Title Report Review with AI: Faster Closings, Fewer Surprises
How AI is compressing one of the most time-consuming steps in CRE due diligence — without replacing the judgment calls.
Title review sits at the intersection of legal risk, transactional timing, and deal certainty. For institutional developers closing on land or existing assets, a clean title opinion can take 10 to 20 hours of attorney time. Exceptions, easements, and chain-of-title gaps buried in hundreds of pages of commitment documents are easy to miss and expensive to fix after closing.
AI is changing how that review gets done. Not by replacing attorneys, but by doing the first 80 percent faster.
What a Title Commitment Actually Contains
A title commitment from a major underwriter (Fidelity, First American, Stewart, Old Republic) runs between 30 and 200 pages for a complex commercial transaction. The document includes:
Schedule A: Legal description, vesting, and proposed insured amounts
Schedule B-I: Requirements to be met before closing (payoffs, releases, corporate authorization)
Schedule B-II: Exceptions — what the policy won't cover
Schedule B-II is where the risk lives. Easements, rights-of-way, restrictive covenants, mechanics' lien exposure, mineral rights reservations, and party wall agreements all show up here, often referenced by recording number with no summary of their actual terms. The attorney then has to pull and review each underlying document.
For a 50-acre industrial or data center site, that list can run 40+ exceptions.
What AI Can Review Today
AI systems trained on legal documents and CRE transaction structures can process a title commitment and flag:
Exception categorization. Every B-II exception classified by type: access easements, utility easements, deed restrictions, mineral severances, environmental covenants, survey matters. Categorization alone saves 30 to 45 minutes on a complex file.
Plain-language summaries. AI converts recorded document numbers into plain-language descriptions once the underlying instruments are provided. A 12-page access easement gets summarized in three sentences, flagged for key provisions: exclusivity, term, maintenance obligations, and termination rights.
Red-flag identification. Deed restrictions that limit use, blanket easements that traverse the buildable area, or mineral rights reservations that include surface entry rights all get escalated automatically. These are the items that can kill or restructure a deal.
Chain-of-title gaps. AI can map ownership transfers chronologically and flag breaks in the chain or conveyances that appear to lack consideration, which may indicate an unrecorded interest or a gift deed that could invite challenge.
Comparison against prior reports. For portfolios or repeat acquisitions in a market, AI can compare a new title commitment against prior ones in the same county or subdivision, flagging new exceptions that have appeared since last review.
Platforms being used for this work include Hebbia (strong on document retrieval and synthesis), FifthDimension (built for CRE transaction stacks), and Build's own workflow layer, which connects title review to broader due diligence across site, environmental, and entitlement workstreams.
What Still Requires an Attorney
AI flags the issues. It does not resolve them.
Curative work — getting a lien released, obtaining a quitclaim deed, or negotiating an easement modification — requires legal judgment and relationships with counterparties. AI has no role here.
Legal opinion on coverage. Whether a specific exception material affects the developer's intended use is a professional judgment. An attorney opining on title coverage is providing a legal conclusion, not a summary.
Unusual instruments. Older deeds in secondary markets sometimes use non-standard language, reference plats that have been vacated, or include conditions subsequent that require interpretation. AI accuracy drops on edge cases.
State-specific nuance. Texas has oil and gas reservations baked into almost every rural parcel. Florida has sovereign submerged lands complications near waterways. Colorado has ditch rights that can impair development. These require local counsel familiar with specific state regimes.
The right model: AI does the first pass in two to four hours. Attorney reviews the flagged items, pulls the high-risk instruments, and issues a title opinion on the material issues in half the time of a cold review.
The Workflow in Practice
For a development team running a typical land acquisition:
Upload the title commitment and all Schedule B-II instrument copies to the AI system
Receive a categorized exception summary with risk flags within two to four hours
Review flags with transaction counsel; instruct on curative requirements
AI tracks curative items through closing as requirements are satisfied
Final title policy compared against commitment to confirm all exceptions resolved or endorsed over
Teams running this workflow report title review time dropping from 15 to 20 attorney hours to five to seven. At $400 to $700 per attorney hour at an institutional firm, the per-deal savings are material.
The Risk of Skipping AI Review
The alternative isn't necessarily a thorough manual review. Under deal pressure and tight timelines, exceptions get skimmed. An institutional developer missed an access easement in favor of a neighboring parcel during a 2023 industrial acquisition in the Inland Empire. The easement ran directly through the planned loading dock configuration. The deal closed, the issue surfaced during construction permitting, and the redesign cost $2.1 million.
AI doesn't guarantee that outcome is avoided. But a systematic review against a known checklist of risk categories — run in hours, not days — reduces the probability of missing something material.
Where This Is Heading
Title companies are starting to build AI into their own commitment workflows. First American and Fidelity have both announced AI pilots for title plant searches and commitment preparation. As those tools mature, the commitment itself may arrive with a pre-populated exception summary.
For developers today, the advantage is in deploying AI on the buyer side before attorney review, compressing the diligence cycle and focusing expensive legal time where it actually matters.