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

Peru's hotels are feeling the same AI tide sweeping the industry worldwide: market forecasts put AI in hospitality at roughly $20.4B in 2025, and operators from Lima to Cusco are eyeing tools that boost revenue, automate routine front‑desk work, and deliver hyper‑personalized stays, from dynamic pricing during festival surges to multilingual chatbots that free staff to craft memorable guest moments.

Industry analyses on the top hospitality tech trends for 2025 flag connected guest platforms, predictive revenue models, and contactless experiences as priorities for hotels that want to compete - and local properties can start small with pilots that target occupancy, guest loyalty, and back‑office savings.

For hoteliers or managers aiming to lead those projects, practical training matters: the AI Essentials for Work bootcamp teaches workplace AI skills, prompts, and real use cases to turn strategy into action.

Learn more from the market forecasts, the trend playbook, and hands‑on training to make AI a measured advantage in Peru's 2025 hospitality scene. AI in Hospitality Global Market Forecast 2025 - The Business Research Company, Hospitality Technology Trends 2025 - Publicis Sapient analysis, and the AI Essentials for Work bootcamp registration (Nucamp) provide practical starting points.

Program	Details
AI Essentials for Work	15 weeks; learn AI tools, prompt writing, and job‑based AI skills; early bird $3,582, regular $3,942; AI Essentials for Work syllabus (Nucamp) • AI Essentials for Work registration (Nucamp)

Peru's national AI strategy is anchored in Law 31814, a risk‑based framework that aims to spur innovation while protecting rights - think clear rules for transparency, mandatory human oversight on critical systems, strict data governance, and even outright bans on certain uses (for example, real‑time biometric identification in public spaces is tightly restricted).

The law, positioned under the Presidency of the Council of Ministers and implemented by the Secretariat of Government and Digital Transformation (SGTD), sorts AI into prohibited, high‑risk, and acceptable‑risk buckets, requires documentation and traceability for higher‑risk tools, and pairs safeguards with innovation measures such as a national AI sandbox and public‑private training programs; practical compliance steps for hotels include risk classification, human‑in‑the‑loop controls for guest‑facing automation, and stronger data‑minimization practices.

Law 31814 first took effect in July 2023 and its Regulations - published in September 2025 - set phased timelines for public and private sectors, sectoral grace periods for compliance, and obligations like internal AI policies and impact assessments that hospitality operators should build into procurement and vendor contracts to avoid surprises when a seasonal revenue‑management bot becomes subject to high‑risk rules.

For authoritative detail see the Nemko overview of Law 31814, the OECD official initiative summary, and the Lexology regulations approval note.

Item	Detail
Law enacted	5 July 2023 - Law No. 31814
Regulations published	9 September 2025 - Supreme Decree No. 115‑2025‑PCM
Entry into force	90 working days after publication (≈ January 2026)
Lead authority	PCM – SGTD (Secretariat of Government and Digital Transformation)

Peru's 2025 AI outlook is increasingly driven by booming data‑center investment that turns local hotel AI pilots into scalable services: market research shows the Peruvian data‑center sector was valued at about USD 130B in 2023 and, at a roughly 15.5% CAGR, is forecast to swell toward USD 310B by 2029 - while other industry briefs cite a near‑term milestone of roughly USD 200.5B by 2028 - signals that capacity and colocation options will finally catch up with demand.

Increased connectivity (early 5G rollouts), major logistics projects like Chancay and airport expansion, and government plus private projects already being mobilized mean more on‑shore compute, lower latency, and better redundancy for hotels that want real-time dynamic pricing, multilingual guest assistants, or AI‑driven housekeeping schedules that scale during Inti Raymi and Fiestas Patrias.

Analysts also note an AI investment shift into new markets, so hospitality operators in Lima and beyond should expect easier access to colocated infrastructure, professional service partners, and cooling/power solutions - all essential when a boutique hotel suddenly needs to double its booking‑engine throughput during a holiday surge.

For snapshots of the market and infrastructure plans, see Arizton/market analysis and reporting on Peru's data‑center rise, Vertiv's overview of Peru as a growing destination for data‑center investment, and recent BNamericas coverage on projects moving in 2025–2027.

Metric	Value
2023 market value	USD 130 Billion
2028 projection (Arizton, cited)	USD 200.5 Billion
2029 projection	USD 310 Billion (≈15.5% CAGR)
Existing colocation facilities	~10 (mostly concentrated in Lima)

For Peruvian hoteliers the future of AI in 2025 is pragmatic and guest‑centric: expect hyper‑personalisation to become baseline, AI to automate repetitive front‑desk tasks, and predictive models to tighten revenue during festival surges like Inti Raymi and Fiestas Patrias so small properties can scale without blowing budgets.

Practical moves include unifying guest data into a single CRM to power real‑time offers and mobile‑first upsells, adding multilingual chatbots and voice assistants to serve international travelers, and layering AI into housekeeping and energy schedules so staffing and rooms flex automatically when demand spikes - turning messy guest breadcrumbs into tailored pre‑arrival and in‑stay experiences that drive loyalty.

Technology trends to watch are precise, data‑driven personalization engines (see Hotelbeds' take on hyper‑personalisation), integrated guest platforms and digital wallets for seamless check‑in, plus marketing automation that converts insights into direct bookings; vendors and operators should prioritize clean data pipelines because the ROI of recommendation engines and dynamic pricing depends on reliable inputs.

For practical inspiration and implementation guidance, Revinate's overview of AI in hospitality and Publicis Sapient's trend playbook offer clear roadmaps for turning pilots into predictable revenue.

Metric	Value (Global study)
AI in hospitality market (2024)	USD 0.15 billion
AI in hospitality market (2025)	USD 0.23 billion
Forecast CAGR (2025–2029)	57.6%

“AI means nothing without the data.” - Karen Stephens, Revinate

Key AI use cases for hotels operating in Peru center on guest-facing automation and smart operations that actually matter during seasonal surges: AI chatbots and virtual concierges (for example, solutions covered in the Nucamp guide to hotel chatbots and virtual concierges) provide 24/7 multilingual support, instant booking and reservation changes, and personalized upsell prompts that drive direct bookings and higher spend; AI concierges that integrate with PMS and booking engines automate service requests, table and tour reservations, and real‑time call routing so front‑desk staff can focus on high‑touch moments; dynamic pricing engines and revenue‑management models tune rates for Inti Raymi and Fiestas Patrias demand spikes and protect margins while increasing occupancy; predictive housekeeping and staff‑scheduling tools convert check‑out patterns into optimized cleaning runs and labor plans; internal AI knowledge bases speed staff responses and reduce training time; and analytics/recommendation engines turn guest profiles into timely offers and loyalty drivers.

Vendors vary on language support, integrations and handover to human agents, so pick solutions that guarantee PMS/CRM hooks, secure guest data handling, and local channels like WhatsApp.

“These virtual concierges are available 24/7, providing seamless service with little effort.” - viajesitaloperu.com

For practical how‑tos and Peru examples, see the Nucamp hotel chatbot primer for Peru and the Nucamp festival dynamic pricing guide for hotels.

Practical compliance checklist for hotel AI projects in Peru: start by classifying each tool under Law 31814's risk-based categories (unacceptable, high, or acceptable risk) so chatbots, dynamic‑pricing engines, or biometric systems get the right controls; embed mandatory human‑in‑the‑loop supervision and clear explainability for anything touching guest rights or critical decisions; document design, data sources and decision logic with traceability and retain impact assessments and related records for the minimum retention periods called out in the rules (three years for key documentation); adopt strict data‑minimization, enhanced consent and cross‑border transfer controls for training data and guest profiles, and schedule regular data audits for high‑risk systems; build internal AI policies, staff training and a named governance team (Digital Security Officer / Data Governance Officer) to meet SGTD/PCM oversight expectations; plan for sectoral phased compliance timelines and potential verification/certification steps before deployment, and prepare incident reporting workflows and civil liability measures required by the framework.

For the legal framing and the approved Regulations see the Nemko overview of Peru Law 31814's risk‑based approach and the Lexology summary of Supreme Decree No. 115‑2025‑PCM approving the Regulations.

Checklist item	What hotels should do
Risk classification	Map systems to prohibited/high/acceptable risk per Law 31814
Human oversight & explainability	Design stop‑gaps and user notices for high‑impact decisions
Documentation & retention	Keep design logs, impact assessments and traceability records (min. 3 years)
Data governance	Enforce minimization, consent, audits and cross‑border limits
Governance & training	Appoint officers, adopt internal AI policies, and train staff
Deployment & certification	Plan for verification/certification and phased sector timelines
Security & liability	Implement incident reporting and assess civil liability/insurance needs

Turn AI ambition into bookings and better service by building a tightly staged roadmap that balances people, process, and tech: secure executive sponsorship, form a cross‑functional team (IT, revenue, ops, legal, and guest‑services) to break silos and keep projects aligned, and start with high‑impact, low‑complexity pilots such as multilingual chatbots and dynamic pricing engines that prove value quickly - then scale.

Treat data readiness as a non‑negotiable: inventory guest records, standardize a single CRM, and automate ETL so models train on clean, auditable inputs; pair that with clear governance, human‑in‑the‑loop controls, and production‑grade monitoring to avoid the common pitfalls that stall 70% of AI projects.

Choose an infrastructure path (cloud, on‑prem or hybrid) based on latency, compliance and cost, adopt MLOps for safe rollouts, and lock in continuous training and change management so staff become collaborators not bystanders.

Expect a realistic cadence - many enterprises plan 18–24 months from strategy to stable operations - and blend structured training with hands‑on experimentation so talent grows as the stack does.

For practical frameworks and team best practices see HP's AI implementation roadmap, the Agile Business Consortium on cross‑functional teams, and HSMAI's guidance on training and talent for hotel AI adoption.

Phase	Typical duration
Phase 1: Strategic alignment	2–3 months
Phase 2: Infrastructure planning	3–4 months
Phase 3: Data strategy	4–6 months
Phase 4: Model development	6–9 months
Phase 5: Deployment & MLOps	3–4 months
Phase 6: Governance & optimization	Ongoing

Peru's hotels need an infrastructure playbook that matches the ambition of new guest experiences: on‑shore compute and reliable colocation to keep latency low, robust 5G/modern broadband to support real‑time concierge agents, and secure cloud or hybrid platforms that let multilingual AI agents, dynamic pricing, and predictive operations run without lag or risky data transfers - Nemko's guide to Peru's AI regulation highlights the country's push for national data centers and stronger telecom capabilities to support this shift (Peru AI regulation overview - Nemko).

At cultural destinations such as Machu Picchu, AR/VR, smart crowd‑management, and GPS‑based safety systems show how immersive previews and crowd smoothing can scale without harming sites; virtual pre‑tour platforms even make travelers 70% more likely to book, a vivid reminder that the guest experience depends on both bandwidth and curated content (Machu Picchu technology features and virtual pre‑tour impact).

Equally important are secure payments, tokenization and agent‑level transaction controls for AI commerce, and integration standards so PMS/CRM, scheduling, energy and housekeeping systems share clean, auditable data - hotel‑grade AI vendors and platforms that focus on multi‑channel messaging, scheduling and monitoring help tie this stack together (AI for hotels: key platform capabilities - Conduit).

The takeaway: pair local compute and network resilience with privacy‑by‑design data flows and tested vendor integrations to turn pilots into reliable, guest‑facing services.

Infrastructure need	Why it matters
On‑shore data centers / colocation	Lower latency, compliance with data‑localization and heavy inference workloads
High‑bandwidth connectivity (5G/fiber)	Supports AR/VR, real‑time agents, and seamless check‑in experiences
Secure cloud/hybrid platforms	Enable scaling, tokenized payments, and audited model pipelines
Smart crowd & safety systems	Manage visitor flows, emergency response, and preservation of sites
Clean, integrated data pipelines	Drive accurate personalization, dynamic pricing, and reliable ML models

“As we enter the era of AI commerce, it's pivotal to have brands and products innovating in this space that users already know, trust and are comfortable with. We're excited to partner with Visa in this next wave of the internet.” - Dmitry Shevelenko, Perplexity

Preparing people, training, and governance is the single most practical way Peruvian hotels turn regulatory pressure into competitive advantage: Law 31814 and its Regulations make internal AI policies, role assignments, and staff training mandatory (with human‑in‑the‑loop controls and trained personnel able to halt or correct high‑risk decisions), so hotels should name a Digital Security Officer or Data Governance Officer, map who has the authority to stop an automated recommendation, and run recurring, role‑based exercises that pair front‑desk, revenue and legal teams with IT. Training should cover risk classification, explainability basics, enhanced consent practices and strict data‑minimization rules tied to ANPDP requirements, while governance practices must capture traceability and impact documentation (kept for at least three years) and link into the SGTD/PCM oversight channels; practical supports include Peru's national AI sandbox and CNIDIA programs for capacity building.

Because the Rules phase in across sectors on staggered timelines (private sector windows range from one to four years and MSEs receive differentiated timelines), start with high‑impact, low‑complexity training - multilingual front‑desk scripts for human handover, incident reporting drills, and vendor‑contract checklists - and scale to certified processes as timelines approach.

For regulatory detail and implementation guidance consult the Peru AI regulation overview by Nemko and the Regulations approval note on Supreme Decree No. 115‑2025‑PCM from Lexology.

Role / Area	Practical next step
Named officers (Digital Security / Data Governance)	Appoint owners for AI policy, audits and vendor oversight
Human oversight	Train staff authorised to halt or correct high‑risk AI decisions
Documentation & retention	Record design, data sources and impact assessments (min. 3 years)
Staff training	Role‑based modules on ethics, consent, explainability and incident reporting
Timing & compliance	Align training cadence with sectoral phase‑in (1–4 years; MSEs 2–3 years)

Peru's AI roadmap for hospitality closes with a clear bottom line: the upside of smarter pricing, chatbots and predictive ops comes with strict guardrails - Law 31814's risk‑based regime expressly bars “unacceptable” systems (think subliminal manipulation, social‑scoring and restricted biometric uses), mandates human oversight, transparency, robust data governance and incident reporting, and pushes verification, audits and sandboxes as part of safe rollout; practical mitigations include rigorous risk classification, human‑in‑the‑loop controls, data‑minimization and traceable documentation to meet regulator expectations and avoid enforcement or civil liability exposures highlighted in policy briefs.

Recent regulatory moves sharpened the checklist (draft rules proposing visible labelling of AI‑generated content and lifecycle security measures are part of the consultation history), so hotels should treat compliance as part of product design, procurement and staff training rather than an afterthought.

For operators ready to act: lean on authoritative guidance (see the Nemko Peru AI regulation overview and the Access Partnership analysis of Peru's draft AI bill), build governance and incident workflows now, and pair those with practical skill development - courses like Nucamp AI Essentials for Work bootcamp teach prompt writing, tool use, and workplace AI practices that turn compliance requirements into operational routines.

The pragmatic takeaway: align pilots to low‑risk, high‑value use cases, document everything, train named owners, and use sandboxes and certified verification pathways to scale with confidence.

Top regulatory risk	Practical mitigations
Unacceptable practices (subliminal manipulation, social scoring, certain biometric ID)	Avoid such designs; perform legal triage and prohibit deployment
High‑risk systems (biometrics, critical decisions)	Human oversight, explainability, impact assessments, audits
Data governance & security	Minimize data, document sources, enforce cross‑border controls, report incidents
Market entry & compliance	Plan for verification/certification, use regulatory sandboxes and maintain traceability

“AI regulation requires organizations to report AI‑related security incidents to the National Digital Security Center.” - Nemko overview of Peru's AI regulation

Nemko Peru AI regulation overview - AI regulation in Peru | Access Partnership analysis - Peru AI bill and governance framing | Nucamp AI Essentials for Work bootcamp - registration