The Use of Technology in M&A Transactions: Challenges and Perspectives for Law Firms

The history of humankind has been marked by technological ruptures that have shaped the way we live, think, and organize ourselves. From the invention of writing to the industrial revolution, and then to network digitalization, each stage represented not only a technical advancement but a change in the very logic of institutions. Artificial intelligence and other innovations have left the realm of promise and have become part of daily life, crossing borders and reaching every sphere of economic and social activity.

Although these effects radiate across the law as a whole, the purpose of this article is to assess how law firms have incorporated technology in the context of M&A transactions, identifying what already works in practice, where the concrete benefits lie, and which risks still require vigilance.

This choice stems not only from the recurrently transnational and highly complex nature of such transactions, but also from the significant growth of this market, which has become one of the fields in which the incorporation of technological and AI solutions is most visible and at the same time most challenging. It is not a distant observation from the market, but a view of how legal practice is reorganizing to deal with the growing presence of these tools throughout the transaction cycle.

One of the first issues to address is confidentiality and transparency, even at the stage of engaging law firms to structure this type of transaction. There is a perception that the use of technology, especially tools supported by artificial intelligence, is in itself insecure and will inevitably lead to data breaches. This idea, often repeated as if it were an absolute truth, is largely a myth. The risks exist, but they can be mitigated by practical governance measures. Some examples that already have the power to bring greater security to legal activities are presented below.

First, law firms that adopt technology in their workflows should make clear in their General Business terms that they use automated tools and, in particular, artificial intelligence, for the performance of certain legal work. This measure by itself already adds a layer of trust and transparency with the client.

It is also of utmost importance to establish internal information security policies and to provide for containment plans for possible incidents, while observing the guidelines of the main data protection regulations in force. Internal training of professionals, with the aim of ensuring proper digital literacy for the use of these tools, has also proved to be a differentiating factor.

In addition, the use of enterprise versions of tools, with robust encryption, access logs, and contractual guarantees of non-use of data for model training, further strengthens protection. In this context, the technological maturity of firms also translates into building internal capabilities. It is equally relevant that firms properly program the assistants they use, customizing them according to their workflow, compliance requirements, and team drafting style, often with the support of information technology companies or, where more convenient, by contracting ready-made legal solutions that already observe security and governance standards. This preventive posture conveys to the client the assurance that technological efficiency does not compromise confidentiality.

Moving on to the execution of the legal work, technology is already present from the earliest moments of an M&A transaction. Even before drafting any document, it is common for the parties to meet to discuss the framework of the transaction and align expectations regarding the subject matter, the economic conditions, and the obligations that will be reflected in the formal instruments. In these meetings, the use of recording and automatic transcription tools can bring gains in precision and recordkeeping, allowing lawyers to have a more organized basis for the strategic information that will guide the preliminary contracts.

This resource, however, cannot be used without caution, and mitigation measures must again be observed to avoid the leakage of sensitive data, precisely because the sensitivity of the information shared at this stage requires the same level of confidentiality expected in contract drafting. It is no coincidence that many companies only authorize the use of such tools after strict compliance validation or simply prohibit them, fearing leaks or misuse of data for algorithm training.

Once the initial phase of data collection and strategic parameters has been completed, the drafting of preliminary agreements begins. In M&A transactions, it is common to use instruments such as term sheets, letters of intent, and memorandums of understanding. At this point it is possible to rely on automated templates or programmed assistants to structure the initial version of the document, organizing the premises of the transaction and integrating the elements discussed in meetings with the client.

The draft resulting from this process, although faster to produce, must necessarily undergo the lawyer’s critical review, who should examine each clause and adjust the wording to reflect the specific terms of the negotiation, ensuring that no strategic aspect is omitted. The time savings are significant because automation handles structure and formal standardization, while the professional’s interpretive work focuses on what truly matters, namely risk calibration, the adaptation of clauses to the peculiarities of the business, and the anticipation of potential friction points.

Advancing a little further, due diligence is perhaps the territory where the gains and limits of technology appear most clearly. On the one hand, document analysis systems allow large volumes of contracts to be processed in a short time. On the other hand, critical reading remains irreplaceable.

Data room platforms already use AI to classify documents, conduct semantic searches, and even automate sensitive drafting. Today it is already possible to use tools to quickly locate clauses that, in M&A transactions, directly affect the valuation of the target and the determination of the purchase price. By way of example, some clauses are recurrently identified, such as acceleration in banking contracts upon change of corporate control, exclusivity provisions that prevent short-term synergies, non-compete undertakings with disproportionate periods, call and put options capable of compromising future governance, and confidentiality obligations that condition data integration. Technology helps to map these provisions more quickly and in a more organized manner, greatly facilitating the lawyer’s work in preparing the report and the risk assessment.

The same reasoning applies to the analysis of litigation contingencies, one of the most sensitive stages of due diligence. Software that applies jurimetrics can statistically estimate the probability of success or loss in pending actions. Such reports are useful as support because they help structure databases and identify patterns, but at least for now they cannot be considered completely sufficient to ground financial decisions in a transaction. What truly defines the legal and economic consequence of a dispute is the analysis of the merits, the evidentiary strength of the record, and the posture of the relevant courts. It is precisely the legal evaluation that determines in practice whether the parties should negotiate a price discount, withhold installments, establish escrow accounts, or require documentary reinforcement as a condition for signing the definitive agreements.

Practical experience shows that the true value of technology lies in allowing the lawyer to devote less time to mechanical tasks and more energy to strategic analysis. It is thus evident that AI tools that organize risk reports, classify documents in different languages, and even suggest automated drafting are valuable in this type of procedure.

The transition to the Share Purchase Agreement and ancillary contracts represents a new balance point between tool and method. If in the preliminary phases technology already brings gains in speed and organization, here it begins to influence directly the way the core documents of the transaction are drafted and negotiated. There is no doubt that there is a real gain in generating preliminary versions and in automated comparison of drafts, especially in the case of long contracts with multiple annexes and recurring clauses. The use of legal copilots allows versions to be aligned more quickly, differences between drafts to be highlighted in seconds, and proposed wording to be suggested based on precedent banks. Even so, the nature of these clauses prevents talk of full automation.

The calibration of precedent conditions, the design of earn-out mechanisms, the drafting of representations and warranties, purchase price adjustment provisions, and material adverse change criteria, among other points, cannot be reduced to static formulas. A detail that a system treats as interchangeable may, in the concrete context of the deal and the jurisdiction in which it will be performed, prove costly if not read with the required depth. An earn-out period that appears mathematically neutral in a model may distort the economic balance of the transaction in light of a specific production cycle or the seasonality of the sector. A representation of regulatory compliance drafted on the basis of boilerplate language may leave out a sensitive aspect of a given jurisdiction, exposing the buyer to unexpected risks.

For this reason, even when the initial draft is produced with technological assistance, the final review must be conducted with the attention of someone who identifies the hidden exception, the collateral consequence, and the stitching necessary to keep the contractual pieces coherent. The risk of a poorly drafted clause or a relevant omission is disproportionate in transactions of this magnitude. In a context in which billions are at stake, no machine can replace human interpretation that considers the parties’ interests, regulatory limits, and the practical impacts of the chosen wording.

The use of solutions for monitoring post-closing obligations has also assumed a relevant role in the practice of law firms. Internal management tools can structure the follow-up of contractual clauses such as reporting deadlines, financial covenants, regulatory obligations, and non-compete commitments. Workflow systems can be programmed to assign tasks, issue automatic alerts, and organize workstreams, reducing failures, facilitating management, and bringing greater predictability.

Another point of interest that deserves mention is a phenomenon which, although still at a stage of consolidation, already presents itself as a vector of innovation for all types of legal relationships and not only for M&A transactions. We are referring to the resolution of disputes by digital means.

It is now possible to identify Online Dispute Resolution platforms that offer the possibility of resolving disputes entirely in a virtual environment through assisted negotiation, mediation, or even automated decisions in lower-complexity cases. In the field of M&A transactions, the use of such platforms may be considered, for example, for post-closing divergences involving earn-out clauses, indemnifications arising from breaches of representations and warranties, or breaches of ancillary obligations.

The appeal lies in speed and cost reduction, but there are relevant questions such as which jurisdiction would recognize these decisions, which authority would have competence to review or set aside the result, how to ensure procedural balance between the parties, and how to avoid bias in decisions produced by automated tools. These are issues that still lack consolidated answers, but that are already on the near horizon of transactions.

All these practices are aligned with a regulatory environment undergoing profound change. The European AI Act, in force since 2024, inaugurates a progressive regime of prohibitions and obligations for systems classified as high risk, requiring that operations supported by technology be anchored in solid compliance mechanisms. The NIST AI Risk Management Framework, complemented by the profile aimed at generative models, provides technical parameters for risk management, while ISO/IEC 42001 sets international governance standards for artificial intelligence systems. Alongside these normative instruments, there are soft law initiatives such as the UNIDROIT Principles of International Commercial Contracts and the UNIDROIT Principles on Digital Assets and Private Law, which can be adapted to strengthen technological audit clauses and responsibility obligations in cross-border contracts.

This normative backdrop reinforces what practice already shows. Artificial intelligence is transforming M&A transactions, but efficiency only turns into value when accompanied by robust governance and the lawyer’s critical supervision.

Finally, it is essential to note that despite advances, the technological ecosystem described remains fragmented. There are effective tools for contract drafting, others quite useful for document review in due diligence, and still others aimed at task management and monitoring of obligations. None, however, manages to cover in an integrated manner all stages of an M&A transaction with the depth required by legal work. The result is that law firms need to combine different applications, often from different providers, which requires organization, discipline, and additional care with data governance.

In this scenario, investment decisions become decisive. Large firms are able to absorb more sophisticated solutions because they have the budget for premium platform licensing and teams dedicated to adapting these technologies to their workflows. Medium and small firms, on the other hand, face cost and adaptation barriers, which limit access and reinforce competitive inequality. More complete and integrated platforms will certainly emerge soon, but the question that matters remains unanswered, namely whether these solutions will be available to all firms or whether they will consolidate as a privilege of a few players capable of investing heavily in technology.

The future will tell whether legal technology will become a vector for the democratization of efficiency or whether it will turn into yet another driver of market concentration. In the meantime, the sound path remains one of prudent and progressive use.

We may once again find ourselves at the threshold of a historical rupture:
If writing reinvented memory, the printing press democratized knowledge, and the digital revolution dissolved borders, artificial intelligence is now reshaping the very contours of legal rationality. There is no defined script. Upcoming M&A transactions may unveil both the promise of radical efficiency and the perils of blind trust in systems we do not yet fully understand.
Between algorithms and clauses, between speed and caution, one question remains:
will we shape the tools, or will we allow them to shape us?

REFERENCES

AMERICAN BAR ASSOCIATION. Formal Opinion 512: Lawyers’ Use of Generative AI. July 29, 2024. Available at: https://www.americanbar.org/news/abanews/aba-news-archives/2024/07/aba-issues-first-ethics-guidance-ai-tools/. Accessed: Sept. 6, 2025.

BAIN & COMPANY. Generative AI in M&A: You’re Not Behind—Yet. Feb. 4, 2025. Available at: https://www.bain.com/insights/generative-ai-m-and-a-report-2025/. Accessed: Sept. 6, 2025.

BUSINESS INSIDER. How AI was used in this $1.5 billion M&A deal (Kraken–NinjaTrader). 2025. Available at: https://www.businessinsider.com/how-ai-was-used-kraken-ninjatrader-acquisition-2025-4. Accessed: Sept. 6, 2025.

EUROPEAN COMMISSION. AI Act – Application timeline. Aug. 1, 2024. Available at: https://digital-strategy.ec.europa.eu/en/policies/regulatory-framework-ai. Accessed: Sept. 6, 2025.

EUROPEAN UNION. Regulation (EU) 2024/1689 of the European Parliament and of the Council of 13 June 2024 laying down harmonised rules on artificial intelligence (Artificial Intelligence Act). Official Journal of the European Union, 12 July 2024. Available at: https://eur-lex.europa.eu/eli/reg/2024/1689/oj/eng. Accessed: Sept. 1, 2025.

FINANCIAL TIMES. AI agents still need a human in the mix for legal tasks. 2025. Available at: https://www.ft.com/content/05e6e97e-26e7-4dab-b035-793c1a0f0ed8. Accessed: Sept. 6, 2025.

FLORIDI, Luciano. The Fourth Revolution: How the Infosphere Is Reshaping Human Reality. Oxford: Oxford University Press, 2014. Available at: https://www.oii.ox.ac.uk/research/publications/the-fourth-revolution/. Accessed: Sept. 1, 2025.

GENERAL COURT OF THE EUROPEAN UNION. T-553/23, Latombe v Commission (decision concerning the EU–US Data Privacy Framework). Sept. 3, 2025. Coverage: REUTERS. Available at: https://www.reuters.com/sustainability/boards-policy-regulation/eu-court-backs-latest-data-transfer-deal-agreed-by-us-eu-2025-09-03/. Accessed: Sept. 6, 2025.

HARARI, Yuval Noah. Nexus: A Brief History of Information Networks from the Stone Age to AI. New York: Random House, 2024.

INTERNATIONAL ORGANIZATION FOR STANDARDIZATION; INTERNATIONAL ELECTROTECHNICAL COMMISSION. ISO/IEC 42001:2023 — Artificial intelligence management system — Requirements. Geneva: ISO/IEC, 2023. Available at: https://www.iso.org/standard/42001. Accessed: Sept. 6, 2025.

KATSH, Ethan; RABINOVICH-EINY, Orna. Digital Justice: Technology and the Internet of Disputes. Oxford: Oxford University Press, 2017. Available at: https://global.oup.com/academic/product/digital-justice-9780190464597. Accessed: Sept. 6, 2025.

LEE, Kai-Fu; CHEN, Qiufan. AI 2041: Ten Visions for Our Future. New York: Crown/Random House, 2021. Revised ed.: 2024.

NATIONAL INSTITUTE OF STANDARDS AND TECHNOLOGY (NIST). AI Risk Management Framework 1.0 (NIST AI 100-1). Gaithersburg, MD: NIST, 2023. Available at: https://nvlpubs.nist.gov/nistpubs/ai/nist.ai.100-1.pdf. Accessed: Sept. 6, 2025.

NATIONAL INSTITUTE OF STANDARDS AND TECHNOLOGY (NIST). Generative AI Profile (NIST AI 600-1). Gaithersburg, MD: NIST, 2024. Available at: https://nvlpubs.nist.gov/nistpubs/ai/NIST.AI.600-1.pdf. Accessed: Sept. 6, 2025.

REUTERS. Legal AI startup Eudia opens law firm under Arizona program. Sept. 3, 2025. Available at: https://www.reuters.com/legal/legalindustry/legal-ai-startup-eudia-opens-law-firm-under-arizona-program-2025-09-03/. Accessed: Sept. 6, 2025.

UNIDROIT. UNIDROIT Principles of International Commercial Contracts (PICC) 2016. Rome: UNIDROIT, 2016. Available at: https://www.unidroit.org/wp-content/uploads/2021/06/Unidroit-Principles-2016-English-bl.pdf. Accessed: Sept. 6, 2025.

UNIDROIT. Principles on Digital Assets and Private Law. Rome: UNIDROIT, 2023. Available at: https://www.unidroit.org/work-in-progress/digital-assets-and-private-law/. Accessed: Sept. 6, 2025.

UNITED NATIONS COMMISSION ON INTERNATIONAL TRADE LAW (UNCITRAL). Technical Notes on Online Dispute Resolution. New York: United Nations, 2017. Available at: https://uncitral.un.org/en/texts/odr/technotes/odr_technotes. Accessed: Sept. 9, 2025.