By now, the “testing the waters” phase of adding GenAI to M&A workflows is coming to a close. A recent Deloitte survey on GenAI in M&A of 1,000 corporate and private equity business leaders found that 86% of organizations have already begun to integrate GenAI into dealmaking.
While GenAI applications have typically focused on pre-signing activities such as strategy and market assessment, supporting tasks such as wargaming, market sensing, and target screening, as organizations continue to invest in GenAI, its influence is poised to extend across the entire M&A life cycle, reshaping how deals are evaluated and executed and ultimately how value is realized. According to respondents from the Deloitte survey, when asked to look ahead over the next 24 months, 83% of organizations expect GenAI to have a moderate or significant impact on M&A decision-making, with optimism high for its ability to enhance strategy, execution, and value realization across the deal life cycle.
As organizations become more familiar with GenAI in M&A, the challenge is no longer experimentation—it’s execution. The focus now is on treating GenAI not as a pilot, but as a priority investment capable of delivering ROI. That shift requires more than scaling what’s already been tested. It means identifying the use cases where GenAI can create the most value and implementing them in ways that align with—and ideally advance—the organization’s broader strategic goals. It also requires preparing talent, establishing governance, and determining where and how GenAI can be deployed most effectively.
What strategies and tactics are leaders pursuing to make that happen? Our experience suggests four major avenues that can position a company for effective and sustainable growth as AI adoption accelerates.
Choose your path: Build or buy?
Deloitte research finds the most reported pathway (32%) to deploying GenAI is for companies to develop their own comprehensive, in-house GenAI platforms specialized for M&A tasks like diligence and valuation. The next most common approach (25%) is to work with established third parties to fit existing GenAI tools into the M&A mold.
Those sound like neatly opposite approaches, but as with anything else in M&A, the details matter. It is also noteworthy that finding and using GenAI solutions suited for M&A tasks straight off the shelf represented only 12% of the organizations in the survey.
Among organizations that expect GenAI to have a significant impact on their M&A decision-making, 40% are looking at taking a “build” approach (i.e., developing proprietary, organization-wide platforms with specialized M&A capabilities). These companies seek not only technological power, but the competitive differentiation that can come from bespoke, enterprise-wide platforms. These specialized M&A capabilities match up with established deal processes for a result that competitors can’t duplicate.
For those that prefer buying GenAI tools to building them, the path may appear shorter, but it can still be complex. Off-the-shelf assets may not be created with specific M&A functions in mind, and it is important to align them with their intended purpose in addition to gauging their raw computing power.
Sometimes, dealmaking organizations add the power of the technology by developing it within their own structures or in their portfolio companies. Another avenue is for acquirers to seek out GenAI capabilities that already exist within potential acquisitions, and to make those strengths a factor in targeting and valuation. While the paths vary, the emphasis on careful decision-making and organizational readiness is a constant.
Establish governance early
There is no question GenAI will change the landscape of M&A, but how this happens is critical. The answer lies in cadence: If technology develops ahead of governance, critical elements such as defining decision rights, accountability, risk thresholds, and oversight can remain unresolved.
Without keeping technological innovation and governance in lock step, an organization is exposed to an array of risks including data security, data quality, model unreliability, ethical concerns, and compliance, all of which were cited by more than 60% of surveyed organizations. Risks such as these can arise from the use of individual tools, but also from the spaces in between them—the gaps where security and compatibility are paramount. Whether or not an organization opts to use third-party tools, it may be advisable to seek third-party advice as well.
In addition to risk, insufficient oversight can also dull GenAI’s effectiveness and blunt the advantages in speed, accuracy, and insight that made it attractive to begin with. So, alongside the M&A lifecycle, consider the GenAI lifecycle—and invest in the work of governance from the outset.
Identify and invest in human powered AI to transform opportunities into progress
The experience and skills that surround GenAI are as essential as the technology itself to a program’s overall effectiveness. That applies to the transformations that build GenAI capabilities into an existing portfolio company. But it is also vital as part of the diligence that goes into identifying acquisition targets when their expected value relies on existing GenAI frameworks.
Some of the critical skills are purely technology-based, such as the ability to evaluate and test source code and data. Other skill areas are less technical but equally important, such as the ability to gauge technology’s impact on business value, an eye for hired or acquired GenAI talent, and a new lens on diligence.
More than half (54%) of organizations from the Deloitte survey cited that a lack of the necessary internal talent was an impediment to the GenAI deployments they wished for. About as many (57%) said training existing teams in new GenAI skills was a priority, and 41% reported an emphasis on recruiting specialized GenAI talent from outside the organization.
Prioritize use cases that focus on solving real business problems
Raw technology is measured in speed and capacity. Enterprise technology is measured in business outcomes. The experimental and pilot phases of GenAI development addressed the first criterion to make sure the tools performed as advertised, but now it’s time to deploy with the second criterion in mind to make sure that tools deliver value in line with an organization’s strategic objectives. What is the impact on customer value? What does technology make feasible that wasn’t before? How does it reshape investment needs and returns?
Alignment of GenAI with business objectives can begin with integration into existing M&A workflows. But if the evolution ends there, the transformative power of GenAI may not fully emerge. As confidence grows, organizations should use GenAI not only to speed what they already do, but to imagine what they could do next.
Because this pursuit lies at the intersection of technology possibilities and business practices, it is advisable to make identifying and evaluating GenAI applications the work of a cross-functional team.
High expectations in a unique arena
To make GenAI transformation effective, it cannot be about the technology alone. Surround it with clearly understood guidelines, build organizational and human strengths to support digital capabilities, and harness the power of technology where it will have the most impact on the bottom line.
To learn more about how to unlock what’s possible in your tech-enabled M&A journey, visit our M&A Technology Solutions site.
