Why Most Proptech AI Pilots Fail Before Reaching Production

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AI adoption in property management rose sharply from 20% to 58%, yet only 8% of processes are fully automated, and a 2025 MIT report found 95% of generative AI pilots generated no profit. In commercial real estate, 92% of firms ran an AI pilot but just 5% met all their goals, a gap engineers attribute to structural flaws rather than model quality. Pilots typically run against clean, sandboxed data, while production systems require authentication boundaries, audit trails, and write paths back into legacy systems — none of which most pilots account for. Key barriers include change management (76%), data integrity failures from unpopulated schema fields (49%), and legacy system limitations (28%), with integration described as the core challenge since 73% of proptech tools must connect to pre-existing infrastructure. Engineers recommend resolving read and write paths, entity resolution, and identity models before signing vendor contracts, and favour a read-replica architecture that defers writes to a later phase.

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