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M&A Due Diligence with AI: Prompts for Merger Agreements & Corporate Law

M&A Due Diligence with AI: Prompts for Merger Agreements & Corporate Law

πŸ“… Published: February 2026 | ⏱️ 10 min read | ✍️ Whisperit Legal Tech Team

M&A due diligence is a race against the clock. Associates spend hundreds of hours reviewing contracts, merger agreements, and disclosure schedules. AI can compress that timeline dramatically β€” but only if you know what to ask.

This guide draws on the MAUD dataset (Merger Agreement Understanding Dataset, 30+ tasks from real merger agreements) and CUAD to give you prompts that mirror exactly what junior associates do on day one of a deal.

πŸ’‘ Pro Tip: M&A prompts work best when you give the AI the exact provision text. Don't paraphrase β€” merger agreement language is precise, and every word matters.


πŸ“Š Why AI for M&A Due Diligence?

Traditional DDAI-Assisted DD
200+ hours of associate reviewFirst-pass scan in hours
Inconsistent flagging across reviewersConsistent clause detection
Key terms buried in 500-page agreementsAutomated extraction of critical provisions
Manual comparison across deal documentsSide-by-side analysis at scale

⚠️ Important: AI provides the first pass. Senior attorneys must still review flagged provisions and make judgment calls on deal-specific risk.


πŸ” Section 1: MAE Clause Analysis

The Material Adverse Effect definition is the most negotiated provision in any merger agreement. MAUD tests AI on 10+ sub-tasks within MAE clauses alone.

Comprehensive MAE Analysis

text
Review the following Material Adverse Effect (MAE) definition from a merger agreement:

"{mae_definition}"

Analyze:
1. What is the MAE standard (e.g., "would reasonably be expected to have")?
2. What carveouts are included (e.g., general economic conditions, industry-wide changes, changes in law)?
3. Are the carveouts subject to a disproportionate impact modifier?
4. Does the definition apply to the target only or to both parties?

Provide a risk assessment from the buyer's perspective.

MAE Carveout Checklist

text
Review the following MAE definition and check whether each of these standard carveouts is present:

"{mae_definition}"

| Carveout | Present? | Language |
|---|---|---|
| General economic conditions | | |
| Industry-wide changes | | |
| Changes in law/regulation | | |
| Changes in GAAP | | |
| Pandemic/public health | | |
| War/terrorism/natural disaster | | |
| Changes in financial markets | | |
| Failure to meet projections (vs. underlying cause) | | |
| Actions required by the agreement | | |
| Disproportionate impact modifier | | |

Flag any missing standard carveouts and any unusual inclusions.

🚫 Section 2: No-Shop & Deal Protection

No-Shop Provision Analysis

text
Review the following no-shop provision from a merger agreement:

"{provision_text}"

Determine:
1. Is a fiduciary exception included?
2. What is the board determination standard (e.g., "reasonably likely to lead to a superior proposal")?
3. What triggers the fiduciary exception?
4. What is the liability standard for breach by target non-D&O representatives?

Matching Rights Period

text
Review the following provision from a merger agreement:

"{provision_text}"

What is the initial matching rights period for a change of recommendation?
What triggers the matching rights?
Are there additional matching periods for revised proposals?

Change of Recommendation Standard

text
Analyze the change of recommendation provisions:

"{provision_text}"

1. What standard must the board meet to change its recommendation?
2. Is the standard different for superior proposals vs. intervening events?
3. What notice and negotiation requirements apply before a recommendation change?

πŸ—οΈ Section 3: Representations & Bringdown Standards

Bringdown Analysis

text
Review the following bringdown condition from a merger agreement:

"{provision_text}"

Determine:
1. What is the bringdown standard for fundamental representations (e.g., "true and correct in all respects" vs. "in all material respects")?
2. What is the standard for general representations?
3. Is there a separate standard for capitalization representations?
4. Are the representations qualified by MAE or materiality?

🏒 Section 4: Successor Liability & Corporate Structure

Successor Liability Classification

text
A company has sold substantially all of its assets. Based on the following fact pattern, determine if successor liability applies and, if so, what type:

{fact_pattern}

Types of successor liability:
1. Express agreement β€” purchaser agreed to assume liabilities
2. Fraudulent conveyance β€” sale intended to escape liability
3. De facto merger β€” continuity of ownership, operations, personnel
4. Mere continuation β€” only one entity remains, overlap of stock/directors

Answer with the type and supporting analysis.

Corporate Lobbying Detection

text
Based on the following text, determine if the company is engaging in corporate lobbying:

"{text}"

Answer Yes or No with reasoning.

πŸ“‹ Template: Useful for ESG and compliance due diligence β€” flag lobbying activity in target company filings and public disclosures.


πŸ“‘ Section 5: Contract-Level Due Diligence

Comprehensive Contract Review for DD

text
You are conducting legal due diligence on a target company. Review the following contract and identify:

1. Change of control provisions
2. Assignment restrictions
3. Termination for convenience rights
4. Non-compete or exclusivity obligations
5. Most favored nation clauses
6. Uncapped liability provisions
7. IP ownership/assignment provisions

Contract: "{contract_text}"

For each identified provision, assess the risk level (High/Medium/Low) and explain the impact on the proposed transaction.

IP Due Diligence

text
Review the following contract provision:

"{provision_text}"

Does this provision address IP ownership or assignment?
If yes:
- Who owns the foreground IP?
- Who owns the background IP?
- Are there any license-back provisions?
- Is assignment of future IP included?

Answer with analysis.

J.Crew Blocker Detection

text
Review the following contractual provision:

"{provision_text}"

Is this a "J.Crew blocker" provision (designed to prevent asset stripping or IP transfers in credit agreements)?

Answer Yes or No with reasoning.

πŸ”„ Section 6: Deal Review Workflow

Step-by-Step: AI-Assisted Merger Agreement Review

  1. MAE Definition β€” Run the MAE analysis and carveout checklist
  2. Deal Protection β€” Analyze no-shop, matching rights, and recommendation change standards
  3. Reps & Bringdown β€” Check bringdown standards for all representation categories
  4. Covenants β€” Review ordinary course covenants and consent requirements
  5. Conditions β€” Analyze closing conditions and regulatory approval requirements
  6. Termination β€” Review termination rights, break fees, and reverse break fees
  7. Material Contracts β€” Run the comprehensive DD scan on each material contract

Deal Comparison Template

text
Compare the following provisions across these two merger agreements:

Agreement A (Deal: {deal_a_name}):
"{provision_a}"

Agreement B (Deal: {deal_b_name}):
"{provision_b}"

Provision type: {e.g., MAE definition / No-shop / Break fee}

Create a comparison table showing:
| Element | Agreement A | Agreement B | Market Standard | Assessment |

πŸ’‘ Pro Tip: Build a library of analyzed provisions from past deals. Over time, you'll have market-standard benchmarks for every major clause type.


πŸ“‰ Pandemic & Special Provisions

MAUD specifically tracks pandemic-related provisions in merger agreements β€” a category that barely existed before 2020.

text
Review the following merger agreement provision:

"{provision_text}"

Does this provision specifically address pandemic-related risks?
If yes:
1. Is pandemic included as an MAE carveout?
2. Are there specific pandemic-related ordinary course covenants?
3. Does the provision address government shutdown orders?
4. Is there a disproportionate impact exception for pandemic effects?

⚠️ Limitations for M&A Use

  • Deal-specific context matters enormously. The same MAE definition might be acceptable for a $50M deal and unacceptable for a $5B deal.
  • Negotiation strategy is human. AI can identify what's in the agreement; it can't tell you what to push back on.
  • Confidentiality is critical. Use only enterprise-grade AI tools with appropriate data security for deal documents.
  • Market standards shift. Post-pandemic deal terms differ significantly from pre-pandemic norms.

πŸš€ Accelerate Deal Review with Whisperit

M&A lawyers juggle hundreds of documents under tight deadlines. Whisperit.ai lets you dictate deal memos, run AI-assisted document analysis, and draft due diligence reports β€” all from one platform designed for legal professionals.

Speed up your next deal β†’


Part 4 of 5 in our Legal AI Prompt Series. Next: AI for Every Practice Area: Specialized Legal Prompts β†’