AI in M&A: How can buyers and sellers harness the technology?

Before too long, artificial intelligence (AI) will come to play a central role in M&A on both the buy and sell side - this is inevitable. Currently, the use of AI in M&A is relatively low, as dealmakers grapple with how best to use the technology, as well as how to avoid the potential pitfalls.

A sense of hesitancy and trepidation in the industry is clear. In a recent Bain & Company poll of 300 M&A practitioners, just 16 per cent of respondents reported using generative AI (gen AI) in their dealmaking processes, while a 2023 survey from Datasite found that the majority of dealmakers feel that there should be greater regulation of gen AI.

However, the use of AI in M&A processes is expected to accelerate massively over the next few years, as the technology develops further, issues are ironed out and the state of global regulatory measures becomes clearer.

The potential uses of AI in M&A are huge, from speeding up and automating processes within M&A, such as screening, finding targets and due diligence, to enabling buyers to implement repeatable processes and standardise their approach to acquisitions – potentially helping acquirers to massively scale-up and optimise their acquisition strategies.

On the sell-side, too, the possibilities are numerous, ranging from simpler, functional tools such as AI chatbots to handle enquiries from potential buyers, to the use of machine learning and data analytics to derive deep, actionable insights about the business that can be used to institute changes and increase valuation prior to a sale process being undertaken.

While the wide-scale adoption of AI into M&A processes may rely on greater understanding of the technology, reassurances about potential risks and clearer regulation, it seems like it is only a matter of time before it is an integral part of dealmaking.

How can buyers use AI?
Research has shown that, currently, AI is largely used in the early stages of acquisitions and during the due diligence phase - these being the areas where buyers see the greatest benefits as lying.

Respondents to the Bain & Company survey who have already incorporated GenAI into their acquisition strategies are primarily using the technology to identify targets and undertake document review.

An M&A practitioner quoted in the report said that using GenAI in the screening process enabled their company to identify targets that traditional tools would not typically pick up. Overall, 50 per cent of the dealmakers that were using AI said that it was used to help them source targets, while a further 50 per cent said they used it to screen targets.

By harnessing AI algorithms built around their specific target company criteria, buyers will be able to sift through huge amounts of data to identify potential targets they may otherwise have missed using traditional methods, providing a quicker and far more efficient means of sourcing targets.

Beyond this, there are suggestions that AI could increasingly be used by buyers to predict which targets will bring success when combined with their business post-acquisition, even when looking at intangible factors like company culture.

Alexis Christofides, UK Regional Head for Tata Consultancy Services (TCS) M&A Services, commented: “The days of most deals originating solely from investment bankers mixing and matching buyers, sellers, and acquisition targets will soon be over, and ultimately, AI will provide deeper insights and probabilities of deal success.”

Christofides added: “It’s only a matter of time. Increasingly, companies are discovering ways to codify their capabilities, even for traditionally unquantifiable things like corporate culture. Sooner or later, all that data on ‘e-mail sentiment analysis’ and ‘product time-to-market’ will be thrown into a machine learning algorithm.”

While AI seems to have a potentially huge role to play in target identification and analysis, perhaps the biggest use case will be in due diligence. This was reflected in the fact that Bain & Company found that 58 per cent of current AI users were utilising the technology at the due diligence stage – the most of any step in the M&A process.

It’s no wonder that AI can be so helpful during due diligence, given that the process largely involves trawling over huge amounts of data regarding historical performance, finances, legal issues, patents and trademarks, workforce, customer base, ESG performance and forecasts, to name just a few things.

When performed manually, the process is highly labour intensive and can consume enormous amounts of time and money. And that’s just in scenarios where the vendor is well-prepared to facilitate the process. In some cases, buyers will be sifting through disorganised, sometimes incomplete, piles of data from a range of sources.

Given the time constraints involved in M&A deals (e.g. if the buyer only has a limited window of exclusivity with the seller), delays in due diligence can be costly. Furthermore, even in an effective, well-organised due diligence process, undertaking it manually leaves huge scope for human error and oversights that could severely damage the deal or cause significant issues if uncovered in the post-acquisition period.

As one respondent to the Bain & Company survey explained: “Generative AI is helpful in parsing the mountain of data that needs to be reviewed. If you miss a critical fact, it can be a loss. Generative AI can be trained to parse material contracts and identify deviations from a model contract, saving time and helping to focus on problematic areas.”

AI algorithms can not only eliminate human error and massively speed up due diligence tasks such as document review, they can also be trained to spot patterns, inconsistencies and potential risk factors in data, generating insights that can help buyers all the way through to post-deal integration.

The post-deal period is perhaps the main area of M&A in which the potential use of AI is least explored. Bain & Company found that just 22 per cent of dealmakers were using AI for integration planning, while only 10 per cent of respondents that have incorporated AI into their processes were using it to execute their integration strategies.

As a report from SS&C and Intralinks stated, post-deal integration is an area of the M&A process in which dealmakers should be using AI more than they currently do. As well as being able to generate actionable insights on a company’s performance that could help new owners to make vital decisions and adjustments post-acquisition, AI can also be utilised to streamline the integration process by identifying important milestones and measuring the performance of the company against the buyer’s aims. By analysing data from both the acquiring and acquired entities, AI can identify synergies, optimise operations, and streamline integration processes.

Ultimately, this is one aspect of M&A which may require significant further development in AI before it is consistently used. The Datasite survey found that 42 per cent of dealmakers see improving productivity during the M&A process itself as the main benefit of AI, with few thinking that generating outcomes is a major advantage. As AI algorithms become more developed and widely used, this may begin to shift.

In brief: 10 ways that buyers can leverage AI at every stage of their M&A process

1. Market analysis and trend identification
Generative AI can analyse vast amounts of data to identify current market trends, consumer behaviour, and emerging industries. This insight can help potential buyers focus their search on businesses that are in growth sectors or have untapped potential.

2. Personalised business matching
By inputting specific criteria, such as industry preference, location, size, and budget, generative AI can sift through listings to find businesses that match a buyer's specific needs and preferences. This personalization can significantly speed up the search process.

3. Financial performance forecasting
I can model potential financial forecasts for businesses of interest based on historical data, current trends, and market analysis. This can give buyers a clearer picture of a business's potential return on investment, helping to inform their decision-making process.

4. Valuation assistance
Determining the appropriate value of a business is crucial. Generative AI can assist by analysing comparable sales, financial records, and market data to suggest a fair market value for a business, ensuring buyers make competitive yet sensible offers.

5. Due diligence process
The due diligence phase can be lengthy and complex. Generative AI can expedite this by rapidly analysing legal documents, financial records, and compliance documents to highlight potential issues or concerns.

6. Negotiation simulations
AI can simulate negotiation scenarios based on historical data, providing buyers with insights on negotiation strategies, potential outcomes, and tactics to prepare them for negotiations and help them to secure a more favourable deal.

7. Integration and transition planning
Once a business is acquired, the integration phase begins. Generative AI can assist in planning the integration process, identifying potential synergies, and predicting challenges, helping to ensure a smooth transition.

8. Customised learning and support
For those new to business acquisition, generative AI can offer customised learning resources, tutorials, and case studies based on the specific interests and needs of the buyer, enhancing their understanding of the M&A process.

9. Market sentiment analysis
By analysing news articles, social media, and other public data, AI can provide insights into the public sentiment towards particular industries or businesses, helping to gauge an important element in the potential success of an acquisition that is often considered tricky to quantify.

10. Post-acquisition strategy development
After acquiring a business, generative AI can help devise strategies for growth, identify areas for improvement, and suggest innovations to keep the business competitive.

AI in sell-side M&A
AI is perhaps less used on the sell-side of M&A deals – predictably, given that its main uses currently are in target sourcing and due diligence. However, it has a powerful, and growing, role in helping business owners to sell their companies.

Fundamentally, of course, some of the tools that buyers use to perform due diligence on target companies can also be used by vendors to organise and analyse their own business ahead of a sale, helping them to gain a more accurate valuation of their business and to facilitate a smoother, quicker due diligence process for potential buyers.

Prior to that, however, AI algorithms could also be used by owners considering a sale to analyse external factors such as emerging industry trends, potential regulatory changes and other risks and assess whether they should move ahead with their sale as planned, accelerate the process or delay it until market conditions are more favourable.

As we’ve emphasised elsewhere, of course, an exit process is one that should ideally be undertaken over a period of years, in order to ensure that the business is as prepared as possible to be sold at a maximum valuation and enjoy a seamless transition to a new owner.

As AI becomes more developed, business owners undertaking exit planning could utilise it to derive actionable insights on their company’s performance, which could help them to identify growth potential and areas where the business needs to improve and could form the basis for efforts to scale up the company and improve its valuation prior to a sale.

During the M&A process itself, AI could also help sellers in various logistical ways. For owners actively seeking buyers, AI can assist in generating high-quality marketing materials such as pitch decks, executive summaries, and business plans. These materials can be tailored to highlight the strengths of the business and appeal to potential buyers.

AI tools could also be used to organise relevant documents in virtual data rooms (VDRs) when negotiating with potential buyers. AI can help sellers to categorise, summarise, and present documents effectively, making it easier for potential buyers to analyse the information.

AI can enhance VDRs by offering more structured and accessible data presentations, employing natural language processing to answer questions directly from the data, and ensuring secure data handling during sensitive stages of the deal.

These kinds of tools can also be used to help build smart chatbots to help owners field enquiries from interested parties, providing potential buyers with basic information and key points about the business. This could help to significantly reduce the administrative burden on the business once the sale process begins to gather pace.

AI can also assist sellers in facilitating the post-deal integration phase. This could range from administrative tasks, such as creating detailed transition plans outlining necessary training, transfer of knowledge and information sharing, to more complex insights such as potential growth strategies and risk forecasts.

What are the potential issues?
Perhaps the main barrier to the widespread use of AI in M&A activity are (understandable) concerns among both buyers and sellers about the potential risks associated with the technology, which, we should remember, is still in its relative infancy.

In Bain & Company’s January 2024 study, 59 per cent of respondents cited data inaccuracy at the most concerning risk of using GenAI in their M&A processes, with one respondent quoted in the report stating that, while they expected this area to improve, they currently had to either review or redo work completed by gen AI in order to eliminate potential inaccuracies.

Data security and privacy are perhaps the next biggest concerns that are delaying the integration of AI into M&A processes. In Bain & Company’s survey, 38 per cent cited data privacy risk as the most concerning risk of using GenAI in M&A, while 36 per cent cited cybersecurity risk.

Similarly, in Datasite’s survey, 34 per cent said that data privacy and security were their leading concerns around the technology, while an additional 36 per cent said that this was the main obstacle preventing them incorporating it into their business.

Clearly, the impact of things such as cybersecurity or data breaches and inaccurate data could have catastrophic consequences in M&A deals and Datasite’s survey showed that such concerns are not just preventing dealmakers from using AI, but also having an adverse impact on deals themselves.

According to the poll, 14 per cent of respondents said that they had seen a deal derailed by concerns over GenAI, with the leading issues being security, privacy and compliance, data and data quality, competence and expertise, transparency and explainability and technology validation.

Of course, much of the hesitancy around incorporating GenAI is due to how new it is to many dealmakers. This was reflected in the Datasite survey, with 26 per cent citing a lack of competence/expertise as a barrier to integrating the technology and 20 per cent citing its immaturity.

As the technology develops over coming months and years, it is likely that many of the potential vulnerabilities with regards to data protection, privacy and accuracy may be ironed out and that a greater number of people in the M&A sphere will receive training and become more comfortable and confident with AI.

This should have a major impact on its uptake, but it’s also clear that much uncertainty derives not from the technology itself, but how it is regulated. A current lack of regulation seems to be majorly contributing to an overall feeling of unease about AI among dealmakers – a sense that there is potentially a lack of structure, oversight and standards that could put those who use the technology in a vulnerable position.

This was reflected in 73 per cent of respondents to Datasite’s survey – which polled 500 dealmakers from the UK, France, Germany and the US – saying that governments should regulate AI.

Datasite Chief Executive Officer Rusty Wiley encapsulated the sense of unease that is tainting the undeniable potential AI offers to dealmakers, commenting: “From automating manual, repetitive tasks, such as organising and categorising files in preparation of due diligence, to powering data analysis to increase value and accelerate M&A integration, AI is already reshaping various phases of the dealmaking process.”

“However, there is a healthy awareness of the challenges associated with GenAI, and acknowledgement that establishing systems, processes and regulatory frameworks are critical to effectively harnessing its benefits and mitigating risks.”

Are concerns based around misunderstandings?
As with hesitancy around any new technology, there will be suggestions that this is driven more by unfamiliarity and a lack of understanding than by genuine faults with the technology itself.

While GenAI in M&A is of course only at its very early stages, and uncertainty and hesitancy is perfectly understandable and perhaps understandable, it does seem that there is a disconnect between the concerns of those who have yet to use the technology and the experience of early adopters of AI into their M&A processes.

It is worth pointing out that just 16 per cent of the respondents to Bain & Company’s survey are currently using AI in their M&A processes and that the concerns cited in the study were largely among dealmakers that are yet to incorporate AI in any way.

Those who had adopted the technology already were mostly larger companies in the tech, healthcare and finance sectors undertaking moderate M&A activity of between three to five deals per year.

Of the survey respondents who had incorporated AI into their M&A processes, 85 per cent reported that it had met or exceeded their expectations and 78 per cent said that it had delivered gains in productivity from reduced manual effort. 54 per cent said that AI had accelerated their deal timelines, while 42 per cent said that the technology reduced costs and improved their focus.

These early views seem to undermine some of the concerns expressed by non-users over how AI may shape their dealmaking processes. According to the Datasite survey, just 15 per cent of respondents thought that gen AI would speed up their dealmaking processes, while 52 per cent felt that it would increase their daily workload.

While it may be the case that, in its current form, GenAI requires significant oversight and supervision by staff (and may therefore add to the workload), the general consensus among the majority of dealmakers who use AI is that the technology has had a positive impact upon their M&A processes.

This suggests, to some degree, that some of the concerns that dealmakers have about incorporating AI would be assuaged by using the technology and seeing how it can benefit their M&A strategies.

How will AI transform the role of business brokers in M&A?
It’s not just buyers and sellers that will increasingly use AI to streamline and optimise their dealmaking processes, business brokers also appear set to see their roles in M&A deals transformed.

Naturally, much of any broker’s role involves the more intangible “human” aspects of business: building relationships, developing a network and establishing trust and connections with their customers.

While this human touch remains vital to M&A deals and is not something that can be readily replaced by technology, harnessing AI can enable brokers to invest more time in these vital functions by automating certain processes, whilst simultaneously providing solutions that can help bolster how brokers build and manage their customer relationships.

1. Dealmaking and efficiency
AI technologies can leverage data analytics to streamline the deal-making process. By processing large datasets, AI can identify trends, evaluate business valuations with greater accuracy and help to facilitate more effective buyer-seller matching.

This efficiency not only speeds up transactions but also increases their likelihood of success by ensuring that the most compatible parties are connected. The kinds of insights provided by AI can make brokers more effective in matching buyers and sellers, which could subsequently have a majorly positive impact on the success rate of the deals that they facilitate.

2. Client relationship management
Harnessing AI in client relationship management can transform how brokers interact with their clients. Through advanced analytics and machine learning, AI can tailor communication strategies to fit the unique preferences of each client, deliver a more personalised service and even enable brokers to become more adept at predicting a customer’s needs.

This approach not only enhances client engagement but could also empower brokers to be more proactive and hands-on in the process by offering insights and suggestions on M&A strategy. Personalised service, combined with this elevated level of insight and analysis, will help brokers to impress their clients, provide a more efficient service and, ultimately, build stronger, more trusting customer relationships.

3. Market analysis and forecasting
AI's predictive capabilities are a potential game-changer for market analysis. By sifting through vast amounts of market data and employing sophisticated algorithms, AI can forecast market trends and provide actionable insights.

Brokers equipped with this forward-looking perspective can advise their clients with greater confidence, helping them to navigate market fluctuations and identify and capitalise on upcoming opportunities that competitors may not have yet spotted.

4. Operational efficiency
This is perhaps the area in which AI will have the biggest impact on brokers in the near-medium term. By automating routine tasks such as data entry, report generation, stakeholder & customer support and preliminary market research, AI frees up brokers to focus on the strategic aspects of their role.

Smart AI Assistants

Some brokers have begun to use smart AI assistants (an evolved form of legacy chatbots) to deal with initial enquiries from both prospective buyers and sellers.

Richard White of Business Data told BSR: “We’ve helped create several smart agents for business brokers and corporate finance firms. The two main benefits they bring are (1) making life easier for the visitor in terms of getting specific information quickly just by asking questions in English (or whatever native language they use); and (2) saving considerable time for the broker, who can now utilise an extremely low-cost ‘worker’ to disseminate information."

"The agent answers questions and filters those serious buy-side and sell-side prospects, recording details and alerting the broker to subsequently call, or even arranging a zoom meeting slot on the Google or Microsoft calendar app.”

"We can upload a large amount of the broker’s PDF documentation onto our secure servers that we integrate with AI and smart bots. It’s just incredible how much of a productivity boost this is.”

This shift will not only improve the brokerage's operational efficiency but also allows brokers to devote more time to the more traditional, relationship-driven elements of their role: client interaction, negotiation, and deal structuring—activities that directly contribute to the brokerage's value proposition.

The integration of AI into business brokerage and M&A activities is not just a trend but a transformational shift that could redefine the industry's standards and practices.

As AI technologies continue to evolve, their role in enhancing deal-making efficiency, client relationship management, market analysis, and operational efficiency will only grow, offering unparalleled advantages to those who embrace them.

As with adoption of AI among buyers and sellers, however, perhaps the main barrier to this transformation will be hesitancy among brokers, with many (especially more “old-fashioned” brokers) likely to be sceptical about the role technology can play in what is still widely seen as a particularly human, relationship-centred industry.

Those that choose to ignore the advantages that AI can offer to brokers, however, could lose a competitive edge as the technology becomes more widespread within the industry. As this occurs, a divide could grow between brokers who lean into the opportunities offered by AI and those who don’t.


The integration of AI into all angles of M&A deals is growing daily. While the technology currently appears more suited to certain aspects of the dealmaking process than others, it is still developing rapidly and dealmakers seeking to lean into the opportunities will continue to find ways to incorporate it at various stages.

More than simply automating laborious manual processes and eliminating the scope for human error, AI can provide deep insights into companies, the wider economy and emerging trends that can enable buyers to become more effective at identifying potential targets and integrating new acquisitions.

On the sell-side, meanwhile, the technology can help owners to identify the best time to sell, build exit strategies and plan how they can build value at their company prior to a sale.

While the technology remains in its infancy and is not without significant issues, the rate of development means that it will only become more adept and proficient at facilitating M&A deals. Ultimately, the timeframe for AI becoming an integral part of M&A seems to be a matter, not of years, but of months.

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