Contract Assurance with AI Training Course: Due Diligence Reviews, Clause Extraction and Findings

Programme Summary

Contract assurance with AI is the subject of this one-week training course for legal, commercial, risk and audit managers at managerial level, ending in a contract assurance file for one transaction or contract portfolio. Machine-assisted tools read thousands of pages in hours, yet their findings are only as reliable as the checks placed around them. The programme moves from the review chain to diagnosis of missed clauses, then to sampling, evidence and a scaled application. Mars Training Centre UK delivers this programme on contract assurance with AI to mixed-organisation cohorts.

The Business Case

Due diligence reviews and contract audits are run against deadlines, and teams are tempted to accept machine output as complete. A missed termination right, an unusual liability cap or an unseen change of control clause can surface after signature, when it is costly to correct. Leaders who test how findings were produced can use speed without giving up reliability or control.

• Review Cycle Time: Falls where machine-assisted reading is used for volume and people decide the exceptions.
• Missed Clause Exposure: Is reduced as sampling and calibration reveal what the tool overlooks.
• Audit Evidence Quality: Rises as every finding is traced to a source passage and a reviewer decision.

Principles and Evidence Base

• ISO 31000 Risk Management Guidelines: Frame how contract and deal risks are identified and rated, applied in Session 1 to the review scope.
• ISO 19011 Guidelines for Auditing Management Systems: Supply principles for evidence and findings, applied in Session 3 to machine-assisted findings.
• ISO/IEC 42001 AI Management System: Sets expectations for controlling AI tools, applied in Sessions 2 and 4 to tool and data safeguards.

Intended Participants

• Legal and contract managers who direct due diligence and contract review work.
• Commercial and deal team managers who rely on review findings to price and sign.
• Risk and internal audit managers who test whether contract controls work.
• Procurement and partnership managers who own supplier and counterparty agreements.

Typical settings include banking, construction, energy and public bodies.

Learning Outcomes

1. Participants will be able to evaluate the claims of a machine-assisted review tool against a sample of contracts.
2. Participants will be able to diagnose why clauses are missed or misread in extraction.
3. Participants will be able to construct a sampling plan that tests machine findings.
4. Participants will be able to prioritise findings by risk to the transaction or portfolio.
5. Participants will be able to design safeguards for confidentiality, privilege and tool change.
6. Participants will be able to justify an assurance conclusion to a deal or audit committee.

Programme Structure

Day 1: Contract Assurance with AI and the Review Chain

Where can machine-assisted review be trusted in due diligence or a contract audit, and where must a person decide?

• Review Chain Process Map
• Contract Population and Scope Sheet
• Due Diligence Issue Taxonomy
• Review Tool Claim Check
• ISO 31000 Risk Context Sheet

Day 2: Diagnosing Missed Clauses and Data Gaps

Why does a tool miss a clause, and how can the miss be seen?

• Clause Extraction Error Taxonomy
• Scan and Document Quality Review
• Confidentiality and Privilege Safeguard List
• Obligation and Exception Register
• ISO/IEC 42001 Control Mapping

Day 3: Designing Sampling and Evidence

How many findings must be checked, and what counts as sufficient evidence?

• Sampling Plan for Machine Findings
• Precision and Recall Reading
• ISO 19011 Evidence Principles Grid
• Finding Rating Scale
• Reviewer Calibration Protocol

Day 4: Findings, Reporting and Control

How are findings reported so that a committee can act on them?

• Issue List and Deal Risk Report
• Remediation Tracker
• Escalation Rule Set
• Reviewer Override Log
• Tool Update Change Control

Day 5: Contract Assurance File

Do the earlier tools combine into one file that a committee can rely on?

• Applying the Session 1 Process Map
• Testing the Session 2 Error Taxonomy
• Checking the Session 3 Sampling Plan
• Rehearsing the Session 4 Escalation Rule Set
• Completing the Contract Assurance File

Methodology

The programme uses case analysis built on prepared files for one acquisition target and one supplier contract portfolio, each with sample agreements, tool output, an issue list and reviewer notes. Participants work in small groups, test what the tool found against the source text, and defend their assurance conclusions to peers acting as committee members.

• Suggested activity: Locating clauses that a supplied tool output failed to extract.
• Suggested activity: Setting a sample size and acceptance rule for a batch of findings.
• Suggested activity: Rating a finding list and arguing which items reach the committee.

Capstone Output

Each participant completes a contract assurance file for one transaction or contract portfolio. It holds a scope sheet, an error finding, a sampling plan, a rated issue list and an escalation rule. The file is used at work to brief a committee and to agree reviewer duties with the teams carrying out the review.

Frequently Asked Questions

Is a course on contract assurance with AI suitable for managers without a legal qualification?

Yes. Contract assurance with AI is taught through prepared files, templates and checklists. It assumes experience in legal, commercial, risk or audit work, but no coding and no earlier use of review tools.

Which standards does contract assurance with AI rest on?

Contract assurance with AI rests on ISO 31000 for risk management, ISO 19011 for evidence and findings, and ISO/IEC 42001 for the control of AI tools.

How is the assurance file for AI due diligence reviews used at work?

You use the contract assurance file to brief your committee, agree reviewer duties and set the rule for which findings are escalated.

How does contract assurance with AI differ from a contract drafting course?

Contract assurance with AI concentrates on testing review findings and evidence, while a contract drafting course concentrates on writing terms and negotiating positions.