Sam Humphreys, head of M&A at Dwelly, discusses how artificial intelligence (AI) is transforming the lettings sector by streamlining operations and enhancing service.
How is Dwelly leveraging AI to streamline the lettings process, and what tangible benefits does this bring for brokers, landlords, and tenants?
At Dwelly, AI is embedded across the entire property management lifecycle – from tenant find through to rent collection and maintenance. For tenant matching, our AI is available 24/7 to answer enquiries, score applications, and surface the most suitable candidates for landlords, making the process faster and more transparent for everyone involved.
For maintenance, issues are logged, categorised, and prioritised automatically, with the AI routing requests to the right staff member or contractor and keeping all parties updated throughout. The results speak for themselves: maintenance resolution times in the UK average around 50 days, and we’ve already cut that by 33%, with a target of 70% reduction. That kind of improvement directly reduces the risk of tenants leaving early due to unresolved issues, protects the landlord’s asset, and frees agents to focus on higher-value work rather than chasing updates.
In what ways can AI help brokers and other property professionals save time or reduce administrative burdens when dealing with lettings?
The administrative burden in lettings is enormous – chasing documents, logging maintenance, routing calls and emails, scheduling contractors, following up on rent. AI can handle much of this automatically and consistently. For maintenance alone, the impact of triage is significant: AI categorises the issue, requests the right information upfront, and routes it to the correct person, cutting out the back-and-forth that causes delays.
Beyond that, AI supports rent reviews by analysing comparable properties, historic tenancy data, and market movement to produce evidence-based recommendations rather than guesswork. For tenant screening, AI gathers structured information from applicants and flags affordability concerns and risk indicators before a negotiator even looks at it – the agent still makes the final call, but with better data in a fraction of the time. The overall effect is that agents stop firefighting and start making proactive decisions.
How does AI contribute to improving the quality of service and communication between agents, landlords, and tenants in the current market climate?
Good AI is largely invisible to the end user – landlords and tenants simply notice faster response times, clearer updates, and more information available to them. One of the biggest service failures in traditional lettings is that agents are reactive rather than proactive, because capacity constraints leave them swamped. When AI absorbs the routine workload, agents can focus on preemptive maintenance, better tenant selection, and genuinely managing the landlord’s investment rather than just reacting to problems.
AI is also a reliable nudger – it doesn’t forget, doesn’t get distracted, and always keeps the full context of a situation in mind. If an agent speaks to a contractor on a call, AI can prepare notes, record deadlines into the CRM, and issue follow-up notifications automatically. That consistency is hard to achieve at scale with human teams alone, and it meaningfully improves the experience for all parties.
Are there any concerns or misconceptions about AI in property management, and how does Dwelly address these to ensure trust and transparency?
The most common concern is around data – and it’s a legitimate one. Letting agents handle sensitive financial and personal information, and GDPR applies regardless of whether AI is in use. The real risk isn’t AI itself, but agents using consumer-grade tools like public versions of ChatGPT and inadvertently feeding tenant data into unsecured systems. At Dwelly, we ensure data is handled within compliant, purpose-built infrastructure rather than general consumer platforms.
On transparency, AI actually improves it in many areas: tenant selection today often relies on gut feel, which is where discrimination and inconsistency creep in. By using anonymised data and auditable algorithms, AI makes decision-making more justifiable and easier to evidence. The UK AI framework requires safety, transparency, accountability, and contestability – and that means any AI making or supporting decisions must be explainable, not a black box. We build with that principle in mind.
What future developments or innovations in AI do you foresee having the biggest impact on the UK lettings sector?
The industry is at the very beginning of this shift – right now, AI adoption among letting agents is practically non-existent beyond basic tools like email drafting. The agencies that move first will be able to grow and scale in ways that weren’t previously possible, handling higher volumes of tenants, landlords, and maintenance requests without proportionally increasing headcount. Those that don’t make this transition will increasingly find themselves acquired by larger groups and tech-native businesses who are already investing heavily.
Looking ahead, the biggest impact will come from AI that operates end-to-end across the full tenancy lifecycle – not just individual tasks, but the connective tissue between landlord, tenant, agent, and contractor.
We’re also expecting significant advances in predictive maintenance, arrears risk identification, and dynamic rent pricing, all of which shift the agent’s role from administrator to strategic advisor. The agents who thrive will be the entrepreneurial ones – not necessarily the most technical, but the ones who ask the right questions and use these tools to keep improving.
