The Complete Guide to Using AI in the Real Estate Industry in Chile in 2025

Chile's 2025 market sits at a crossroads - Santiago is penciled in for roughly 5% growth with about USD 8,000M in transactions while multifamily and rental segments rebound, creating fertile ground for PropTech and AI adoption; read the market snapshot at Adventures in CRE for the full picture.

At the same time, a booming AI-in-real-estate sector (global forecasts put the 2025 market in the low hundreds of billions) means local firms can use machine learning, NLP and computer vision for AVMs, chatbots, price engines and IoT-driven utility management to speed valuations, cut paperwork and tighten underwriting (see the global AI forecast).

For agents, developers and municipal planners in Chile the

so what

is simple: AI can turn slow permit queues and a tight supply of buildable land into faster, data-driven decisions that preserve value - and professionals can gain those practical skills in targeted programs like Nucamp AI Essentials for Work bootcamp registration.

Chile's 2025 market is a study in contrasts: modest headline price gains (Global Property Guide reports residential prices up about 2.32% YoY in Q3 2024) sit alongside a clear demand slowdown and a construction collapse that leaves developers cautious, which is why AI moves from “nice to have” to “practical necessity.” Sales through Q1–Q3 2024 fell roughly 15% to about 29,858 units while building permits plunged year‑on‑year, yet pockets of recovery - Adventures in CRE projects ~5% growth for Santiago with ~USD 8,000M in transactions - suggest targeted, data-driven tools can pick winners from weak supply and long sales cycles.

AI-powered AVMs, permit‑processing automation and portfolio analytics help convert slow signals (stock-to-sell and unusually long Greater Santiago months-to-sell of ~30.8) into faster, localized pricing and underwriting decisions; Trading Economics also shows building permits improving in mid‑2025 (4,484 units in June) and a rising House Price Index (160.90 in June 2025), signaling openings where timely models and smarter lead scoring can shave weeks off closings and reveal cheaper land parcels before competitors do.

For Chilean agents and developers, that “so what” is a competitive edge: better forecasts, fewer wasted permits and more disciplined risk pricing.

Chile's AI landscape in 2025 is best described as actively building a rulebook while nudging industry to get ready: the national Política Nacional de Inteligencia Artificial 2021–2030 (led by the Ministry of Science, Technology, Knowledge and Innovation) frames three pillars - enablers, adoption and ethics/regulation - while the May 7, 2024 AI Bill adopts an EU‑style, risk‑based approach that promises transparency, human oversight and new compliance duties; read a clear summary at the OECD AI Policy dashboard for Chile's 2021–2030 AI Policy.

At the same time, commentators warn the Bill faces local limits - an embryonic Personal Data Protection Agency with unclear powers, unanswered liability questions and even a risk rating that could bar tools “used daily” in business - points drawn out in an in‑depth analysis of Chile's proposal (In-depth analysis: Chile's AI Bill facing local limits).

For Chilean real estate this means opportunity and chores: sandboxes, SME support and governance requirements can accelerate trustworthy AVMs, underwriting and permit automation, but firms should plan for audit trails, risk assessments and documentation as compliance moves from optional to essential.

Top practical AI use cases for the Chilean real estate industry cluster around fast, data-driven valuation, risk and portfolio tools: automated valuation models (AVMs) provide instant, locally calibrated price estimates and confidence intervals that help agents and investors move from intuition to evidence in days rather than weeks - local work comparing AVM methods in the Santiago Metropolitan Region shows machine‑learning approaches and hedonic pricing with spatial adjustments can improve precision and interpretability (Automated Valuation Models in the Santiago Metropolitan Region - PLOS ONE study).

Real‑time portfolio analytics and ESG/financial indicators let developers monitor at‑risk or recovering assets and prioritize scarce capital (Real-time AVM and portfolio analytics for real estate developers), while rental AVMs and ensemble models speed due diligence for buy‑to‑let strategies and underwriting.

Best practice in Chile will blend these models with human appraisal and local market rules - think of spotting a mispriced Providencia flat before the morning café crowd - so teams should pilot AVMs on specific districts (Providencia, Ñuñoa, Greater Santiago) and validate outputs against local comps and site inspections (Automated Valuation Models for Providencia - implementation and case study).

AI‑powered valuations and mortgage underwriting in Chile hinge on locally tuned data and proven model recipes: automated valuation models (AVMs) that combine hedonic pricing, spatial adjustments and ensemble methods can deliver instant UF/m² price estimates with confidence intervals - useful when the Greater Santiago apartment benchmark sits around 69.5 UF/m² and houses near 56.9 UF/m² (see the local benchmark at Adventures in CRE) - and studies show machine‑learning approaches improve precision and interpretability for Santiago districts (PLOS ONE study: Automated Valuation Models (AVMs) for Santiago real estate).

For mortgage underwriters, feeding AVMs with rental market signals (multifamily average rents ~0.265 UF/m², high occupancy rates) and portfolio analytics speeds debt sizing and stress tests while preserving human oversight; ensemble rental and sale models shave appraisal time and reveal outliers - imagine flagging a mispriced Providencia flat before the café opens.

Operationally, Chile's expanding compute and cloud capacity under the National Data Center Plan means models can be trained on richer datasets domestically, lowering latency and compliance friction while enabling real‑time scoring and audit trails that lenders will soon require (Trade.gov: Chile National Data Center Plan and data center expansion).

Beyond valuations and underwriting, Chilean property managers and developers can squeeze outsized value from AI by pairing IoT sensors, edge analytics and governance to cut energy use, lower operating costs and meet ESG goals - exactly the shift Frost & Sullivan identifies as central to 2025 strategies for smarter, greener buildings (Frost & Sullivan report: AI automation and ESG strategies for homes and buildings (2025)).

Practical wins in Chile include AI-driven HVAC and lighting schedules that respond to occupancy, predictive maintenance that flags failing assets before tenant complaints spike, and digital twins for portfolio-level energy audits; Cohesion's smart-building playbook shows how integrated BAS, smart access and maintenance workflows turn sensor streams into timely action (Cohesion smart-building playbook: IoT and AI transforming real estate).

The result is tangible: fewer emergency repairs, measurable reductions in energy intensity and a tenant experience that rewards sustainable buildings - picture an AI that notices a chiller trending toward failure and schedules a fix before the Monday morning commute feels the chill.

Streamlining permits, due diligence and urban planning in Chile can start with practical pilots that mirror successful municipal experiments abroad: cities are already using AI to cut wait times and pre‑check designs (see municipal pilots in Los Angeles and Austin for context), and California's statewide “e‑check” rollout shows how computer vision, machine learning and automated rulesets can turn a process that once took weeks or months into approvals in hours or days - an outcome Chilean municipalities could target by deploying plan‑validation tools tied to cadastral and zoning datasets.

Operational wins are straightforward: automated code‑checks and rule engines can flag incomplete submissions, a permit dashboard can create real‑time visibility of application status for developers and planners, and parcel‑level analytics can speed urban planning by surfacing underused land before competitive bids bid up prices.

These efficiency gains come with guardrails: legal reviews, human‑in‑the‑loop signoffs and audit trails should be baked into pilots so AVM‑style confidence intervals and automated decisions remain defensible in court and administration - lessons drawn from recent legal and federal permitting debates emphasize careful governance as a prerequisite for scaling.

We're thinking critically about a host of issues that AI in permitting raises - under a legal framework currently reliant on human review.

Chile's tooling and vendor scene is shifting from concept to concrete pilots: local startups and regional proptechs are being backed by a national AI push and meaningful capital, so buyers and developers can now choose between in‑country model training, cloud providers and niche AVM or smart‑building partners; the Chile generative AI market grew to about USD 85.7M in 2024 and - at a projected CAGR north of 30% - is expected to reach roughly USD 459.2M by 2030, which helps explain why vendors are launching Chile‑focused products (see the market outlook at Grand View Research generative AI market outlook).

Investors and vendors are responding: public and private plans - including a reported US$26B investment program tied to the national AI policy - are accelerating talent, data access and commercial offerings across IT, cloud and sensors, according to DataCube's market tracker, and that momentum is visible in proptech case studies and pilots across Latin America.

Equally practical is infrastructure: Chile hosts dozens of data centers (58 today) and a National Data Center Plan that foresees further capacity and a US$2.5B buildout, meaning models can be trained and scored domestically with lower latency and clearer compliance paths (see InvestChile National Data Center Plan details).

For real estate teams this translates into three vendor playbooks to evaluate - local model builders for AVMs and underwriting, BMS/IoT integrators for energy and maintenance, and municipal SaaS for permit automation - each supported by growing capital, domestic compute and real Chilean case studies that make pilot‑to‑scale paths realistic and repeatable.

Adopting AI in Chilean real estate is a practical, phased exercise: start with tight pilots on high‑value use cases (AVMs, lead scoring, predictive maintenance), build a clear data strategy and pick tools that let models be retrained locally, then test and scale - steps echoed in implementation guides like Zealousys' roadmap for real estate AI. Expect upfront line items for data engineering, model development and governance rather than only software licences; factor in compliance costs too, because the draft Chilean AI bill requires authorisation, a risk‑management/data plan and event logging for high‑risk systems and sets a 60‑day review window (non‑compliance can trigger a 200 UTM fine, roughly USD $14,000) - see a practical legal summary at HGomez Group.

The upside is material: the global AI in real estate market is sizeable (about USD 301.58 billion in 2025 with a strong projected CAGR), and Chile's leading ILIA score (73.07) means infrastructure and talent are already comparative advantages for faster time‑to‑value.

Plan pilots that measure lift (reduced days‑to‑close, lower vacancy, predictive maintenance savings), budget for governance and audits up front, and treat compliance as part of deployment costs to protect ROI and unlock scale.

Chile's path to practical, responsible AI in real estate now boils down to three clear next steps: (1) start tight, measurable pilots - AVMs for districts like Providencia, permit‑validation tools and predictive maintenance - so teams can “catch the wave” of mispricings and efficiency gains before competitors do; (2) bake governance and sustainability into every deployment because the draft AI Bill is pioneering yet imperfect (see a careful legal read of Chile's AI Bill at Legal analysis of Chile's AI Bill) and new rules (including Article 7's high‑risk framing and Decree No.

12) elevate environmental impact and require greener compute practices (read about the push for “green AI” at Why Chile must move toward green AI); and (3) upskill staff quickly with practical, workplace‑ready training - teams can get hands‑on with tools, prompts and governance in courses like Nucamp's AI Essentials for Work bootcamp registration, then measure ROI in reduced days‑to‑close, lower vacancy and fewer emergency repairs.

Start with a one‑quarter pilot, document audit trails for compliance, favour renewable‑powered data centres where possible, and use local validation to keep models honest - small experiments plus clear governance are the fastest route from pilot to scalable, defensible value in Chile's 2025 market.

“In real estate, you make 10% of your money because you're a genius and 90% because you catch a great wave.” – Jeff Greene