M&A Report

Generative AI in M&A: You’re Not Behind—Yet

How early adopters are getting faster and better at dealmaking.

By Jeff Haxer, Maja Omanovic, Ben Siegal, and Brooke Houston

First published on fevereiro 04, 2025
min read


Executive Summary The performance gap between active acquirers and less frequent acquirers will widen as a result of generative AI usage and capabilities. About one in five surveyed companies currently uses generative AI in M&A processes, and more than half expect to integrate it into their dealmaking by 2027. Early adopters tell us that extending usage of generative AI tools across more M&A processes multiplies the benefits. Late followers will be outbid for good deals and find themselves staying too long in processes for bad deals. Este artigo faz parte do Relatório de Fusões e Aquisições de 2023 da Bain. Acesse o relatório Generative AI is here to stay. The potential is nearly limitless, and its impact on M&A will be profound. We expect that companies that master the use of generative AI in M&A over the next five years will identify targets faster than their competitors, underwrite more deal value with confidence, execute diligence and integration activities more rapidly with fewer resources, and ultimately deliver higher M&A-assisted total shareholder returns (TSRs) (see Figure 1). Figure 1 M&A practitioners see potential benefits from generative AI tools at various stages of the deal-making process Source: Bain M&A Practitioners 2025 Outlook Survey (n=307) The good news is that if you’re not yet using generative AI in your M&A process, you’re not alone. We surveyed more than 300 M&A practitioners and found that 21% of respondents currently are using generative AI for M&A. It was 16% in 2023. Frankly, we expected higher growth. But digging into the numbers to determine which companies exactly are using generative AI and for what purposes, we see how those M&A practitioners investing in the emerging technology have positioned themselves to leap ahead of the competition. First, consider that 36% of the most active acquirers are using generative AI for M&A. This is important because our decades-long study of M&A performance shows that companies that do one or more deals per year consistently outperform their less active counterparts in TSRs. It means that they are honing their processes to get better and better at dealmaking. Companies that do infrequent M&A and that are not actively investing to build generative AI into their M&A processes should expect to see that TSR gap widen. Second, private equity is an avid early adopter of generative AI technology across industries, with more than 60% of interviewed private equity firms using at least one tool to improve sourcing, screening, or diligence. That means if private equity is active in your sector, and you are not investing in generative AI, then you can expect even stiffer competition. Related Infographic Ten Takeaways from Our M&A Executive Survey We asked over 300 practitioners across the globe about their dealmaking efforts in today’s market. Here’s what they said. In addition to relying on generative AI–enabled tools to accelerate sourcing, screening, and diligence, early adopters have started to dip their toes into the technology for integration and divestiture planning as well as program management. The most active users have plans to systematically expand generative AI tools’ reach across their entire M&A processes. Within the next 12 months, we expect early adopters will use generative AI tools to draft integration workplans and transition service agreements (TSAs) in less than 20% of the time that they previously spent on such activities, allowing them to mobilize working teams faster with better initial information. The wave after that will involve using generative AI tools to access specific company data to help size realistic cost and revenue synergies and to craft value creation plans based on the prior performance of their acquisitions. Within the next five years, we expect every single step of the M&A process will be enabled by generative AI. As more companies take advantage of such improvements in their M&A capabilities, they set a higher bar for competitors. Late followers in adopting generative AI for M&A are going to face an uphill battle in three areas—namely, making the best-informed bids and knowing when to walk away from a deal, identifying new ways to underwrite and quickly realize value, and protecting people and the business during M&A. Making the best-informed bids and knowing when to walk away from a deal. For example, early adopters relying on generative AI for deeper diligence will spend only about one day summarizing the data, instead of one week, so they will have more time to analyze how to extract maximum value from the deal. Faster summarizing helps companies identify and underwrite more concrete opportunities for good deals while quickly determining the bad deals they can avoid. Identifying new ways to underwrite and quickly realize value. Companies relying on generative AI will be able to identify more detailed cost and revenue synergy opportunities as well as vastly improve their ability to write the draft plan to achieve them. Consider the possibilities in cross-selling potential. By feeding a tailored generative AI tool information such as sales, pricing, and customer relationship management data, as well as catalog information, a company can quickly identify, prioritize, and suggest actions to achieve specific cross-selling targets. This will allow it to underwrite higher synergies in a transaction if that is needed and capture more value more quickly post-close. Protecting people and the business during M&A. Deals can be hard on employees as line leaders across the business must juggle time on M&A projects with their day jobs, risking distraction to the business. Nearly 80% of companies using generative AI in their M&A processes said that they benefit from reduced manual efforts. This means employees spend less time on the M&A program and can more easily juggle demands from the base business. Easing the load on employees can improve performance and retention. Nearly 80% of companies using generative AI in their M&A processes said that they benefit from reduced manual efforts. Facing the prospects of losing out on good deals, falling behind in synergies, and failing to unburden employees, more companies are planning to use generative AI, with more than half of all companies expected to deploy the technology for M&A by 2027. Here's what they can learn from the early adopters. Start now. New technology requires testing and learning to build expertise, identify high-value use cases, and change user behavior. All that takes time. Companies won't be able to catch up to the earlier adopters by simply buying a generative AI–enabled solution in the future; it will slow the learning curve. While becoming fluent in generative AI will take time, companies can begin reducing the time required for manual processes within the first week of adopting the technology. Build an AI portfolio. A basic version of a generative AI tool can be as simple as a well-engineered prompt that references high-quality data sources. If nothing else, companies can start with this initial giant step: They can get an enterprise license and start using it. Then, they can buy or build more advanced solutions in which they find value. Innovate with intent. The best companies will quickly look beyond simple automation tasks. They’ll rethink their end-to-end M&A processes with generative AI capabilities in mind. They’ll prioritize the opportunities to transform M&A capabilities, protecting and growing areas of competitive advantage. Evolve the M&A team. Generative AI will increasingly pick up the time-consuming project management tasks. That raises the question of what skills a company will need to evolve its M&A capability. Great deals are executed by practitioners who focus more on strategic value creation than on the project management tasks. So, using generative AI to outpace competitors in M&A requires companies to rethink their talent strategy, with a focus on creating sustained value in the future. The promising technology will have a significant impact on the entire M&A process. If you have not invested yet, don’t worry; you aren’t behind. But you will need to begin your journey quickly toward becoming fluent in the technology. Otherwise, you’ll find it difficult to complete the deals that truly move the needle. Read the Next Chapter Where the Deals Are: 2024’s Top M&A Markets Este artigo faz parte do Relatório de Fusões e Aquisições de 2023 da Bain. Acesse o relatório Overview Looking Ahead to 2025: Preparing for What Comes Next Looking Back at M&A in 2024: Dealmakers Adapt as the Market Idles Generative AI in M&A: You’re Not Behind—Yet Where the Deals Are: 2024’s Top M&A Markets Ten Takeaways from Our M&A Executive Survey Industry Views Aerospace & Defense M&A Automotive & Mobility M&A Building Products & Technology M&A Consumer Products M&A Energy & Natural Resources M&A Financial Services M&A Healthcare & Life Sciences M&A Machinery & Equipment M&A Media & Entertainment M&A Retail M&A Technology M&A Telecommunications M&A

Executive Summary

The performance gap between active acquirers and less frequent acquirers will widen as a result of generative AI usage and capabilities.
About one in five surveyed companies currently uses generative AI in M&A processes, and more than half expect to integrate it into their dealmaking by 2027.
Early adopters tell us that extending usage of generative AI tools across more M&A processes multiplies the benefits.
Late followers will be outbid for good deals and find themselves staying too long in processes for bad deals.

Generative AI is here to stay. The potential is nearly limitless, and its impact on M&A will be profound. We expect that companies that master the use of generative AI in M&A over the next five years will identify targets faster than their competitors, underwrite more deal value with confidence, execute diligence and integration activities more rapidly with fewer resources, and ultimately deliver higher M&A-assisted total shareholder returns (TSRs) (see Figure 1).

M&A practitioners see potential benefits from generative AI tools at various stages of the deal-making process

The good news is that if you’re not yet using generative AI in your M&A process, you’re not alone. We surveyed more than 300 M&A practitioners and found that 21% of respondents currently are using generative AI for M&A. It was 16% in 2023. Frankly, we expected higher growth.

But digging into the numbers to determine which companies exactly are using generative AI and for what purposes, we see how those M&A practitioners investing in the emerging technology have positioned themselves to leap ahead of the competition.

First, consider that 36% of the most active acquirers are using generative AI for M&A. This is important because our decades-long study of M&A performance shows that companies that do one or more deals per year consistently outperform their less active counterparts in TSRs. It means that they are honing their processes to get better and better at dealmaking. Companies that do infrequent M&A and that are not actively investing to build generative AI into their M&A processes should expect to see that TSR gap widen.

Second, private equity is an avid early adopter of generative AI technology across industries, with more than 60% of interviewed private equity firms using at least one tool to improve sourcing, screening, or diligence. That means if private equity is active in your sector, and you are not investing in generative AI, then you can expect even stiffer competition.

Related Infographic

Ten Takeaways from Our M&A Executive Survey

We asked over 300 practitioners across the globe about their dealmaking efforts in today’s market. Here’s what they said.

In addition to relying on generative AI–enabled tools to accelerate sourcing, screening, and diligence, early adopters have started to dip their toes into the technology for integration and divestiture planning as well as program management. The most active users have plans to systematically expand generative AI tools’ reach across their entire M&A processes.

Within the next 12 months, we expect early adopters will use generative AI tools to draft integration workplans and transition service agreements (TSAs) in less than 20% of the time that they previously spent on such activities, allowing them to mobilize working teams faster with better initial information. The wave after that will involve using generative AI tools to access specific company data to help size realistic cost and revenue synergies and to craft value creation plans based on the prior performance of their acquisitions. Within the next five years, we expect every single step of the M&A process will be enabled by generative AI.

As more companies take advantage of such improvements in their M&A capabilities, they set a higher bar for competitors. Late followers in adopting generative AI for M&A are going to face an uphill battle in three areas—namely, making the best-informed bids and knowing when to walk away from a deal, identifying new ways to underwrite and quickly realize value, and protecting people and the business during M&A.

Making the best-informed bids and knowing when to walk away from a deal. For example, early adopters relying on generative AI for deeper diligence will spend only about one day summarizing the data, instead of one week, so they will have more time to analyze how to extract maximum value from the deal. Faster summarizing helps companies identify and underwrite more concrete opportunities for good deals while quickly determining the bad deals they can avoid.

Identifying new ways to underwrite and quickly realize value. Companies relying on generative AI will be able to identify more detailed cost and revenue synergy opportunities as well as vastly improve their ability to write the draft plan to achieve them. Consider the possibilities in cross-selling potential. By feeding a tailored generative AI tool information such as sales, pricing, and customer relationship management data, as well as catalog information, a company can quickly identify, prioritize, and suggest actions to achieve specific cross-selling targets. This will allow it to underwrite higher synergies in a transaction if that is needed and capture more value more quickly post-close.

Protecting people and the business during M&A. Deals can be hard on employees as line leaders across the business must juggle time on M&A projects with their day jobs, risking distraction to the business. Nearly 80% of companies using generative AI in their M&A processes said that they benefit from reduced manual efforts. This means employees spend less time on the M&A program and can more easily juggle demands from the base business. Easing the load on employees can improve performance and retention.

Nearly 80% of companies using generative AI in their M&A processes said that they benefit from reduced manual efforts.

Facing the prospects of losing out on good deals, falling behind in synergies, and failing to unburden employees, more companies are planning to use generative AI, with more than half of all companies expected to deploy the technology for M&A by 2027.

Here's what they can learn from the early adopters.

Start now. New technology requires testing and learning to build expertise, identify high-value use cases, and change user behavior. All that takes time. Companies won't be able to catch up to the earlier adopters by simply buying a generative AI–enabled solution in the future; it will slow the learning curve. While becoming fluent in generative AI will take time, companies can begin reducing the time required for manual processes within the first week of adopting the technology.

Build an AI portfolio. A basic version of a generative AI tool can be as simple as a well-engineered prompt that references high-quality data sources. If nothing else, companies can start with this initial giant step: They can get an enterprise license and start using it. Then, they can buy or build more advanced solutions in which they find value.

Innovate with intent. The best companies will quickly look beyond simple automation tasks. They’ll rethink their end-to-end M&A processes with generative AI capabilities in mind. They’ll prioritize the opportunities to transform M&A capabilities, protecting and growing areas of competitive advantage.

Evolve the M&A team. Generative AI will increasingly pick up the time-consuming project management tasks. That raises the question of what skills a company will need to evolve its M&A capability. Great deals are executed by practitioners who focus more on strategic value creation than on the project management tasks. So, using generative AI to outpace competitors in M&A requires companies to rethink their talent strategy, with a focus on creating sustained value in the future.

The promising technology will have a significant impact on the entire M&A process. If you have not invested yet, don’t worry; you aren’t behind. But you will need to begin your journey quickly toward becoming fluent in the technology. Otherwise, you’ll find it difficult to complete the deals that truly move the needle.

Read the Next Chapter

Where the Deals Are: 2024’s Top M&A Markets