Most of What a Property Developer Knows Is in Somebody’s Phone

Property in this region runs on relationships and spreadsheets, and most of what a developer actually knows lives in somebody's phone. Which buyer is serious. Which agent brings real enquiries. Which contractor slips. Which estate moves quickly and which one has been sitting since the launch event. All of it exists, none of it is written down, and it walks out of the building when the person holding it resigns. That is the honest starting point for this sector, and it is why so many proptech conversations in Nigeria skip past the thing that would actually help. ## Where the money goes missing **Lead qualification.** Developers generate large volumes of enquiries and convert a small fraction. The sales team treats most of them identically because there is no basis for doing otherwise. Meanwhile the signals that distinguish a serious buyer from a browser are sitting in the enquiry history: what they asked about, how quickly they replied, whether they returned, whether they asked about payment plans rather than finishes. Ranking enquiries changes where a small sales team spends its week, and in a business with long cycles and high ticket sizes that is the single highest value change available. **Collections on instalment sales.** A large share of African property is sold on payment plans running over years. Default and late payment behaviour follows patterns that are visible well before a payment is missed. Most developers discover a problem when the payment does not arrive, which is the worst moment to start the conversation. **Project cost and schedule.** Overruns are routine and are usually attributed to conditions outside anyone's control. Some are. Many follow patterns visible in the organisation's own history of previous projects, if anybody had ever assembled that history. **Facilities and service charge.** For managed estates and commercial property, maintenance spend and utility consumption both carry detectable anomalies. ## The document load nobody mentions Property generates extraordinary volumes of paper. Title documentation, governor's consent, deeds of assignment, allocation letters, subscriber agreements, contractor variations. This is one of the clearest applications available and it needs the same caution as any legal document work. A first pass that flags what deviates from standard, reviewed by a person who is qualified to judge. Never a final answer, because title in this market is precisely the place where being confidently wrong is expensive. ## The exposure here BROAI, people quietly using their own AI tools, shows up in property with a particular flavour. The material is buyer financial information, payment plan status, identity documents collected at subscription, and commercial terms with partners and contractors. A sales administrator pasting a subscriber list into a free chatbot to reformat it has handled identity and financial data belonging to hundreds of people. Under the Nigeria Data Protection Act that is regulated material, and this is a sector where personal data is collected in volume by teams who have rarely been trained on handling it. ## What good looks like Write down what is currently in one person's head. That is the real first project and it does not need any technology at all. Then approved tools, a rule about buyer data, and a first use case with an owner and a number. SWITCH, the framework I use with clients, opens with Scan and Score because in property the scan usually reveals that the organisation has far less written down than it believed. A question for the next management meeting. If your best salesperson resigned tomorrow, how much of what they know about your buyers would leave with them? ## Frequently asked questions **Where should a property developer start with AI?** Lead qualification. Enquiry data already exists, the sales team is small relative to enquiry volume, and better ranking changes conversion within one cycle. **Can AI help with instalment sale collections?** Yes. Payment behaviour patterns are visible before a default, which moves the conversation earlier when it is still easy to resolve. **Is AI useful for title and documentation review?** For a first pass that flags deviation from standard, reviewed by a qualified person. Never as a final determination on title. **What data protection issues apply?** Buyer identity and financial information collected at subscription is regulated personal data under the Nigeria Data Protection Act. It should never enter tools the business does not control. **What about smaller agencies rather than large developers?** The same first step applies and costs nothing. Write down what your people know about your buyers so it survives them leaving. *Stanislaus Martins advises and trains enterprise teams across Sub Saharan Africa on practical AI adoption and governance. Formats are on the [speaking and training page](/speaking), or start a conversation on the [work with me page](/work-with-me).*