2025 M&A Generative AI Study
GenAI makes inroads in M&A, but challenges remain
Generative artificial intelligence (GenAI) has become an established technology, but what contributions is it making in mergers and acquisitions (M&A)? According to a new survey, organizations are adopting GenAI at a rapid pace, with the potential to fundamentally transform the M&A process. However, the speed of adoption differs across various stages of the M&A life cycle and sometimes varies between corporate and private equity (PE) participants. Despite GenAI’s growing popularity, many users remain cautious, citing a range of risks that may be limiting broader or deeper implementation.
The findings, contained in Deloitte’s 2025 M&A Generative AI Study, represent the views and observations of 1,000 senior corporate and PE leaders from across major industries, surveyed in the first half of 2025. According to that survey, 86% of responding organizations have integrated GenAI into their M&A workflows, and 65% of them did so within the past year.
What M&A organizations want from GenAI varies, with many seeking process improvements and accelerated insights to build a competitive edge in today’s fast-paced M&A environment. While some organizations have created their own well-defined strategies to drive internal development efforts, respondents have overwhelmingly partnered outside of their organization to drive rapid deployment of AI-enabled M&A capabilities. Additionally, across all surveyed organizations, concerns about data security, accuracy, ethics, and compliance remain critical risks and are likely to influence where organizations build capability in the M&A life cycle and the value they receive from those investments.
We also see parallels from the findings of this study and our observations from our earlier article, “Artificial intelligence and mergers and acquisitions: Observations from the frontlines and how to prepare for the coming shift.” Consistent with our earlier view, we observe that while enthusiasm for GenAI is high and early adopters are already realizing tangible efficiencies, particularly in diligence, market assessment, and deal execution, organizations are proceeding thoughtfully, balancing innovation with caution. Many leaders are prioritizing robust governance and risk management frameworks, and we see a clear trend toward piloting GenAI in targeted M&A use cases before scaling more broadly. The most successful adopters have been those who integrate GenAI into existing workflows while keeping a close eye on data quality, security, and regulatory compliance.
Overall, 86% of organizations report they have incorporated GenAI into aspects of their M&A workflows or daily activities. Of that 86%, whom we will call “adopters,” nearly three-quarters have made these inroads into GenAI within the past year. Notably, approximately 40% of organizations say they use GenAI in more than half of their deals. That recent, rapid integration shows greater awareness of GenAI and its potential to transform the M&A process.
These GenAI investments are not only rapid, they also represent meaningful commitments within the M&A function itself. Among adopters, 83% have invested $1 million or more in the technology, specifically for their M&A teams. That includes 88% of private equity firms and 77% of corporate organizations. In addition, most indicate they are not finished: Many anticipate increasing their GenAI investments over the coming 12 months, either slightly (54% of private equity, 58% of corporate), or significantly (24% of private equity, 28% of corporate).
The study found that GenAI is being used at every stage along the M&A life cycle, though adoption is weighted more heavily toward the early part of the life cycle: 40% of adopters are applying it to M&A strategy and market assessment, while 35% use it for target screening and due diligence. In contrast, the later stages, including valuation, deal execution, and post-deal integration and value realization, each saw 32% of adopters applying GenAI tools to those areas.
Despite the demonstrably rapid pace of investment and implementation of GenAI in M&A, there are still concerns that may be holding organizations back from moving even faster. Many of the risk categories familiar with AI users across business were also on the minds of survey respondents in this sector. For GenAI to achieve its full potential in enhancing M&A, it will be crucial to address these challenges.
The primary barrier is data security, cited by 67% of respondents. Closely following is concerns about data quality (65%). Model reliability, a prominent concern in AI, was identified by 64% of respondents. Additionally, many respondents pointed to ethical considerations (62%) and uncertainty about regulations and compliance (61%) as factors that could hinder broader adoption of GenAI.
Bringing GenAI into an M&A workflow is more than simply adopting new tools; it also requires preparing people to use them effectively. When they work as intended, GenAI can drive shifts in organizational culture and transform established ways of working.
Among private equity firms, 31% of adopters are developing organization-wide, cross-department GenAI platforms that include specialized M&A capabilities. That approach was slightly more prevalent (33%) among corporate entities. Other organizations are partnering with established technology providers to customize GenAI tools for M&A use cases, including 26% of private equity and 24% of corporate entities.
Private equity adopters show a greater tendency (14%) than corporate ones (11%) to license ready-made solutions from trusted vendors.
What is the ultimate role GenAI will play in the M&A process once the initial phase of adoption and implementation is complete? Most adopter organizations say they anticipate it will have a moderate (48%) or significant (35%) impact on M&A decision-making. Only 4% think it will have no impact at all.
Where will GenAI likely deliver the greatest benefits for M&A? When asked to look ahead over the next 24 months, 37% of organizations identified strategy and market assessment as the area most likely to see “very high” benefits. Optimism was nearly as strong in other areas: 35% anticipate “very high” benefits for enhanced overall M&A capabilities, while 34% expressed the same expectation for post-deal integration and value realization, due diligence, and target identification and screening.
Turning insights into action
Translating these insights into real-world impact remains a top priority for organizations. Deloitte has previously outlined four strategic decisions that organizations can take to strengthen their AI capabilities. As the AI race in M&A accelerates, our latest survey findings and marketplace experience confirm that these four actions are more foundational and relevant than ever. The only notable evolution is a refinement to the fourth action: as GenAI technology evolves, organizations now focus on piloting and adopting high-priority use cases, moving beyond initial experimentation to drive measurable impact.
- Stand up or strengthen sensing capabilities using internal and external resources to keep a pulse on AI and GenAI activity, considering direct and indirect competitors and partners.
- Recast the M&A strategy by taking into consideration how AI and GenAI might affect existing value chains and opportunities to capitalize on disruption and drive greater growth and value creation throughout the portfolio.
- Identify and invest in expertise that can help validate and amplify AI and GenAI opportunities and that brings a blend of commercial, operational, and technical perspective.
- Pilot and adopt high-priority GenAI use cases to accelerate value realization, focusing on those with the greatest potential impact across the enterprise and ensuring alignment with overall organizational objectives.
Taken together, these actions provide a practical framework for organizations seeking to navigate the complexities of GenAI adoption in M&A. By continuously refining their approach grounded in robust sensing, strategic alignment, expert engagement, and targeted use-case deployment, organizations not only can keep pace with rapid technological change but also can position themselves to create meaningful value from their M&A-related AI investments.
