Artificial Intelligence (AI) has moved beyond being a mere enabler to becoming a core strategic element, shaping both the execution process and the object of M&A transactions. Law firms and M&A lawyers must restructure their operating models to harness the full potential of AI, while dealing with the complex legal risks it brings.
1. The new context – the era of technology
1.1. The modern M&A landscape and the status of AI
Companies developing or applying AI are driving mega deals and strategic partnerships, accounting for the majority of deals in recent M&A deals. The characteristic of AI-related deals is the multidisciplinary complexity. They require the involvement of a large team of legal experts because they simultaneously touch on a variety of legal fields, including intellectual property (IP), data privacy, finance, infrastructure, environment, and energy.
This intersection forces leading law firms (Big Law) to build integrated, seamless consulting capabilities across professional fields. Leading law firms are now taking on the role of Technology Advisors, developing extensive expertise in large language models (LLMs), machine learning, and other AI technologies. The goal is to provide strategic advice to clients across the entire "AI tech stack", [1]from investors and platform model developers to application adopters. This is a paradigm shift in which AI is both an M&A object and an M&A object. as well as an M&A tool, requiring deep technical and legal understanding to succeed.
1.2. Classification and impact of AI technology in law
AI tools used in the legal field of M&A can be broadly categorized into two main groups: Predictive AI and Generative AI. Predictive AI focuses on extracting and classifying data from existing documents. Meanwhile, Generative AI (GenAI) is used to speed up creative tasks such as drafting, summarizing, or synthesizing legal documents.
Legal technology platforms that lead the market and fundamentally change the workflow of leading law firms include:
Kira systems (Litera): Many of the top 20 law firms have used Kira, an AI/ML software that automatically reads and extracts data from contracts. Freshfields Bruckhaus Deringer is a long-time customer of Kira and appreciates the Quick Study feature that allows for fast AI training to identify new terms. Allen & Overy has also officially licensed Kira system-wide since 2018 for M&A due diligence, lease review, and regulatory compliance. A&O still incorporates AI iManage RAVN shows that the company takes advantage of multiple AI platforms depending on the situation (Kira for lawyers to use on a daily basis, RAVN for large projects with technical support). Latham & Watkins was also an early investor in the technology in 2017 Latham adopted Kira in its M&A process, which helped speed up due diligence and was hailed by CEO Kira as "at the forefront of innovation". Similarly, Sidley Austin, DLA Piper, Skadden were among more than 90 global law firms that used Kira before Kira was acquired by Litera in 2021.
Luminance: This is another AI platform (born in the UK) that uses semi-supervisory ML to read and understand legal documents. Dentons, the world's largest law firm in terms of headcount, has deployed Luminance for contract analysis and eDiscovery across multiple offices. In 2021, Dentons expanded Luminance to its Malaysian branch, after its European and Middle East offices had previously used Luminance's Diligence to review contracts and Discovery to serve litigation. Dentons' global use of Luminance shows confidence in this AI's ability to save time compared to traditional methods. In addition to Dentons, Slaughter and May (a British law firm) has also supported the implementation of this AI, and Luminance announced that it has been used by more than 300 organizations, including a fifth of the top 100 global law firms.
Harvey (Generative AI): The rise of Generative AI saw major law firms quickly get involved. Allen & Overy made headlines when it announced in February 2023 that it was the first firm to partner with Harvey, a startup to build a customized GPT-4 platform for legal services. Harvey is integrated to assist A&O lawyers in tasks such as automated contract drafting, due diligence analysis, and multilingual legal research, saving clients time and money. Following suit, Latham & Watkins also signed a contract to deploy Harvey AI on a company-wide scale by 2025. This is a very remarkable move because Latham & Watkins is the world's 2nd largest revenue law firm. Latham has purchased corporate licenses for its 3,600 lawyers to use Harvey daily, integrating it into workflows from legal research to document analysis to document drafting. Latham & Watkins aims to have all AI-powered lawyers trained by the end of the year, and sees it as a strategic step in legal services innovation. The deployment of GPT by leading names such as A&O, Latham & Watkins shows that generative AI is gradually becoming an indispensable support tool in legal service delivery today.
LawGeex and other contract AIs: White & Case made its mark with the implementation of LawGeex, an AI solution that automatically reviews contracts commonly used by corporate legal departments. LawGeex uses AI to compare contracts with standard policies, suggest amendments, and even automatically redline contracts. What's special is that LawGeex used to serve enterprise customers (eBay, Office Depot), but White & Case applied it internally to speed up regular contract processing. This is a typical example of a law firm actively borrowing technology from clients to "take shortcuts to catch up" with automation needs. Similarly, many other companies are also testing contract AI tools: Clifford Chance uses Kira and Luminance for due diligence; Baker McKenzie and Orrick tried eBrevia (an AI that extracts contracts). In addition, Litera (after buying Kira) also offers the Litera Transact package that supports the automation of the transaction process (smart checklist creation, signing management) – used by Maslon or Wilson Sonsini and may soon spread to top companies.
2. Intensive application of AI in law firm M&A service provision
AI creates the greatest added value for M&A lawyers in the due diligence (DD) phase, transforming the process from a manual search/discovery effort, limited by time and manpower, into an integrated risk management process.
2.1. Optimize contract legal due diligence
AI has revolutionized contract review, which is one of the most time-consuming and labor-intensive tasks in traditional M&A.
AI-powered platforms can quickly scan thousands of contracts and legal documents to identify important terms, obligations, renewal conditions, or deviations from standard language. Natural Language Processing (NLP) technology is particularly useful in detecting inconsistencies, missing signatures, or potentially liable terms. The integration of AI can reduce the time it takes to review contracts from weeks to days or even hours, while maintaining a high level of accuracy.
2.2. Comprehensive risk management and interdisciplinary data analysis
One of the most important contributions of AI is to expand the scope of due diligence into non-traditional sectors, providing a more comprehensive risk assessment for trading:
Compliance assessment: AI automatically checks compliance documentation, licenses, and certifications against local, national, and international regulatory databases. This is especially essential in highly regulated industries such as healthcare or finance.
Financial data analysis: Machine learning models can analyze historical financial data to detect anomalies, forecast future performance, and warn of deviations in revenue or expense reports. AI due diligence platforms are often integrated with enterprise resource planning (ERP) systems to access real-time financial data, helping to validate financial positions and predict post-acquisition value.
Assess IT systems and cybersecurity: In technology and data deals, cybersecurity risk is paramount. The AI system is used to analyze logs, network behavior, and past breach data to assess the resilience of the target company's IT infrastructure and digital assets.
The integration of AI in due diligence has helped to minimize the inherent flaws of manual review, allowing lawyers to identify additional risks that might have previously been overlooked. It helps lawyers move from focusing solely on legal documents to synthesizing and advising on an "interdisciplinary chain of risk" that includes both financial and cybersecurity risks.
2.3. Deal drafting and management support
AI is not limited to reviewing but also assists lawyers in management and drafting tasks. Attorneys can leverage AI to streamline the preparation of a list of due diligence requests and assist in drafting basic documents such as Confidentiality Agreements by referencing a pre-established "negotiation manual" of standard terms.
Furthermore, generative AI can be used to draft the initial transaction summary of the due diligence report, highlighting critical issues that need attention or points that need to be secured for compensation in the purchase and sale agreement.
3. The strategic role and economic efficiency of AI
The adoption of AI in M&A is reshaping the economic structure of law firms, allowing them to transition from a time-based fee model to a value- and efficiency-based model.
3.1. Superior performance and competitive advantage
In addition to the benefits of speed, AI also allows lawyers to provide superior quality of advice. Thanks to AI handling routine tasks, lawyers have time to perform deeper, more comprehensive analysis, which was previously impossible within the cost and time limits of the transaction.
For law firms, the integration of AI becomes a strong competitive advantage. The ability to demonstrate more efficient workflows and provide high-speed service has made AI an important advantage in service presentations to potential customers. Moreover, the efficient workflow brought by AI also has a positive impact on the company's human resources, helping to improve the work-life balance for young lawyers and leading to better retention of talented lawyers.
3.2. Changing the billing model and saving costs
AI is creating shifting pressure in the legal service charging model. Automating routine activities such as document review significantly reduces the cost of M&A transactions. As a result, law firms are being pushed to shift from the traditional hourly billing model to fixed pricing or semi-fixed.
This change is a direct response to the speed of AI. When a job that took hundreds of hours of manual work is now only a few hours by machine, lawyers can't continue to charge the old way. This transforms lawyers from part-time to value sellers. Profits are generated through the ability to provide deeper analysis and the speed of transaction completion, creating a positive loop: investing in AI, achieving high efficiency, adopting a more attractive fee model, thereby attracting customers and creating a competitive advantage. Clients can also use AI tools to perform preliminary analyses themselves before hiring outside counsel, changing when and how lawyers are involved in deals. While some companies have considered charging separately for AI tools, this cost is predicted to become standardized, just like the cost of regular software licensing.
4. Some challenges and requirements in the process of using AI in M&A
As AI is deeply integrated into the M&A process, lawyers face new ethical responsibilities and complex due diligence requirements related to the target technology.
The integration of AI is driving a fundamental shift in the skill requirements and training models for M&A lawyers.
Firstly, AI rapidly changes the important skills of lawyers
AI frees young lawyers from "conventional administrative" tasks and repetitive tasks. This shift allows them to focus their time on more complex legal issues that require higher analytical, problem-solving, and strategic advisory skills.
M&A lawyers in the coming time must build a new skill set including:
- Foundational technology skills: A basic understanding of AI concepts such as machine learning, deep learning, neural networks, NLP, and LLMs, including assessing the risks, limitations, and benefits of AI.
- AI management and command engineers: This is an emerging skill that requires lawyers to know how to formulate accurate, contextually appropriate legal queries or instructions for the AI model. This skill helps to minimize ambiguity and ensure accurate, relevant outputs are obtained.
If AI automates clause extraction, the value of lawyers lies in explaining the relationship between those clauses and providing risk-based advice. Lawyers need to become information architects, know how to ask the right questions to AI to synthesize data into legal business strategies.
Secondly, the challenge in training talented lawyers
The use of AI tools in M&A document review poses a "strange paradox". Despite the increased efficiency of AI, many are concerned that it hinders young lawyers' ability to learn the trade because they no longer get to experience the manual identification and extraction of contract terms.
The core challenge is the elimination of the possibility of dependence on technology. This is a mental effort and a challenge encountered when processing complex information. In traditional training, the struggle of reviewing thousands of documents is a source of cognitive friction, encouraging critical thinking and problem-solving skills.
To address this lack of experience, law firms need to shift to a more intentional approach to learning and development. The solution is through structured, interactive, well-planned training programs that are tied to real work, replacing the traditional method that is somewhat outdated. These programs should emphasize soft skills training such as critical thinking, problem-solving, and creativity.
Third, it requires close cooperation between sectors
The complexity of technology M&A transactions requires an interdisciplinary model of collaboration. Leading law firms are building integrated teams that include not only M&A lawyers but also IP specialists, data security specialists, and those with advanced degrees in science, mathematics, technology, and engineering. This combination gives the law firm the ability to anticipate its clients' most complex legal and commercial challenges and provide the seamless, integrated legal support needed to navigate high-tech M&A deals to the next level.
In conclusion, AI has become an indispensable element in the delivery of modern M&A legal services, playing a key role in optimizing contract due diligence performance, comprehensive risk management, and changing cost structures. It can be said with certainty that AI is almost completely changing the leading law firms providing legal services in the field of M&A.
