GuidesM&ANovember 5, 2026Dennis Raisich

AI in M&A

Today, AI helps in M&A wherever many documents have to be read, sorted and compared: in the search for target companies, in the data room and due diligence, in reviewing contracts and financial statements, and in drafting documents all the way to the purchase agreement. The assessment, the negotiation and the decision stay with the people in the deal.

In short

In a deal, AI mainly takes over the reading and writing: screening companies, sorting documents, analyzing contracts and financial statements, writing drafts.
Most of the reading happens in due diligence, which is why AI pays off there in particular.
Every AI statement needs a source in the documents. Without evidence, it is of no use for the report or the contract.
Before using AI, check where the data is stored, whether the non-disclosure agreement allows you to pass documents on to a provider and whether your documents will train AI models.

Where does AI help in a deal today?

A deal consists largely of text: company profiles, contracts, financial statements, questions, answers and drafts. Language models read such texts quickly, extract details and write first versions. In the phases described in our guide on how selling a company works, it looks like this.

Search and initial screening

When it comes to finding target companies or buyers and taking a first look at them (sourcing and screening), AI scans registers, websites and industry sources for companies that match a search profile and summarizes them. That way, a long list becomes a short one faster. The limit is the data: for private companies, often only a few figures are public, and what is online may be out of date. Only a conversation shows whether a company really fits.

Data room and due diligence

This is where most of the reading in a deal happens, because every document in the data room has to be read and cross-checked against the others. AI recognizes what a document is, files it in the right area and uses text recognition to make scans readable. When it checks the documents against the request list, it shows what is still missing. In due diligence, it reads every document and puts contracts, financial statements and the business plan side by side. What this means in detail is explained in our guide to AI in due diligence, and how a data room is structured in our guide to the data room.

Reviewing contracts

AI pulls the key details from every contract into a table: parties, term, termination, exclusivity, liability and the change of control clause. You can then ask all contracts one question at once, for example: “Which contracts can the other party terminate if the company is sold?” Our guide to legal due diligence shows which clauses matter here.

Financial analysis

AI reads revenue, EBITDA and debt directly from annual accounts and interim financial statements, over several years and for every company in a group. It recalculates key figures, flags unusual items and puts the business plan next to past results and the contracts. Which adjustments ultimately apply and what price follows from them remains a matter of judgment and negotiation. More on the numbers in our guide to financial due diligence, and on taxes in our guide to tax due diligence.

Writing drafts

Teaser, information memorandum, request list, questions to the seller, meeting notes, the due diligence report and first versions of clauses for the purchase agreement: AI quickly drafts all of these. A draft is no more than a starting point. Every number and every commitment has to be checked against the documents, and a contract clause has to fit the applicable law and the deal.

After closing

During integration after closing (post-merger integration), AI helps analyze the acquired contracts: which ones need to be renewed, terminated or renegotiated, and which deadlines are running. The obligations under the purchase agreement can be tracked the same way, such as the deadlines for warranties or the key figures of an earn-out. If the documents from the due diligence are already in order, nobody has to gather them a second time.

Where does AI reach its limits in M&A?

Language models sometimes make up statements that sound plausible but appear in none of the documents. In a deal, that is dangerous, because the purchase price, the warranties and the liability rest on these statements. AI also only knows what it is given. Talks with management, the mood in the team, the market situation and the other side’s intentions are not written down in any document.

No machine answers the questions a deal hinges on: whether a company fits your own strategy, which risk you take on at what price and where you give way in the negotiation. Responsibility for the report, the valuation and the agreement stays with the buyer, the seller and their advisors.

What should you look out for when using AI in a deal?

Data location

Deal documents contain trade secrets and personal data. Ask where the database and files are stored, where the AI runs and which subcontractors the provider uses, and have the provider confirm in the contract that your documents won’t train AI models. In Switzerland, the Federal Act on Data Protection (FADP) applies, and in Germany and Austria, the GDPR. If you are bound by professional secrecy, for example as a lawyer, you have further obligations.

Confidentiality

Almost every deal starts with a non-disclosure agreement (NDA). Check whether it allows you to pass documents on to service providers, and on what terms; the same goes for the engagement agreement with your client. Deal documents don’t belong in publicly available AI services where it is unclear what happens to the inputs. If the shares of one of the parties are traded on a stock exchange, the rules on inside information also apply.

Evidence for every statement

In a deal, an AI statement is worth as much as its evidence. Insist that every statement leads to its source in the document and that you can read the sentence in the original. A number without a source can’t be verified, and what can’t be verified belongs neither in a report nor in a purchase agreement.

How does majiq use AI in a deal?

majiq is an AI due diligence platform from Switzerland: data room, analysis and report, all in one place. majiq reads every document in the data room, checks it in context and writes the due diligence report. Every finding is backed by evidence from your documents and cross-checked by two AI reviewers. The AI assistant in the deal creates findings, requests documents and drafts emails, and it carries out each task only after you confirm it.

The database and files are stored in Switzerland, with hosting in Zürich. Text recognition and AI analysis run in the EU, and your documents don’t train any AI models, as set out in the contract. The sample report shows what a report looks like, and all features are listed under Features.

Frequently asked questions

Does AI replace M&A advisors?

No. AI takes over the reading and writing. Approaching buyers, building trust, negotiating and taking responsibility for the report and the agreement remain tasks for the people in the deal.

Am I allowed to upload deal documents to a public AI chat?

Only if the non-disclosure agreement, the engagement agreement and data protection law allow it. With publicly available services, whether your inputs are stored and used for training often depends on the plan and the settings. Deal documents need a provider with a known data location, a data processing agreement and a contract that rules out training.

Can AI value a company?

AI can read the numbers from the financial statements, recalculate them and prepare a valuation, for example using comparables or projections. But the value depends on assumptions about the future, and the price is set in the negotiation. That judgment stays with the buyer, the seller and their advisors.

What AI tools are there for M&A?

Roughly four types: tools for finding companies, data rooms with AI features, tools for reviewing contracts, and platforms that combine data room, analysis and report. Which one fits depends on the phase of the deal where you want to save work.