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<\/p>\nAt Salesforce\u2019s Agentforce World Tour in Sydney last week, Geocon CIO Andy Magee delivered a big red warning: the success of agentic AI isn\u2019t about rolling it out \u2013 it\u2019s about testing it in the real world first. <\/p>\n
He believes if you implement it blindly, you risk a combination of customer frustration and lost trust.<\/p>\n
Magee, who is in charge of Geocon\u2019s AI initiatives, told B&T that he wants every customer interaction to feel \u201cunbelievably helpful,\u201d due to the agent \u201calways getting it right\u201d.<\/p>\n
The Australian developer is preparing to launch a new AI sales development agent in Q1, building on what Magee describes as the \u201cmassive impact\u201d of its first production AI agent in customer service. Yet he remains acutely aware of the hurdles, from initial skepticism to outright resistance.<\/p>\n
\u201cWe\u2019re definitely not rushing this,\u201d Magee told B&T. \u201cYou don\u2019t really get to take it back once it\u2019s out there. I\u2019m confident we\u2019ll do this right, and that\u2019s why we\u2019re taking the time\u2014it\u2019s critical when you\u2019re taking this inquiry away from a human initially.\u201d<\/p>\n
No more bottlenecks<\/p>\n
Geocon\u2019s first AI agent was built to tackle \u201ca long-standing operational blind spot\u201d: defect management for tenants and property managers.<\/p>\n
Around 60 per cent of Geocon\u2019s apartment sales go to investors, meaning the end resident is often not the original buyer. When defects are lodged \u2014 anything from cabinetry issues to water leaks \u2014 the developer still holds responsibility during the defect liability period, but historically lacked direct visibility and structured engagement with tenants.<\/p>\n
\u201cThe problem was scale\u201d, Magee said.<\/p>\n
\u201cWhen a high-rise precinct settles, sometimes hundreds of apartments at once, defect requests surge overnight.\u201d<\/p>\n
<\/p>\n
According to Magee, human teams \u201cstruggled to keep up\u201d.<\/p>\n
\u201cTickets were often incomplete, missing photos or critical information, subcontractors sent jobs back and tenants waited weeks before anything progressed,\u201d he said.<\/p>\n
\u201cWe have some critical things that it looks at, for instance a leaky tap. Anything that indicates there could be leaking water, we have an internal requirement to make that an urgent case, because no one wants a leak in their apartment and also there\u2019s potential further damage to neighbouring apartments.\u201d<\/p>\n
So we\u2019ve got some context built into the agent, where it\u2019s able to understand certain things and certain cues to ensure that we\u2019re able to actually prioritise those kinds of problems.\u201d<\/p>\n
Magee said the idea of using an AI agent has proved successful.<\/p>\n
Embedded on a public-facing page, the conversational bot builds a tenant profile from scratch \u2013 categorises the issue, ensures minimum data requirements are met and instantly routes the case to the correct subcontractor.<\/p>\n
Urgent cues \u2013 such as those water leaks \u2013 trigger internal prioritisation rules. The system also checks whether the defect falls within the liability period, filtering out invalid claims and educating tenants in real time.<\/p>\n
Magee said \u201cwhat previously took weeks of back-and-forth now happens within a single session.\u201d<\/p>\n
The impact has been felt across all sides: tenants receive faster fixes, property managers can bulk lodge issues efficiently, and subcontractors receive complete, actionable tickets.<\/p>\n
\u201cIt\u2019s infinitely scalable,\u201d Magee said. \u201cWhen inquiry goes up, AI just handles it.\u201d<\/p>\n
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<\/p>\n
Another agent on the way, this time in sales<\/p>\n
Now Geocon is moving further up the funnel.<\/p>\n
Its next AI agent, which is currently in advanced testing, will act as a sales development representative, intercepting property enquiries from websites, listing portals and social media before they reach external sales agencies.<\/p>\n
\u201cIf someone enquires on a Sunday night, within five minutes they\u2019ll hear from us,\u201d Magee explained.<\/p>\n
Rather than simply sending a brochure, the AI builds a contextual profile which understands budget, investor status and interests, while also answering lifestyle-based questions using curated local data on schools, caf\u00e9s, restaurants and amenities near each development.<\/p>\n
He said the goal is not to replace the human agents, but to just elevate them.<\/p>\n
\u201cNo real estate agent wants to do data capture and grooming,\u201d he said. \u201cThey want to close sales. If we can hand over a fully profiled, sales-ready prospect, that\u2019s better for everyone.\u201d<\/p>\n
Crucially, the AI is designed with guardrails. It introduces itself transparently, identifies when a prospect wants to speak to a human, and automatically escalates if engagement stalls. Human oversight capabilities are also on the roadmap.<\/p>\n
Why you can\u2019t ignore the frustration<\/p>\n
Magee is candid about a core tension: not every customer wants to interact with AI.<\/p>\n
Older generations may resist. Some buyers will simply prefer a human voice. Others may assume AI adds friction rather than value.<\/p>\n
His view is pragmatic.<\/p>\n
\u201cEveryone\u2019s going to have to become more accepting of it,\u201d he said, noting that AI is rapidly becoming the default customer service layer across industries.<\/p>\n
But acceptance, he argues, \u201cmust be earned\u201d. Poorly implemented AI lowers expectations, and well-architected AI changes minds.<\/p>\n
The focus, therefore, is not on deploying technology for its own sake \u2013 something Magee believes many organisations get wrong \u2013 but on solving defined business problems first. Geocon spent years strengthening its CRM data governance before layering AI on top, ensuring the agents operate with meaningful context rather than guesswork.<\/p>\n
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<\/p>\n
\u201cIf you don\u2019t have good data, it\u2019s very hard to have AI with context,\u201d he said.<\/p>\n
For customers who disengage, the system quickly routes enquiries to humans. For those who embrace the interaction, the goal is a \u201cwow factor\u201d \u2014 an experience so helpful that it enhances trust rather than erodes it.<\/p>\n
\u201cI want people to say, \u2018I dealt with Geocon\u2019s AI and it was unbelievably helpful.\u2019\u201d<\/p>\n
A high-stakes launch<\/p>\n
The sales AI is expected to go live by the end of Q1, though Magee is deliberately resisting pressure to accelerate the timeline.<\/p>\n
The stakes are high internally as well as externally. A misstep could undermine sales team confidence and damage brand perception. A successful launch, however, could redefine how property developers manage global agency networks and customer journeys at scale.<\/p>\n
For Magee, the strategy is clear: control the narrative, nurture the customer and use AI to enhance \u2014 not gatekeep \u2014 human expertise.<\/p>\n
In a sector often criticised for patchy service and inconsistent communication, Geocon is betting that intelligent automation, done properly, can become a competitive advantage.<\/p>\n
Whether customers love it or hate it will soon become clear. But one thing is certain: AI agents in property are moving from pilot projects to the front line.<\/p>\n
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