The use of ChatGPT in corporate markets may have made headlines about the adoption of artificial intelligence, or AI. However, it's not the first AI tool to find widespread use in business applications. Businesses have been using AI assistants for years, particularly when it comes to large data sets. AI is capable of analyzing large data sets quickly, providing a second set of “eyes” to support due diligence. Read on to discover how AI systems and generative tools such as ChatGPT can help with data analysis, deal due diligence, deal sourcing and other relevant applications.
Why Companies Are Using AI in Mergers and Acquisitions
Let's look at a few of the most common applications for mergers and acquisitions AI to understand how companies are using these tools. It's worth mentioning that AI changes so rapidly that new use cases are discovered as the tools and our understanding of them evolve.
Here are the ways most companies are choosing to use AI, as of this writing:
Deal Sourcing
The deal sourcing process requires significant time searching for M&A targets and analyzing data before making an offer. Compared to human workers, who have only so much capacity to search and review documents from a diverse range of sources, AI is more efficient. AI technology can search for M&A opportunities using defined criteria and return results, helping organizations keep up with fresh data.
Accelerated Deal Timeline
Rushing the M&A process can backfire. Companies who rushed mergers and acquisitions in the hopes of gaining market share have come to regret it. In some cases, bitter feelings from a previous bad experience can prevent them from taking advantage of new opportunities that are a better fit. AI tools help remove workflow bottlenecks while preserving review discipline.
Enhanced M&A Due Diligence
The use of AI in M&A due diligence has taken off in the virtual data room environment. Tasked with reviewing thousands of pages of documents in a compressed time format, experts increasingly turn to AI assistants to support the process.
Artificial intelligence for M&A due diligence is capable of parsing data for key performance indicators with greater speed and accuracy than humans.
AI-equipped M&A due diligence software can scan thousands of pages of documents, from PDF reports to spreadsheets, and provide actionable information very quickly. This speeds up the pace of the deal, bringing benefits to both sides. Some estimates have revealed that companies save anywhere from 30% to 90% of time on the due diligence phase by using AI.
Many M&A deals have an international component these days. Increasingly, parties need to communicate in other languages, review documents in original languages and use translation to ensure communication is understood. AI in due diligence tools like ChatGPT can provide language support when it comes to translating in the international deal environment.
Enhanced M&A Valuation & Deal Structuring
In an income-based M&A valuation approach, an expert typically reviews the business's financial statements to gain an understanding of the company's projected future earnings.
From there, they can work backward to calculate the value of the M&A target in the present day. AI can review the statements and provide a preliminary analysis for the expert to unpack in detail. AI can also use the valuation to determine benchmarks that can guide the process forward.
Regulatory Compliance
In an M&A, both sides have to adhere to laws and regulations. While each party will have their own legal counsel who can advise on how to comply with laws, AI plays a role here, too. Legal counsel may use AI to review contracts and other legal documents, checking for issues that must be addressed during disclosure and deal execution. Using AI can help you find and fix errors, avoiding the need for a last-minute fix.
Avoiding Unsuccessful Acquisitions
Sometimes deals fall apart. This can happen when a problem develops after the initial agreement that causes one or both sides to walk away from the planned M&A. It can also happen if a deal exceeds the timeline. Fortunately, AI can help companies avoid many unsuccessful acquisitions.
Within the due diligence phase, AI in M&A(s) can review documents looking for red flags. For example, inconsistencies within the documents or less-than-stellar reports from marketing, sales, human resources and other departments could be a warning of insurmountable issues if the deal proceeds. The company may seek to adjust the valuation based on information discovered in the AI due diligence phase, or it can decide to abandon the deal outright.
During the post-merger integration phase, players typically seek to realize operational advantages while decreasing redundancies. AI can review processes and internal structures with the aim of identifying areas to consolidate or streamline.
When it comes to roles and responsibilities, AI can also streamline workflows. For AI tools like ChatGPT M&A, post-integration tasks can focus on the best way to automate certain workflows. AI can enhance workflows by taking over some of the tasks previously performed by humans. This in turn allows human workers to perform the more complex and subjective tasks where it would not make sense to run an AI tool.
AI can also monitor the integration process in real-time, providing an overhead view of complex processes. This in turn supports better decision-making, because information can be acted upon faster.
AI Governance and Data Security in M&A
Although the technology continues to dominate headlines, not all enterprises have been as quick to adopt AI as others. According to a recent Deloitte survey on generative AI, the two biggest barriers to adoption among organizations are data security and availability. However, these are far from the only concerns companies have about AI. Other significant risks that come with using AI include:
- Confidential data exposure
- Hallucinated or inaccurate outputs
- Biased acquisition target screening
- Incomplete summaries
- Lack of auditability
- Overreliance on automation
- Use of unapproved public AI tools
Rather than embracing the technology with blind faith, organizations must take a measured and careful approach with an emphasis on governance. With regard to how the technology is used for M&A deals, there are some established best practices that companies should follow, including:
- Determining which AI tools should be approved
- Restricting confidential deal data from unauthorized tools
- Requiring human review of all AI outputs
- Involving legal, compliance, and IT security teams in any AI implementation process
- Using only permissioned platforms for diligence materials
- Maintaining strict audit trails and version control
The governance protocols used should be tailored to the workflow. For example, public market screening is lower-risk, while confidential diligence review is higher-risk and therefore needs stricter controls.
AI Can Accelerate M&A Deals, But Governance Determines Value
There’s no doubt that AI has become a practical tool across the M&A deal lifecycle, from deal sourcing and diligence to valuation support and integration planning. AI delivers the greatest value when it is used to accelerate analysis, surface risks, and improve workflow efficiency. However, it should not be used as a substitute for experienced, expert judgment from deal teams, legal counsel, corporate finance leaders, or advisors. Instead, AI adoption needs to be paired with governance, data security, document control, and clear review processes.
DFIN's M&A software leverages AI capabilities to support due diligence, company valuation, post-merger integration and all aspects of the dealmaking process. Not only does DFIN provide the products companies rely on for complex corporate M&A transactions, we also keep up with the latest changes to help clients stay abreast of new regulations, compliance issues and technologies. Discover why global players choose DFIN as their AI in M&A(s) technology partner.
