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How Generative AI Can Help Investors Redefine the Competitive Deal Landscape


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By Dr. Khalid A. Khan

The transformative potential of generative AI (GenAI) could have a dramatic impact on corporate transactions by helping investors more accurately identify potential deals and execute them with greater speed and higher returns.

One reason mergers and acquisitions (M&A) fail to deliver on their objectives is that humans are making decisions about them by synthesizing data in limited ways. But GenAI holds the promise of significantly increasing the competitive advantage by detecting possible M&A targets early and by improving the diligence conducted on expected M&A integration and value creation levers.

GenAI makes this possible because it augments human decision-making through its unique ability to summarize, synthesize, infer and, importantly, create new insights from large swaths of qualitative, unstructured and fragmented pockets of institutional knowledge, and publicly available data.

GenAI can have a big impact in transaction strategy:

• It can be a due diligence tool to investigate the deal market and identify where to allocate capital, as many players compete to transform business models.

• It can simplify the massive complexities before a transaction closes and on day one of new ownership.

• It can point to new products and services that boost value.

GenAI can be a brainstorm partner and a copilot in many transaction scenarios. For leaders, the need is pressing to embrace disruptive technology despite the risk. In a recent EY survey, 62% of CEOs agreed their organizations must act now on GenAI to avoid giving competitors a strategic advantage. However, the same percentage of CEOs were uncertain about how to proceed.

Four GenAI use cases show ways business leaders might start reimagining their future.

1. Understanding the deal market: M&A professionals can use GenAI to shape the views on market success factors to anticipate and understand potential buy-side and sell-side reactions. An M&A professional focused on industrial manufacturing, for example, can tap vast data inputs, including several layers of public and private information such as market research reports, activist investor sentiment, industry analyst recommendations and deal data, synthesized to make smarter decisions faster.

M&A professionals can also connect complementary objectives in such areas as R&D, innovation, corporate strategy and corporate venture capital to better shape the M&A portfolio strategy.

2. Learning from past transactions: Through analyses of massive data sets containing historical transaction documents and market reports, a health care industry deal specialist might use GenAI to infer valuable insights on why some deals succeed where others fail and generate innovative ideas with latent trends. This can help buyers and sellers justify valuations and take action.

3. Helping with M&A and divestment nuts and bolts: Carving out a business for sale requires standing up new legal entities. For a company with global technology considerations, a deal might require new registrations, new regulations, and often significant global research and paperwork.

Tax experts look at jurisdictions, lawyers talk to other lawyers, and this curation and synthesis of information is time-consuming and costly. GenAI can help with the legwork related to collecting and synthesizing the information needed to create new legal entities. It can draw data from prior work, with public information pulled from various regions. In a similar way, GenAI can help investors negotiate transition service agreements (TSAs) by using precedents to cut time-consuming processes.

4. Anticipating the regulators: GenAI could effectively analyze information on deals terminated by regulatory bodies across sectors, extracting essential metrics on the competitive landscape, price elasticities and market share to provide valuable insights on how regulatory bodies would look upon certain deals.

There are cautionary tales. With so much power to use large data sets to synthesize and infer, GenAI is not without potential security, ethical and legal uncertainty. GenAI can create hallucinations, which may be information connections that exist mathematically in a deep learning model but not in the practical world. This is why adequate guardrails must be in place to temper any GenAI mistakes. Human judgment cannot take a back seat.

What does this mean for your next deal?

If you are considering GenAI in dealmaking, whether you are a serial acquirer or not, here are three things to consider now:

1. Use GenAI internally to strengthen your corporate development strategy. GenAI is a powerful tool to bring together internal documents that use your intellectual property (IP) to help you understand deal success — and failure — tapping a wealth of knowledge from prior transactions that you can apply to future deals.

Documents and lessons learned may be isolated in proprietary spots in-house, requiring an internal exercise to connect this IP. You can build your own GenAI solutions that put knowledge in the hands of practitioners across the transaction lifecycle to accelerate processes and help enhance deal value.

2. Create a strong data strategy. The value of GenAI comes from enriching large language models (LLMs) with accessible IP, such as transaction expertise, that is unique to your business. This will lead to differentiated use cases with growth potential.

A well-structured data framework can optimize GenAI’s ability to generate meaningful insights and innovations from a company’s extensive, disparate intellectual assets while facilitating compliance with data governance and privacy regulations.

3. Adopting GenAI means adapting to change. Those driving a GenAI-powered transaction strategy need to be the practitioners who determine new processes. Technologists might write the code, but artificial intelligence and GenAI have been democratized.

Having an internal GenAI champion can help: a person who can both identify the strategy and roll out use cases, and also ensure that GenAI initiatives are technically sound, strategically aligned, legally compliant, ethical and accretive. This role is central to integrating GenAI into the fabric of a company’s operations in a way that engages all practitioners and supports the overarching objectives and stakeholder commitments.

Keeping GenAI out of transaction planning means a missed opportunity for corporate strategy and M&A professionals. Without the greater insights GenAI could have uncovered, the risk for deal professionals is using scarce capital to make the wrong transaction, missing hidden deal synergies or ending up with stranded costs.

Using GenAI with proprietary transaction data and broader market information could help deal professionals move quickly with a compelling offer while their competitors working without GenAI’s insights are still surveying the landscape.


Learn more about how EY teams can help you develop a GenAI and deal strategy.  


Dr. Khalid A. Khan leads the EY Americas Strategy and Transactions artificial intelligence group, which leverages advanced analytics and quantitative frameworks backed by deep engineering and technical acumen to support the understanding, adoption and implementation of advanced and emerging technologies.


The views reflected in this article are the views of the author and do not necessarily reflect the views of Ernst & Young LLP or other members of the global EY organization.



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