By Alex Vail

The most successful operators are unlikely to begin with futuristic concepts or experimental technology. They are far more likely to start by solving everyday operational frustrations.

As I discovered while researching my book, Data Culture, one of the most persistent myths surrounding AI is that every deployment must be transformational.

The reality is often much less dramatic and much more useful.

Across Build to Rent, many of the highest-value opportunities are emerging in areas that operators already understand deeply: repairs, maintenance, compliance, communications and reporting. The ARL’s recent AI in Build to Rent Guide highlights these as among the most promising entry points because they offer measurable benefits while carrying relatively low regulatory sensitivity.

Take repairs management, for example. Most operators face familiar challenges: high volumes of requests, varying urgency levels, contractor scheduling issues and pressure to improve resident experience, all while trying – in a challenging economic climate – to control costs.

AI has the potential to support maintenance triage, identify likely priorities and improve scheduling efficiency. Similar approaches in other housing sectors have been associated with significant reductions in emergency call-outs and improved operational performance.

Document management presents another opportunity: many organisations devote considerable staff time to locating, reviewing and extracting information from leases, compliance records, policies and safety documentation. The Guide points to evidence showing substantial time savings through document intelligence tools that help categorise and summarise large volumes of material.

Perhaps the most important lesson is that value is never created by AI alone, but by informed humans applying the technology to real-world business challenges.

Having spoken to CTOs, CIOs and operational leaders in the UK’s 300 biggest companies, I can attest to the fact that successful deployments begin with a clearly defined business problem. (Conversely, failed deployments almost always begin with board members or senior executives expressing a fascination about using new technologies.)

The Guide recommends starting with low-risk, high-value operational use cases that build confidence, improve data quality and strengthen governance capability before pursuing more complex opportunities. The financial and operational case for AI in BTR is well-evidenced in adjacent sectors and growing in BTR itself.

The highest-return, lowest-risk use cases are:

• Repairs triage and predictive maintenance – evidenced 15–30% reduction in emergency callout rates in social housing;
• Document intelligence – 60–80% time reduction for lease abstraction and compliance checking in real estate;
• AI-assisted resident communications – 20–40% reduction in call volumes for routine queries;
• ESG and energy analytics – 5–15% energy cost reductions documented in commercial buildings;
• Transparent market-responsive rent setting – void reduction and occupancy improvement evidenced in commercial real estate and hotels.

As I mentioned in my last article, you are almost certainly using AI across your estate already, but if you’re just starting out on your meaningful AI journey – looking to commission or build a bespoke AI-driven solution, it may be helpful to understand that doing a small thing well is infinitely better than doing a big thing badly.

For many rental living businesses, the most valuable AI strategy is probably not focused on a ‘moonshot’ to solve your biggest problems. It may simply be removing friction from the processes your teams deal with every day.

We’ll be talking about this and much more at the AI in Rental Living Summit, taking place in Manchester on 28 September. We’re excited to bring together a host of experts to help our members understand what AI means for their businesses. We hope to see you there!

Register now to secure your place at the AI in Rental Living Summit, Manchester, 28 September.

Alex Vail is the Operations Director at the Association for Rental Living and the author of Data Culture, available from all good bookshops.