GenAI in M&A – a deal process revolution?

October 2024  |  FEATURE | MERGERS & ACQUISITIONS

Financier Worldwide Magazine

October 2024 Issue

Generative artificial intelligence (GenAI) burst onto the scene with the promise of exciting efficiency and productivity benefits, as well as potentially greater returns for organisations. These tools utilise models that can automatically discover and learn the regularities or patterns in input data and produce new data consistent with those patterns.

According to Statista, the GenAI market is expected to grow by leaps and bounds between 2023 and 2030. It stood at just under $45bn at the end of 2023, nearly double its size in 2022. This growth of nearly $20bn annually is expected to continue until the end of the decade.

GenAI can be applied across myriad industries in many different ways. While it is still early in the adoption phase, companies are starting to take on new technologies and practices to enhance efficiency, drive value and streamline processes. This includes applications to assist the M&A process. AI could have a substantial impact on dealmaking, potentially creating greater value for organisations in the long term.

Transformative potential

At present, GenAI is only used sparingly in transactions. But that is very likely to change.

A Bain survey of 300 M&A practitioners about their views on using GenAI in the deal process found that only around 16 percent of respondents are currently doing so – however, 80 percent of respondents said they expect to use it within the next three years. Just 16 percent of companies are unlikely to turn to GenAI over that same period.

Early adopters are primarily in the technology, healthcare and finance sectors, and they tend to be larger companies with moderate M&A activity of three to five deals per year, according to Bain.

Similarly, a recent Accenture survey of 750 global C-suite executives with decision-making authority in M&A revealed that 64 percent of respondents expect GenAI to revolutionise M&A deal processes in the future, more than other recent technological advancements. Seventy percent of M&A decision makers believe GenAI can help boost expected returns on their transactions. There is growing belief among dealmakers that GenAI will improve the post-deal phase of transactions too, though organisations are yet to fully exploit this area. Only 35 percent of firms say they are investing heavily in the technology for M&A purposes.

GenAI’s transformative potential will continue to shape the M&A landscape, enhancing every stage of the process from target identification to negotiation to post-deal integration. By automating complex tasks, offering predictive insights, and improving decision making, AI can boost the efficiency and success rates of M&A deals. Companies that invest in AI capabilities and incorporate them into M&A strategies are likely to achieve superior outcomes and sustain a competitive advantage in the market.

Use cases

A prudent M&A strategy can differentiate companies, extend market share and condemn less savvy organisations to market irrelevance. The right transaction can eliminate competitors, grow capabilities, achieve economies of scale and reduce costs.

In recent years, many companies have turned to technology to streamline and accelerate M&A processes. Great strides have been made with respect to virtual data rooms, cloud-based platforms, big data and analytics. A combination of these tools has transformed due diligence, collaboration, risk evaluation and decision making.

In the coming years, the most valuable technology could be GenAI.

GenAI is already being used for target sourcing. It can quickly analyse extensive datasets to identify potential acquisition targets that meet specific criteria. AI tools can forecast future performance, identify synergies and highlight potential risks, enabling companies to make more informed decisions. Case studies have shown that companies deploying AI for target identification and assessment have achieved higher success rates and better returns on investment.

By leveraging AI algorithms, companies can process large volumes of market data, financial reports and industry trends to find businesses that align with their strategic goals. GenAI can scan and analyse unstructured data, providing companies with actionable insights. As a result, GenAI is able to identify potential targets that might not be detected with traditional tools. This capability not only speeds up the target identification process but also improves the quality of the targets identified, making them more likely to result in successful acquisitions.

Another AI application is reviewing due diligence data. According to a Datasite study, most dealmakers say increased productivity is the biggest benefit of GenAI. The technology has the potential to speed up deals by 50 percent, with some of the most telling advances in due diligence. It can help dealmakers to quickly sort and summarise content, as well as improve the speed and accuracy of research, including relevant deal precedents and buyer recommendations.

By analysing historical data, market conditions and past financial performance, GenAI programmes can provide predictive analytics that help decision makers evaluate the potential risks and benefits of a deal.

The crux of this process is data. AI algorithms must be provided with the right data input to allow them to make constructive decisions. Companies produce huge quantities of data across a wide spectrum of capabilities, and AI learning models must be granted access to these stores of data. While AI may not be sophisticated enough to understand what it is measuring – be it culture or leadership, for example – once a target company’s capabilities have been roughly approximated, the software can connect an organisation’s attributes to the results of a deal, and discover a formula to accurately predict which companies are likely to combine most successfully.

GenAI can be useful in other areas, such as managing a data room, automated filing, advanced document search, and document question and response.

Challenges

Though many organisations are embracing GenAI for M&A, there are drawbacks. According to Bain, data inaccuracy, privacy and cyber security are the most frequently identified risks.

Data inaccuracy challenges, for example, may require companies to review or even redo work completed by GenAI, thus negating its advantages. And from a speed perspective, GenAI might not be as efficient as expected, taking organisations almost as much time to go through GenAI as it saves them in writing summaries or crafting reports.

Data privacy concerns in M&A are also significant, and may intensify when GenAI is involved – particularly as regulators are looking to strengthen data protection standards.

Potential sensitive data exposure may result from incompatible security protocols and systems, data mapping gaps, or substandard data governance. Legal restrictions on cross-border data transfers may disrupt the process. The physical or digital consolidation of data centres could raise the likelihood of data loss or breach. Outdated cyber security in legacy systems heightens vulnerability. And conflicts between the compliance standards of merging entities can lead to regulatory penalties.

A skills gaps can also cause issues for organisations. GenAI should not be able to operate independently of human supervision and input. No model is foolproof, and no large dataset is entirely free of errors. If used incorrectly or irresponsibly, it has the potential to deskill the workforce.

To help counteract some of these risks, companies should carefully vet the third parties they engage when sourcing AI technology. Collaborating only with GenAI solution providers who are trusted experts in the field goes a long way to alleviating some of the pressures.

Reinvention

Going forward, dealmakers will need to find ways to take advantage of GenAI’s potential and work toward reinventing the M&A function.

To fully benefit from the advantages offered by GenAI, dealmakers and executive teams should continuously educate themselves on the technology, identify areas of the M&A lifecycle where it can offer the greatest boosts, and assess the effectiveness of their supporting infrastructure.

Generating and preserving value is a pressing challenge for companies engaged in M&A, particularly in the post-deal phase. Dealmakers should explore the value that GenAI can bring to transactions.

GenAI is a fast moving, evolving space and its impact will continue to grow. Dealmakers need to prepare their organisations for the potential changes GenAI is set to bring. Developing the skills to adapt to this new paradigm will be imperative as GenAI is further embedded into the deal process.

In an ongoing process of renewal, optimisation and value creation, GenAI may revolutionise transactions. To navigate these developments, companies should take an organised, structured approach. They should also ensure that GenAI is deployed responsibly, ethically and safely. Efforts to mitigate leaks of confidential or personal information are paramount. While value generation is a key driver, there are risks if it is pursued at the expense of data security.

Gathering momentum

Despite the risks, the direction of travel is increasingly clear: the applications of GenAI in M&A transactions are gaining momentum and expected to accelerate significantly in the years ahead. The question is not whether GenAI will impact dealmaking – it already is – but rather to what extent, how rapidly, and with what consequences

According to Accenture, more than two-thirds of executives are already working with consulting partners to build bespoke GenAI tools for M&A. Challenges along the way include a need to learn complex technical skills, to gather fit-for-purpose data on which the model can be trained and to deploy the necessary computing power demanded by a homegrown GenAI model.

Other organisations are instead acquiring a model from a selected partner and then building the supporting ecosystem around it. Whether they build or buy, more and more companies are turning to GenAI to augment key features of their M&A process.

Target identification, virtual data rooms, due diligence and other facets of dealmaking will continue to advance alongside the growing prevalence of GenAI. In this rapidly evolving space, companies should stay informed about the latest developments to maintain an edge.

Deploying GenAI does not, on its own, guarantee success, but it can certainly strengthen a company’s approach to M&A. Companies will need to evolve with GenAI over time and address the risks that come with its adoption. This requires thoughtful management, careful direction and clear guardrails.

While it will not replace a skilled M&A practitioner, by proportionately aligning investments into GenAI, organisations may outperform their peers and drive shareholder value.

© Financier Worldwide

BY

Richard Summerfield