Can Artificial Intelligence Help Prevent Double Land Sales in Ghana?

Imagine saving for years to buy a plot of land, only to arrive one morning and find someone else laying a foundation on it. The other buyer also has documents, receipts and a convincing account of how the purchase happened. Both believe the land belongs to them. What began as a plan to build a home has become a dispute that could consume more money than either person can afford.

Double land sales raise a difficult question for Ghana’s land administration: how can competing transactions be detected before buyers commit their savings? Artificial intelligence could help by drawing attention to suspicious applications and conflicting records early enough for officers to investigate. Its usefulness, however, would depend on the quality of the information available and the willingness of institutions to act on what it reveals.

The strongest case for AI is its ability to compare large volumes of information. A registration officer reviewing one application may have to consult survey plans, earlier transactions and supporting documents. Where these records are available in a connected digital system, AI could help identify relationships that deserve closer examination. An application that appears ordinary on its own might look very different when compared with another submission concerning the same parcel.

Overlapping boundaries are one place to begin. A proposed system could compare the coordinates on a submitted survey plan with existing parcel maps. If the new parcel occupies part or all of an already recorded parcel, it could generate an alert before the application proceeds further.

The distinction between ordinary mapping tools and AI matters here. Geographic information systems can already detect geometric overlaps. AI could add value by helping prioritise alerts, identifying patterns across applications and assisting officers where older records contain inconsistent descriptions. Ghana should choose tools according to the problem they solve, with clear evidence that they improve the work.

An overlap would not, by itself, prove a double sale. It could arise from an inaccurate survey, a mapping error, an outdated record or a legitimate transaction affecting an existing parcel. The alert should prompt examination of the plans and documents, followed where necessary by a site inspection. Accurate surveys remain essential because a computer cannot establish the true boundary of a plot from unreliable coordinates.

Duplicate applications present another opportunity. Two submissions might concern the same land but use different spellings, document formats or descriptions. A proposed AI system could compare parcel references, coordinates, parties’ details and supporting documents to flag possible duplication.

That comparison must account for legitimate circumstances. A corrected submission, an authorised transfer or an application made through a representative could resemble a duplicate. The system should preserve the application and identify the reason for its concern. An officer should then determine whether the submissions relate to the same transaction, competing claims or an innocent administrative error.

Ownership records require equally careful treatment. AI could assist in arranging documents into a sequence and flagging apparent inconsistencies. A seller’s details might differ across records. A later document might refer to an earlier transaction that cannot be found. Two applications might present conflicting accounts of who has authority to deal with the land.

These are reasons to ask questions. They are not sufficient grounds for declaring someone dishonest. A difference in names could reflect a spelling error, a marriage or incomplete record keeping. Missing information could require clarification from a family, a customary authority or another relevant party. Human investigation must establish what happened and give affected people a fair opportunity to respond.

Reliable records are therefore the foundation of any credible AI project. Digitising documents is useful, but scanning them does not correct their contents. Before introducing automated checks, the responsible institutions should assess record completeness, reconcile parcel identifiers and distinguish confirmed information from unresolved claims. Otherwise, an efficient system could simply circulate old mistakes more quickly.

Coverage also matters. If a transaction has never entered the available records, AI may have nothing against which to compare it. A system could find no conflict even though a competing claim exists outside its database. Buyers and officers must understand this limitation. A result showing no detected inconsistency should never be presented as an unconditional assurance that a purchase is safe.

The practical workflow should be straightforward. When an alert appears, a designated officer should review the supporting evidence, request clarification where needed and record the outcome. Serious concerns should receive timely attention. Applicants should receive an understandable explanation of any delay and have a route to challenge an incorrect finding.

Privacy deserves the same care. Land records can contain identity documents, signatures, addresses and sensitive family information. Access should be limited according to an officer’s responsibilities, with records of who viewed or changed information. Public verification services should disclose only what is necessary for their purpose.

Ghana could begin with a limited pilot using records that have been checked for quality. Its performance should be assessed against practical questions: Does it identify conflicts that officers would otherwise miss? How often does it wrongly flag legitimate applications? Does investigation become faster? Are applicants receiving clearer explanations? Those answers should guide expansion.

Artificial intelligence could help Ghana detect some warning signs of double land sales earlier. Preventing harm would still require accurate surveys, dependable records, responsible officers and effective action against proven misconduct. The real achievement would be a buyer receiving a timely warning, a disputed application being properly investigated and a family’s savings being protected before another foundation is laid.