Beyond the hype: Property funds unlocking real AI value

AI is playing a bigger role in areas like investor communications, compliance processes, property management and more for unlisted property funds. But whether AI delivers on its promise depends not just on tools but mindset, according to a recent industry panel discussion on AI as part of the PFA 2025 Conference held on the Gold Coast.
The panel was moderated by Larry Rudman, founder of business systems consultancy, Lincoln Ruby, which specialises in software solutions for property funds. Larry is also Business Development Partner for Agora, a leading investor management platform for property funds.
Larry was joined by Alice Tang, a Senior Financial Services Executive with over 25 years’ experience, including 16 years at Macquarie Group, where she held senior leadership positions in real estate investment and funds management, and Tom Veron, a Manager at property management software specialists, Yardi.
To ground the discussion, Larry offered a straightforward definition: “At its most basic level, AI is a combination of business rules embedded in software, fed by data, and designed to produce a relevant and meaningful output.”
Three real-world AI use cases in funds management
Alice Tang, who has implemented AI tools and has discussed AI uses with senior executives across the industry, explained three use cases which have worked well in funds management:
- Investor Query Handling: In many firms, investor queries get passed from distribution to investment teams and back again, creating delays and inefficiencies. “By building a chatbot trained on your fund and strategy’s offer documents and investor reports you can automate much of this. It reduces friction and speeds up communication”, Alice said.
- Automated Investor Reports: With data already housed in internal systems, AI tools can generate automated investor reports. “If you have your data already in a data warehouse, that can easily go into the graphs and all those things that generate your standard report, and then AI can be trained in your tone of voice to write it.”
- Extracting Data from PDFs: Whether reading compliance documents or valuation reports, AI can now extract complex information with high accuracy. “For a project I recently worked on, the AI tool could correctly identify 93% of relevant dates on a wholesale investor certificate, so it’s working well at gathering information”, Alice said.
The industry pulse and AI adoption trends
Tom Veron shared insights from Yardi’s long-running annual survey with the Property Council of Australia. The survey tracks AI sentiment among over 160 firms—and shows clear momentum.
“Five years ago, most were in ‘wait and see’ mode. Now, they’re actively exploring,” Tom said. The top three key areas where AI is going to be used includes content generation, administrative automation, and research.
But many firms still face challenges around resourcing and understanding how to implement AI in practice. “People are keen to explore it, but there’s a massive, I guess, barrier to entry because of fundamental resourcing and training. It’s moving so quickly people are not sure how to use it.
“The biggest hurdle is still internal strategy—knowing what to do with the technology once you decide to adopt it.”
The importance of mindset when trialling AI
Larry Rudman said AI success is less about budget and more about culture. “The tools are low-cost and accessible. What matters is the mindset of leadership.”
Teams expecting instant perfection will be disappointed. Instead, leaders must embrace experimentation, tolerate early-stage imperfection, and iterate with purpose.
“Success in this area will depend on the mindset of senior management and the decision makers. If management’s mindset is that it has to be done, and it has to be done quickly, and it has to achieve 100%, you’re probably not going to be that pleased with the outcomes, and you’re probably not going to get there.
“If you have a mindset where you’re happy to take a leap, you’re happy to have an iterative process, and you’re happy to experiment and go and move forward, then you probably have a greater chance of success”, Larry said.
Innovative use cases emerging across the industry
Tom Veron named four key areas where property companies are deploying AI, with potential for meaningful efficiency gains:
- Chatbots for Tenant Communication: This is low hanging fruit for many organisations, he said. “It’s about streamlining the comms with our tenants, whether they be residential, whether they be commercial, so that it reduces the load on the frontline team to have to constantly respond.”
- Lease Abstraction: AI can scan hundreds of leases, identify key clauses, and summarise them. “You will still need, obviously, to go and validate it, but you can import that new asset into your system directly with broader applications into the potential acquisition due diligence phase”, Tom said.
- Predictive Maintenance: AI can analyse service history, and can recommend proactive maintenance, reducing costly reactive repairs.
- Natural Language Reporting: Instead of manually querying ERP systems, teams can now ask plain-language questions, like ‘show top 10 tenants by turnover rent’, and instantly receive a report.
Alice Tang also highlighted several forward-thinking uses of AI already taking shape:
- AI as an Investment Committee Member: “Some super funds are trialling AI as a non-voting ‘black hat’ Investment Committee member, being at the table and testing out the theory.”
- Real Estate Prediction Engines: Agents with access to leasing and sales data are using AI to predict high-performing asset types and geographic trends.
- Retail Forecasting: Alice cited a major retailer, which uses AI to anticipate demand shifts – like stocking up on cold and flu supplies when premium tissue sales spike.
Finally, the panellists’ discussed the low cost entry point when you are using Co-Pilot or a team’s Open AI license, and the ROI that is already being seen by teams who have adopted Gen AI.
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