Navigating The Digital Frontier: AI In Mergers And Acquisitions Presently, AI remains unregulated in India and therefore currently there are no guidelines for development or use of AI software in the M&A space. Technology in M&A transactions have come a long way in the last decade or so. In the early 2000’s and up until a decade or so later, physical data rooms were the norm...
Navigating The Digital Frontier: AI In Mergers And Acquisitions
Presently, AI remains unregulated in India and therefore currently there are no guidelines for development or use of AI software in the M&A space.
Technology in M&A transactions have come a long way in the last decade or so. In the early 2000’s and up until a decade or so later, physical data rooms were the norm and advisers had to travel to the offices of the target company to physically review documents and prepare their due diligence report. Now, virtual data rooms are the norm, and they provide unparalleled security, safety and confidentiality of the data room documents which even physical data rooms do not. Similarly, in the pre-covid era, representatives from the acquirers, the target company and their respective advisers would travel for day long meetings to negotiate and finalize transaction documents. However, now, online negotiations are the norm, and they provide cost and time efficiency that physical negotiations do not provide.
None of these changes in the M&A transaction landscape have come by easily. Initially, most companies were resistant to these changes, with only a few outliers embracing the change. However, over time, these changes on account of their cost, time or practical efficiencies have slowly taken over and become the norm of the industry.
On the same lines, Artificial Intelligence (AI) will be a game changer in the transaction landscape and in this article, we explore the benefits as well as the potential shortcomings/ legal challenges in the use of AI in the M&A deal making landscape.
From a deal making perspective AI can be a useful tool in the following domains: (a) due diligence; (b) deal documentation and negotiation; and (c) predictive analysis for deal success.
AI-powered contract negotiation tools are designed to support legal professionals in drafting agreements that align with their clients' objectives while minimizing legal exposure
(a) Due Diligence:
Traditionally, due diligence has been a labor-intensive and time-consuming process, requiring exhaustive reviews of legal documents, financial statements, and other critical information. However, with the help of AI, the domain is undergoing a significant transformation. Advanced algorithms can now swiftly analyze extensive datasets at unprecedented speeds, identifying potential risks and opportunities that might have gone unnoticed in the manual review process, which also makes the due- diligence efficient and effective.
AI-powered due diligence tools leverage Natural Language Processing (“NLP”) and machine learning to comprehend complex legal language and decode complex contractual relationships. This not only expedites the due diligence process but also improves accuracy, minimizing the risk of oversight and ensuring a more comprehensive evaluation of target companies.
(b) Deal documentation and Negotiation:
One of the most significant breakthroughs in AI applications for M&A lies in the realm of contract analysis and negotiation. Machine learning algorithms can rapidly assess bulk of contracts, highlighting crucial provisions, potential liabilities, and contractual risks. This capability empowers legal teams to make informed decisions, negotiate more effectively, and streamline the overall negotiation process. AI-powered contract negotiation tools are designed to support legal professionals in drafting agreements that align with their clients’ objectives while minimizing legal exposure. The outcome is a more streamlined and collaborative negotiation process, promoting transparency and expediting deal closures. Additionally, there are AI powered bots that also record and minute the negotiations in the hope of providing bias free and accurate transcripts of deal negotiations.
(c) Predictive Analytics for Deal Success:
In the competitive landscape of M&A, anticipating the outcome of a deal remains a persistent challenge. AI, equipped with its predictive analytics capabilities, stands out as a notable change in this regard.
Through the analysis of historical deal data, market trends, and various external factors, AI algorithms offer valuable insights into the potential success or challenges associated with a specific transaction.
Legal professionals can leverage these predictive analytics tools to evaluate the feasibility of a deal, identify potential obstacles, and develop strategies to minimize risks. AI use will not only enhance decision-making but will also empower legal teams to proactively address issues before they arise, contributing to the overall success of the M&A transaction.
As discussed above, AI as a tool can be extremely useful in a transaction, however it does come with its fair share of ethical and legal challenges.
Some of the key challenges revolve around data privacy, confidentiality and predictive bias. Since AI is a third-party tool, sharing vast amounts of confidential data with a third party that is not governed by the same confidentiality and non-disclosure requirements that legal advisers are subject to could potentially raise serious challenges.
Similarly, the predictive bias of the AI software in analyzing data or in contract negotiation could potentially create issues if they are relied on heavily by lawyers who are not able to identify the biases which could then have a negative outcome for the clients as well as the deal itself.
EU regulation of AI
The European Parliament and Council reached political agreement in December 2023 on the European Union’s Artificial Intelligence Act (“EU AI Act”) and it is a global first and makes EU the frontrunner for regulation of AI. The EU AI Act follows a risk-based approach towards regulation classifying AI systems into: (a) unacceptable risk; (b) high-risk; (c) limited risk; and (d) minimal / no-risk. AI systems that are classified as posing “unacceptable risk” which pose clear threat to fundamental rights are banned in the EU, and the remaining categories will be regulated based on their risk posed, i.e. the greater the risk the greater the regulation.
Since the text of EU AI Act is not available publicly, the full details of the EU AI Act remain unknown at this stage with only the limited information relating to harmonised rules on AI1 being available.
It still remains to be seen how the EU AI Act will impact AI software in the M&A space, but presumably the type of data analyzed by the software would determine the amount of regulation and compliance required.
Way forward for India
Presently, AI remains unregulated in India and therefore currently there are no guidelines for development or use of AI software in the M&A space. However, software developers in the AI space can be guided by the EU principles (as and when those become available) since most software will have global application/ use.
Disclaimer – The views expressed in this article are the personal views of the authors and are purely informative in nature.
Kaushalya’s has over 14 years of experience in practicing corporate and commercial law. She has a well-rounded practice with a good mix of advisory and transactional work. Her focus areas are largely mergers and acquisitions, private equity and venture capital. Kaushalya has been recognized as a “Notable Practitioner” in M&A by IFLR 1000 and she is also part of IWIRC (International Women’s Insolvency & Restructuring Confederation), India. Prior to joining C&M, she was with Shardul Amarchand Mangaldas & Co and has previously worked with leading law firms such as Amarchand Mangaldas and P&A Law Offices.
By: - Harshita Sawla
Harshita has over 3 years of experience in practicing corporate and commercial law. She is graduated from Amity University Madhya Pradesh in year 2021. She has an experience in Company Secretarial work along with general corporate and transactional work. In her previous role, she has worked as an in-house counsel to advise global startups and incorporating entities in US. Her main focus areas include private equity, venture capital, and mergers and acquisitions. Prior to Chandhiok & Mahajan, she has worked with Algo Legal and Upekkha, a leading early-stage fund and SaaS accelerator.