AI Contract Review: Evidence and Human Approval

A supplier agreement lands in the procurement inbox on Friday afternoon. By Monday, the business owner wants approval. Legal wants the deviations highlighted. Security wants to know where the supplier will process customer data. Procurement wants to know whether the commercial terms are within policy. No one is asking for a prettier summary.

That is the difference between document AI and an operational workflow. An impressive summary can still omit the one clause that changes the decision: a subprocessor in another jurisdiction, an uncapped liability exception, or an incident-notification period inconsistent with policy.

Begin with the decision, not the model

The intended output is a defensible recommendation for a named human decision-maker, with traceable evidence. The system must distinguish an extracted fact from an interpretation, a policy requirement from an exception, and an unresolved question from a positive finding. No model should silently translate “not found” into “compliant.”

What the workflow actually does

First, intake records the supplier, contracting entity, jurisdiction, agreement version, review purpose and responsible owner. Source files receive stable identifiers and integrity metadata. Extraction then identifies clauses, obligations and key fields; each finding points back to a page, section and document version. Low-confidence extraction creates a verification task rather than a fabricated answer.

Next, retrieval obtains current, approved guidance for the applicable business unit and jurisdiction: data protection, information security, outsourcing, risk appetite and contract playbooks. Permission checks run before retrieval and again when evidence is assembled; a search index is not a new authorization boundary. Policy version, owner and effective date travel with each retrieved passage.

Only then does comparison begin. A clause can be consistent, divergent, missing, or impossible to assess. The reviewer sees the exact contractual language alongside the relevant policy rule, the reason for the finding and the unresolved evidence. An exception is a separate business decision with its own approver and expiry—not a prompt instruction to ignore a mismatch.

The handoff matters more than the summary

Consider an agreement permitting a supplier to engage subprocessors without prior notice. Extraction may correctly capture the clause. Retrieval may find a policy requiring notification and assessment. Yet the system still needs to determine which contracting entity is in scope, whether a negotiated schedule overrides the general clause, and who can accept the residual risk. The right output is a review packet and a routed exception, not an autonomous approval.

Control points and failure modes

Untrusted contract text must never be treated as operating instructions. A malicious sentence embedded in a PDF is evidence to analyze, not an order to the agent. Tool permissions should be scoped to read-only retrieval and controlled draft creation. Signing, vendor activation and risk acceptance require separate authorization. Idempotent workflow transitions prevent duplicate approvals after retries.

The operational record should capture document and policy versions, retrieval sources, prompt or workflow configuration version, tool calls, findings, human edits, decisions and timestamps. Sensitive excerpts need retention and access policies of their own.

Measure whether the review improved

Track the proportion of findings supported by source citations, false negatives discovered by legal review, exception-routing accuracy, reviewer correction time, cycle time by contract type, and the share of cases that require manual rework. A reduced handling time means little if the system systematically misses high-impact clauses.

This is an illustrative architecture, not a claim that Archy autonomously performs legal review. Archy can provide the orchestration foundation for agents, enterprise knowledge, tools, and governed handoffs; the organization's policies, integrations and decision rights define the actual workflow.

Further reading

NIST Generative AI Profile; OWASP LLM Top 10; EU AI Act Article 26 (applicability depends on system classification and circumstances).

Explore enterprise agent orchestration: Archy Platform.

For the related architecture decisions, see Enterprise RAG Security: Permissions and Tenant Isolation; Enterprise AI Workflows: State, Approvals and Recovery.