AI usage is in for a swift expansion, with Grand View Research projecting an impressive annual growth rate of 37.3% from 2023 to 2030. This growth prediction also spills over into mergers and acquisitions (M&A) territory. 


So, where exactly does AI fit into your M&A strategy? This detailed overview explores the growing influence of AI technologies in M&A and their anticipated impact on transactions in the near future.

How is AI transforming the due diligence process?

AI is transforming due diligence in M&A transactions across different stages. Due diligence, a critical phase in the M&A process, involves thorough investigations and evaluations to ensure informed decision-making. Traditionally, this process has been time-consuming, labor-intensive, and prone to human error. However, AI is set to redefine how due diligence is conducted, bringing unprecedented efficiency, accuracy, and insight.


McKinsey Global Institute’s recent research shows an increase in the value of productivity from artificial intelligence and analytics by 15% to 40% compared to previous generations of the technology. These figures are expected to double as generative AI spreads more diffusely across the global workplace. Stakeholders across the board need to explore ways to leverage AI to gain a competitive edge in their M&A activities.

The current landscape for AI-powered due diligence

Here is a breakdown of how AI tools and technologies are being leveraged to streamline due diligence processes. 

AI Skills in M&A Due Diligence

AI significantly enhances the M&A due diligence process by efficiently leveraging its ability to analyze large volumes of documents, contracts, and financial data. Advanced machine learning algorithms can autonomously learn from data, identifying patterns, anomalies, and inconsistencies without requiring explicit programming for each new task. This capability allows AI to streamline and accelerate the due diligence process, uncovering critical insights that human analysts might miss. Additionally, natural language processing (NLP) enables AI to understand and generate human language, making it adept at analyzing text-heavy documents, extracting relevant information, and providing deeper contextual understanding. These skills make AI an invaluable tool for improving the accuracy and efficiency of due diligence in the following phases:

Public information analysis

The buyer's initial due diligence phase typically involves inspecting publicly accessible information about the target company. Given the large amount of data available, AI is ideal for reducing the burden of a lengthy initial assessment. AI scours public records to uncover tax and legal disputes, aiding in creating tailored information requests and questions for management. The buyer can process more information, thereby increasing the effectiveness of their investigation.

VDR setup

The grunt work of setting up a virtual data room (VDR) typically takes up a lot of resources. During setup, the seller has to ensure sensitive information is excluded while also providing the buyer with everything they require. In this phase, sellers can leverage AI to organize documents, identify sensitive information, and suggest redactions. This approach significantly improves efficiency in document-heavy transactions. AI algorithms can streamline the process, reducing the time and resources needed to set up VDR.

VDR due diligence

AI excels in identifying gaps, summarizing documents, and detecting critical clauses, significantly speeding up the due diligence process. While human oversight remains necessary for complex interdependencies, AI helps buyers efficiently manage large transactions, even those involving multilingual documents. By recognizing standardized legal language, AI-powered software can quickly identify critical clauses, such as indemnification and non-compete provisions, and draft initial due diligence reports, highlighting key issues for further review.

Limitations of AI in M&A Due Diligence

Despite its strengths, AI does face notable hurdles in the M&A due diligence context. The primary challenge lies in the accessibility of critical information. Data housed in virtual data rooms (VDRs) is well secured to ensure confidentiality. Also, sellers are often reluctant to share sensitive information for AI training purposes. Such restrictions limit AI’s ability to adapt in real time during transactions. 


Moreover, the reliability and data protection concerns associated with AI, particularly large language models (LLMs), are significant. Even sophisticated models can fabricate facts or unintentionally reveal sensitive information from their training data. These risks necessitate cautious, supplementary use of AI in due diligence, with human oversight and rigorous verification to ensure the integrity and security of M&A processes.


Another hurdle is making information digestible for AI. Due diligence extends beyond legal and financial documents to include soft information, such as insights from management interviews or unwritten regulatory practices. AI algorithms need access to this data to learn patterns and accurately assess risks. Bridging this gap requires presenting such behavior in written form to enable AI to identify and apply these patterns.


The impact of AI on due diligence goes beyond just making the process more thorough and efficient. It could potentially change the way M&A procedures are done. A good example would be benchmarks for "fairly disclosed" facts and how they will be assessed by each party in the transaction. Considerations must be made for every legal concept referencing human knowledge, capabilities, and attention. Integrating AI introduces new risks, such as cybersecurity threats, data privacy issues, and algorithmic biases. This is a push for companies to adopt thorough due diligence practices tailored to the AI era and negotiate specific contractual safeguards in M&A agreements covering GDPR-related provisions and disclosure of AI utilization for AI-generated items among others.

Sigtax’s Outlook for AI-Powered M&A Strategies

Sigtax supports investors in navigating the complexities of AI in their transactions. We provide risk assessment frameworks customized to the target company's local regulatory environment. In addition, our team of experts offers comprehensive support for sellers in Switzerland utilizing advanced risk intelligence in due diligence. 


Best-in-class M&A strategies acknowledge that AI can’t replace a skilled M&A practitioner’s rigorous screening, diligence, and execution. As consultants, ensuring the technology is used effectively and ethically is a priority. We help clients manage data accessibility and protection concerns, ensuring compliance with GDPR and other regulations in their negotiations. Sigtax offers critical oversight, validating AI-generated insights and addressing potential inaccuracies or biases. This comprehensive approach includes advising clients on best practices for AI-powered procedures, optimizing the benefits of AI while mitigating associated risks, and ultimately facilitating more informed and secure M&A decisions for Swiss businesses.

A look to the future 

By understanding AI's implications in due diligence, stakeholders in the M&A ecosystem can better prepare for a future where technology augments human capabilities and reshapes the landscape of business acquisitions and mergers. Adopting AI will enhance the quality of analyses and uncover hidden risks and opportunities. 


With expert guidance from Sigtax, you can leverage a comprehensive approach that equips investors with the tools to navigate the complexities of AI in M&A, safeguarding against potential risks while capitalizing on technological advancements. Contact Sigtax today and let our experts guide you through the changing business environment.

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