Perspectives

AI in M&A: Where art and science meet

The evolving role of Generative AI

There’s plenty of hard arithmetic in M&A, but it’s not all about numbers. There’s art alongside the science, and parts of the life cycle depend more on heuristic judgment than on quantifiable metrics. Learn why there is a role for Generative AI in M&A, but it may not always be a starring one.

Where AI in M&A needs human help

Organizations should embrace Generative AI as an ally in the M&A life cycle. The challenge in doing so is not to automate as much as possible, but to blend the precision of data-driven insights with the intuitive judgment it takes to navigate the intricacies of M&A and valuation.

Finding GenAI’s place in the art and science of M&A

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Strategic alignment

Identifying a target that fits with an acquiring company’s long-term goals is crucial. What are the target’s market position, competitive advantages, and potential synergies? Do acquisition goals envision market expansion, diversification, or new technologies or capabilities?

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Cultural fit

For integration success, the two companies’ cultures must align. Differences in management styles and expectations can breed conflict and dilute synergies.

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Due diligence

Financial analysis is critical—but so are potential risks and liabilities. It takes an eye for legal, operational, and strategic detail to perceive what hasn’t happened yet.

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Valuation method

Machines can add up the elements, but first people need to define the purpose of the valuation and judge which method captures the asset’s value on those terms given market conditions and industry trends.

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Valuation assumptions

Gauging future cash flows, growth rates, discount rates, and other variables requires a blend of analytical skills and informed judgment. Historical performance, market trends, and economic conditions all factor in.

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Perception and sentiment

Understanding how the market views an asset’s growth and risk potential requires a deep understanding of market dynamics and the ability to interpret qualitative information.

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Where AI fits into the arrangement

M&A and valuation have evolved from manual analysis to data-driven, tech-supported processes. “Traditional AI,”, like machine learning, already automates risk assessment and sentiment analysis. Generative AI in M&A is set to deepen these capabilities, but technology still has its place. You may look up a pancake recipe on a tablet, but you don’t use the tablet to flip the pancakes. The role of art is persistent—and invaluable. Here is a look at places in the life cycle where Generative AI can further enhance processes:

Key controls and procedures for AI in M&A

Keeping AI within guardrails is a business responsibility. Some of the key controls and procedures we should enable to oversee this process include:

Governance and oversight: A dedicated group should ensure AI operates within ethical and regulatory boundaries, verifying outcomes, maintaining documentation, and setting stakeholder-focused guidelines.

Human oversight: Humans should validate AI results, with all conclusions traceable to original data sources. Regular, comprehensive review is critical.

Data integrity: The data used by Generative AI must be kept accurate and up to date.

Training: Staff should receive training in using AI tools effectively, especially Generative AI, and understand the role of human oversight.

A collaboration that’s greater than the sum of its parts

Technology, process, and people are the cornerstones of effective M&A. Machines enhance our capabilities, but they never make human’s expendable;  – rather, they complement us, amplifying our M&A efficiency and value. The seamless integration of technology, processes, and human perception and experience has the potential to unlock new frontiers of value and efficiency in M&A. Generative AI in M&A is ready to significantly enhance the efficiency and effectiveness of M&A processes, from formulating strategies to monitoring post-merger

 

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