Canadian Renters Are More Comfortable With Building AI Than You Think

Canadian renters are more open to AI than you think: what operations teams should do now

For years, the default stance on AI in buildings has been caution. We expected the same when we reviewed simplydbs' 2025 Canadian Multi-Residential Satisfaction Study. The data went the other way. Most renters are comfortable with AI in building operations, including tools many assumed would be contentious, like facial recognition.

Across applications such as predictive maintenance, security systems, and operational efficiencies, roughly 60% to 75% of renters reported comfort or neutrality. "Comfort" here includes essential, nice to have, or indifferent. That's a wide permission slip for operations leaders to improve service and reduce friction, while still being mindful about privacy and consent.

Purpose matters more than age

No single age group was consistently the most accepting or the most resistant. Acceptance shifted by use case. That's the headline.

Older renters showed the highest comfort with AI surveillance that flags suspicious behaviour: about 80% of renters aged 70+ were comfortable, compared with 64% of renters aged 19-29. Flip the scenario and the pattern changes. For AI chatbots that handle amenity bookings, renters aged 30-39 were roughly 15 points more comfortable than those 70+.

Some tools drew steady support across ages. AI-assisted background checks, rental history verification, and energy-saving suggestions all scored consistently high comfort. These are seen as practical, low-risk, and clearly useful.

Ops takeaway: Select use cases based on clear resident value. Safety features resonate more with older populations; digital self-service shines with younger renters. Don't make age the strategy-make the use case the strategy.

Provincial differences exist, but use case still leads

Geography didn't create fixed attitudes either. Comfort changed by application. That said, Quebec posted the highest overall comfort across all 15 AI applications in the study. British Columbia showed some of the lowest overall comfort, yet still a majority position across applications.

The same three use cases topped both Quebec and British Columbia: package delivery management, personalized notifications (rent, maintenance, community updates), and predictive maintenance. Even in a province with lower overall comfort, renters aligned on what's most valuable.

Ops takeaway: Standardize a core stack around those three. Localize messaging, consent flows, and rollout plans by province, but keep the value story consistent.

What this means for building operations

• Prioritize high-utility use cases first: Start with package delivery management, predictive maintenance, and personalized resident notifications.
• Match features to resident profiles: Buildings with older populations: spotlight security benefits and human oversight. Younger buildings: emphasize speed, self-service, and 24/7 availability.
• Build privacy by design: Collect less data, store it for less time, and use on-device processing where possible. Offer clear opt-outs and non-biometric alternatives.
• Vendor due diligence: Ask for Canadian data residency options, PIPEDA/Law 25 readiness, SOC 2 or equivalent, false-positive rates (for surveillance), bias testing, and audit logs.
• Transparent communication: One-page resident briefs, lobby signage for visible tech, and office hours for questions. Keep it plain language.
• Define success upfront: Track MTBF, work orders per suite, response times, package loss rate, false alarm rate, energy per suite, and resident CSAT/NPS.
• Plan for fallbacks: Maintain non-digital workflows, staff override paths, and access options for residents without smartphones.
• Pilot, then scale: Run a 60-90 day pilot across 2-3 properties. Measure, adjust, then roll out by cohort.
• Model total cost: Include software, hardware, training, resident comms, privacy reviews, and change management-plus savings from avoided truck rolls and faster turnarounds.
• Upskill your team: Train site staff on the "why," the process, and the exceptions. Short resident how-tos reduce ticket volume. For structured learning, see role-based options at Complete AI Training.

Compliance checkpoints in Canada

You'll want a clear path through Canadian privacy requirements (PIPEDA federally; Quebec's Law 25; BC and Alberta's PIPA). If you're evaluating facial recognition or similar tools, consult guidance from the Office of the Privacy Commissioner of Canada to align early with expectations.

OPC guidance on facial recognition

• Complete a privacy impact assessment before launch.
• Minimize data, set strict retention, and define clear purposes.
• Offer meaningful opt-out paths and non-biometric alternatives.
• Provide signage and a plain-language notice for residents and guests.
• Prevent function creep with locked-down access and audits.
• Establish an easy complaint and redress process.

A simple decision grid for your roadmap

Use a two-by-two: value to residents vs. data sensitivity. Start with high-value, low-sensitivity. For high-value, high-sensitivity, add stronger controls and transparency. Skip low-value, high-sensitivity unless there's a compelling safety case with community support.

• High value, low sensitivity: Predictive maintenance, package delivery management, personalized notifications.
• High value, high sensitivity: AI-aided surveillance, facial recognition (only with strict safeguards and alternatives).
• Moderate value, moderate sensitivity: Background checks and rental verification (standardize criteria and explain the process).
• Convenience tools: Amenity chatbots and self-service-great fit where digital habits are strong.

What's next

Part II (next week) will dig into differences by citizenship, income, and life stage, with takeaways for both tenants and multifamily owners and operators. For now, the signal is clear: renters will support AI that solves real problems and respects their privacy.

If you've been waiting for resident buy-in to move forward, you likely have it-use cases first, controls in place, and outcomes measured. Line up your pilots, define your KPIs, and keep the communication open.