Due Diligence in Real Estate: A Developer's Checklist
What every institutional developer needs to verify before committing capital, and where AI is compressing the timeline.
The due diligence period is where deals are won or killed. For institutional developers, it is a 30-to-90-day window to confirm every assumption that shaped the underwriting. Compress it poorly and you miss deal-killers. Run it inefficiently and you burn analyst time on tasks that should not require analysts.
This checklist covers the four workstreams every development deal requires: physical, legal, financial, and environmental. It notes where AI has meaningful traction today and where human judgment remains non-negotiable.
Physical Due Diligence
Physical DD confirms the site can actually support the development program. Scope varies by asset class but the core items are consistent.
Site inspection and survey
ALTA/NSPS land title survey confirming boundary, easements, and encroachments
Topographic survey for grading and drainage assessment
Geotechnical investigation: borings, soil bearing capacity, liquefaction risk
Utilities and infrastructure
Power availability and transformer capacity (critical for data centers and industrial)
Water and sewer capacity confirmation from the utility
Gas, fiber, and telecom infrastructure proximity
Zoning and entitlement status
Confirm permitted uses and any conditional use requirements
Check for variance history, active appeals, or pending rezoning nearby
Review setback, height, FAR, and parking requirements against the program
AI handles the data aggregation well here. Zoning lookups, utility infrastructure mapping, and site scoring against multiple criteria can now be run in hours. Geotechnical interpretation and the judgment calls around entitlement risk still require experienced practitioners.
Legal Due Diligence
Legal workstreams are document-intensive and sequence-dependent. AI has materially improved throughput without replacing legal review.
Title
Review preliminary title report for exceptions, liens, encumbrances
Confirm title insurance commitment covers intended use
Flag any CC&Rs, easements, or deed restrictions that affect the program
Verify chain of title and resolve any cloud issues before closing
Contracts and agreements
Review PSA for contingencies, representations, and default provisions
Analyze any existing leases, management agreements, or service contracts that survive closing
Check for ROFO/ROFR obligations or transfer restrictions
Permits and approvals
Confirm all required permits and entitlements are in order
Identify any conditions attached to approvals
Check for open code violations or stop-work orders
AI tools can extract and flag exceptions in title reports accurately. Clause-level review of PSAs and development agreements is now AI-assisted at most institutional shops. Final sign-off and risk assessment remain attorney work.
Financial Due Diligence
Financial DD is where underwriting assumptions get stress-tested against reality.
Revenue assumptions
Confirm comparable rents from direct lease comparables, not just asking rents
Validate absorption assumptions against current market velocity
Stress-test rent growth forecasts against the supply pipeline
Cost verification
Obtain contractor-level hard cost estimates, not rule-of-thumb numbers
Confirm soft costs: architecture, engineering, permitting fees, legal, financing
Validate carry costs over the development timeline with lender term sheets
Returns analysis
Run sensitivity analysis on cap rate exit, rent growth, and cost variance
Confirm equity waterfall mechanics and preferred return structures with LP counsel
Stress-test the deal at the 10th-percentile cost overrun scenario
AI can run sensitivity analysis and populate pro forma assumptions from comparable data at speed. The deal-level judgment calls — what comp set to use, how much credit to give a market forecast, whether a cost estimate is credible — require the underwriter's read.
Environmental Due Diligence
Environmental DD is non-negotiable for any development involving land acquisition or ground disturbance.
Phase I Environmental Site Assessment
Must comply with ASTM E1527-21 (updated 2021 standard)
Covers recognized environmental conditions (RECs), historical use review, regulatory database search
No sampling — desk review and site inspection only
Phase II Environmental Site Assessment
Triggered when Phase I identifies RECs warranting further investigation
Involves soil and groundwater sampling
Results determine remediation scope and cost
Emerging contaminants
PFAS contamination is now a standard concern on any industrial or former-use site
Vapor intrusion pathway analysis often required in urban infill contexts
AI can process regulatory database searches and flag environmental records faster than manual review. Phase I conclusions and Phase II design still require licensed environmental professionals. Remediation cost estimation requires in-market expertise.
Sequencing the DD Period
For most development deals, due diligence follows a standard sequence:
Execute PSA with contingency period (typically 30-60 days for development land)
Order title, survey, and Phase I simultaneously on Day 1
Complete physical inspections by Day 15
Receive and review Phase I by Day 21
Confirm utility capacity and zoning by Day 21
Complete financial sensitivity analysis and legal review by Day 30
Decision: proceed, renegotiate, or terminate
AI platforms are compressing Days 1-15 significantly. Site data aggregation, zoning analysis, and document extraction tasks that previously took analyst teams days can now run overnight. That compression creates real competitive advantage in competitive deal processes where sellers favor buyers who can close DD windows faster.
What AI Handles vs. What Stays Human
The pattern across all four DD phases is consistent: AI handles data aggregation, document parsing, and standardized analysis. The interpretive layer — where expertise and market knowledge determine the call — stays with the practitioner.
Development teams running AI-assisted DD report 40-60% reductions in analyst time on document review and data-gathering tasks. That time is being redirected toward judgment-intensive work, not eliminated. The goal is not to automate the decision. It is to make the analyst making that decision faster and better-informed.