The Increasing Role of Artificial Intelligence In M&A

The use of Artificial Intelligence in cross-border mergers and acquisitions is accelerating as dealmakers explore new ways to apply it, from screening investment opportunities to risk modelling and accelerating deal timelines.

However, rising use of AI must be accompanied by expert human judgement and appropriate regulatory frameworks in order to safeguard against potentially damaging data errors or breaches in data security.

Currently, deployment of AI in M&A transactions is limited. Only 16% of M&A practitioners are using it, primarily in the pre-deal process, according to Bain & Company. However, Bain found that this is expected to rise to 80% in the next three years as AI-driven software applications become more mainstream among the deal community.

The increasing influence of AI on international M&A coincides with phenomenal growth in the value of the global generative AI market. Statista calculates that it will reach $36 billion this year, rocketing to $356 billion by 2030. 

Applications are multiplying both in the M&A realm and beyond, as part of a wider digital transformation agenda that is reshaping every aspect of life from manufacturing to defence, healthcare, transportation and government. 

Regulators and legislators are arguably lagging behind changes being wrought by AI, which may have far-reaching impacts on businesses, consumers and society – not all of which may be positive. The European Union has just enacted the EU AI Act, the world’s first comprehensive regulation for AI, although most rules will not apply until 2026.

Partners from Moore Global Corporate Finance (GCF) firms met recently in Budapest to consider opportunities for AI adoption in mid-market transactions, with a strong focus on responsible implementation and how to harness technology to deliver value for clients.

A large part of AI’s appeal for dealmakers is its ability to rapidly analyse huge amounts of data from financial performance to valuation criteria and to speedily review complex and lengthy legal documents.

Being able to tap into large repositories of information and extract accurate data and actionable insights helps advisers to identify strategic acquisition targets that could add long-term value to a client’s business.  Conversely, it could also help identify potential buyers for companies looking to divest subsidiaries or non-core parts of their operations.

Swedish venture capital firm EQT is a pioneer in using AI for deal sourcing. It built Motherbrain, an AI-driven platform, which it uses to identify emerging technology businesses that might otherwise have gone under the EQT radar. So far, Motherbrain has crunched data on more than 50 million individual businesses.

Number-crunching is only part of the AI story. GCF firms are examining other ways in which AI can make deal sourcing and execution more efficient and they are weighing potential for AI to generate higher returns for clients on transactions.

Deal parameters for venture capital firms seeking stakes in hot tech start-ups are different to those of advisers helping more mature or traditional businesses to structure and execute M&A agendas.

M&A strategy may be linked to geographic or sectoral diversification or to ownership changes in family-owned businesses. Access to detailed AI-generated data and intelligence could be particularly useful for cross-border deals involving privately-owned mid-market businesses – particularly those operating in sectors or markets where information on both buyers and sellers is difficult to obtain.

Rigorous inspection of facts and figures in data rooms is a customary part of due diligence before a deal is struck. It is both time-consuming and costly in terms of human resources required to scrutinise reams of documents and large quantities of data often held in multiple Excel spreadsheets. 

Likewise, the legal documentation process is labour-intensive yet vitally important to ensure a deal progresses smoothly and a client’s best interests are protected. Industry estimates suggest that AI can reduce due diligence document reviews by as much as 70%. It seems plausible given that AI software achieves a reading speed of 27,000 words per minute compared to around 238 words per minute for humans.

Risk analysis and mitigation is another aspect of the M&A process in which AI-powered solutions can be beneficial. Advisers can conduct complex risk modelling on variable factors such as interest rate or currency movements which can be of critical importance in cross-border deals.

It is relevant to the cost of capital whether a company is buying assets or operations in different territories, establishing a new supply chain or obtaining funding from a lender in a different jurisdiction.

AI is also revolutionising the landscape of Environmental, Social, and Governance (ESG) initiatives by enabling organisations to efficiently analyse and interpret vast amounts of ESG-related data. Advanced algorithms and machine learning tools can identify patterns, assess risks and predict future ESG outcomes – all vital in ensuring deals align with sustainability goals. These technologies enhance due diligence in M&A, facilitate real-time monitoring of ESG performance and improve transparency in reporting to stakeholders.

It is important to remember that while artificial intelligence may be capable of remarkable feats, it is also fallible.

AI can repeat and compound errors, even adding a few of its own for good measure. In an AI context, an error is called an ‘hallucination’ – a term which made its way into the Cambridge Dictionary in 2023 as AI hallucinations became headline news.

Microsoft executives were left red-faced during a demonstration of the company’s AI-powered Bing search engine: when asked to compare earnings of clothing retailers Gap and Lululemon, it got several key numbers wrong and appeared to invent others.

Meanwhile, a US lawyer faced sanctions after submitting AI-generated legal briefs citing fictitious cases as legal precedent. American Chief Justice John G Roberts advises: “Any use of AI requires caution and humility.”

There are also legitimate concerns about AI being fed confidential or sensitive data which may then inadvertently find its way into the public domain, as well as wider concerns about data security.

Financial and legal mistakes in an M&A context can have serious ramifications if they go unchecked, underlining the need for AI innovation to be overseen by humans with appropriate expertise and experience.

While financial and legal issues may scupper a deal – the most commonly cited reason for M&A transactions either failing completely or failing to achieve their objectives is culture. In cross-border deals, cultural alignment and shared cultural understanding and respect can be pivotal.

Successful deals are founded on strong inter-personal relationships and some deals can be years in the making as trust is slowly built. That is a role where advisers are unlikely to be usurped by AI any time soon.