickly turn costly if governance is missing.

Peruvian retailers can pick practical, high‑impact AI plays that map directly to local realities: start with hyper‑local, real‑time personalization (swap banners, tailor emails and offers for Lima, Arequipa or Iquitos customers) to nudge basket size and repeat visits - see the Real‑time Personalization playbook for Peru (Real-time personalization playbook for Peruvian retail); pair that with smarter stock control and demand forecasting to keep shelves aligned with regional tastes and avoid costly overstocks (inventory and predictive analytics are core Gen‑AI wins).

Convenience stores and grocers should prioritize dynamic pricing and electronic‑shelf‑label experiments to protect margin while automatically discounting near‑expiry perishables, a practical ROI lever in price‑sensitive Peruvian neighbourhoods (Generative AI dynamic pricing and electronic shelf labels - Publicis Sapient).

In stores, computer‑vision loss‑prevention and cashier‑less checkouts cut shrink and speed throughput - pair automated detection with clear human review and explainability so deployments stay compliant and trusted (Computer vision loss-prevention use cases for retail in Peru).

Add conversational shopping assistants for grocery and virtual try‑ons for apparel to lift conversion online, but build them on a cleaned, unified customer dataset first: without that data foundation, even great use cases stall.

A focused portfolio of pilots - personalization, forecasting, dynamic pricing, computer vision and conversational assistants - lets Peruvian retailers move from experiments to measurable KPIs while keeping human oversight and explainability at the center.

“If retailers aren't doing micro-experiments with generative AI, they will be left behind.” - Rakesh Ravuri, CTO at Publicis Sapient

Peruvian retailers preparing AI pilots should follow a tight, Peru‑specific compliance checklist rooted in Law 31814: first, categorise each system under the risk ladder (unacceptable / high / medium / low) and document that decision in a retained record; second, run and keep lifecycle risk assessments and recommended impact assessments (minimum 3 years of retention) and treat them like audit receipts; third, embed mandatory human oversight with trained staff able to halt or correct automated decisions; fourth, deliver transparency - clear labelling, explainability and traceability of models, data sources and decision logic; fifth, lock down data governance: enhanced consent, minimisation and cross‑border safeguards in line with Peru's personal data rules and ANPDP supervision; sixth, implement security controls and a reporting channel for AI incidents to national digital security authorities; seventh, plan for verification/certification and civil liability/insurance where required; and finally, map sectoral timelines so deployment meets phased deadlines (e.g., health/finance: 1 year; commerce/labour: 2 years) rather than scrambling later.

These steps echo the law's risk‑based bedrock and give retailers a practical path to innovate without trading away compliance (see the Law 31814 overview, the implementing Supreme Decree, and the Official Gazette notice for full context).

Peru AI regulation Law 31814 overview - Nemko
Supreme Decree No. 115-2025-PCM implementation guidance - Lexology
Peru AI regulation Official Gazette publication - DataGuidance

Peruvian retailers should treat AI adoption as a phased, measurable journey rather than a one‑off experiment: begin with Discovery (identify high‑ROI use cases such as hyper‑local personalization or computer‑vision loss prevention and map regulatory touchpoints), move to Prototype/MVP to test a single market (try swapping digital banners in one Lima aisle to see AOV and click lifts), then run a Pilot in select stores or regions, scale the winners across the chain, and finally embed governance and continuous optimization into operations - this six‑phase approach (discovery → prototype → pilot → scale → integration → governance) matches proven guidance for retail and keeps risk manageable while producing clear KPIs (pilot→production conversion rate, time‑to‑value, AOV uplift, forecast error reduction, shrinkage cut, and model drift alerts); note the common trap - 80–85% of companies stall at PoC, so insist on go/no‑go gates and defined success thresholds from day one (see a concise Strategic Roadmap for AI Implementation for the Proof‑of‑Concept reality) and plan for a typical 18–24 month enterprise timeline with phase gates and MLOps in place (HP's implementation roadmap).

Start small, measure often, and expand only when KPIs prove sustainable - this keeps innovation compliant, practical and profitable in Peru's regulated 2025 landscape (pilot ideas for Lima, Arequipa and Iquitos are a good place to begin).

Strategic Roadmap for AI Implementation in Retail | AI Implementation Roadmap: From Infrastructure to Services to Applications (HP) | Real-time Personalization across Touchpoints (Peru)

Technology choices for Peruvian retailers hinge on a practical build‑vs‑buy calculus: buy when speed‑to‑value matters and proven vendors can deliver quick pilots (3–9 months), build when AI is a core differentiator that demands full data residency and custom control, and use a hybrid mix for regulated or sensitive functions - guidance well captured in HP's Enterprise AI build vs.

buy framework (HP Enterprise AI Services: Build vs. Buy guide). For Peru, that means vetting vendors not only for features and TCO but for security and compliance (look for AES‑256 encryption, SOC‑2/ISO attestations and clear data‑processing locations) and mapping their services against local regulatory touchpoints; nearshore development in Latin America can speed custom work while keeping collaboration close - see practical nearshore advantages in HatchWorks' guide (Build vs Buy and Nearshore software development guide - HatchWorks).

Start pilots with high‑impact, low‑risk plays - real‑time personalization or computer‑vision loss prevention - so a Lima grocer can test neighborhood‑specific banners or shelf‑label swaps before full rollout (AI Essentials for Work bootcamp syllabus - Nucamp); the memorable test: trade a week of printed shelf tags for a dashboard that flips promotions by barrio and watch AOV move within days, provided vendor SLAs, portability and export rights are contractually protected.

Peruvian retailers must treat AI risk and ethics as operational imperatives: beyond the clear business upside of personalization and loss‑prevention, the New Regulation to the Personal Data Protection Law now forces concrete duties - designation of a Personal Data Officer in many cases, mandatory security documentation, and breach notifications for large incidents (NDPA notification can be required within 48 hours) - so preparedness isn't optional (Peru Personal Data Protection Law and New Regulation - DLA Piper).

The National Centre for Digital Security (CNSD) is the coordination point for digital‑security incident handling, making quick, tested incident response plans essential for any cashier‑less or computer‑vision rollout (National Centre for Digital Security (CNSD) Peru - Cybersecurity Intelligence).

Workforce change is real - self‑checkout and cashier‑less models shift roles rather than erase them - so pair automation pilots with reskilling: short, practical programs such as the 15‑week AI Essentials for Work course equip floor managers and merchandisers to own human oversight, prompt engineering and vendor governance (AI Essentials for Work 15‑week syllabus - Nucamp).

Quick‑start action items: classify systems on the national risk ladder, map regulators (NDPA, CNSD, BCRP/SBS/INDECOPI where relevant), lock down lifecycle security and breach playbooks, appoint or plan for a DPO if thresholds apply, and run small, human‑in‑the‑loop pilots with measurable KPIs - remember that fines can escalate into six‑figure soles for severe breaches, so the cost of doing nothing can be substantial.

The practical win: short, disciplined steps protect customers, preserve trust, and make AI a durable competitive advantage in Peru's regulated 2025 market.