AI, and generative AI (genAI) in particular, has great potential to transform the mergers and acquisitions landscape. As the demands and challenges of dealmaking grow, genAI offers new tools and approaches to help address them.

Dealmakers have the opportunity to harness the power of AI and genAI in three distinct ways: how deals are getting done by optimizing M&A processes across the entire lifecycle, improving speed, quality of insights, and financial outcomes during execution; which deals to pursue with an increasing focusing on the acquisition of AI – and genAI – capabilities, assets, and data, and the divestiture of business models vulnerable to AI disruption; and how you create value and realize potential synergies to post deal cost structures that could be obtained via genAI.

Digitally transforming the M&A lifecycle

According to Deloitte’s “State of Generative AI in the Enterprise" study, nearly every surveyed company is already using genAI in some form. Digital transformation is also top of mind with dealmakers. Findings from Deloitte’s “2025 M&A Trends Survey” show nearly all corporate and PE executive respondents report having digitally enabled “completely” or “almost completely” all stages of the M&A lifecycle.

While much of the focus to date has been application of genAI earlier in the deal lifecycle, this is likely driven by companies starting to apply it where they are most comfortable and feel the least risk versus where it may end up driving the most value.

The trends survey also shows usage in areas like target identification and target screening having risen substantially in terms of digitizing deal processes. Ways AI and genAI are being applied to these areas include product portfolio analysis and assessing product mix and recommended growth strategies; identifying and prioritizing high-performing assets for future deals to correlate with investment strategy; and market sensing and analytics.

Medium and longer term, the potential to have an impact on getting to deeper insights more quickly in diligence and streamline some of the time consuming and data heavy processes in integrations will likely become a focus as noted below in the discussion of potential to leverage genAI to identify and execute on synergies.

Buying AI and genAI capabilities

According to the latest “PitchBook-NVCA Venture Monitor,” nearly 58 percent of global venture capital (VC) dollars invested during the first quarter of this year went to AI and machine learning (ML) startups. The capital is even more concentrated in North America, with just over 70 percent of VC deal value going into AI and ML startups. VC investment flows can be viewed as a potential precursor to future M&A activity as the development of new technologies will often spur deal activity.

Buyers are using AI to not only drive efficiency but fuel innovation and growth. Deloitte’s “2025 MarginPLUS” study shows companies are pursuing growth by using genAI to serve customers more effectively – not just more efficiently – and to deliver a high-quality customer experience. They are also using genAI to enable innovative, new products, services, and business models that can boost their revenues and help them expand into new markets. Particularly within the technology, media and telecommunications sector, genAI is notably being leveraged to drive innovation, opening pathways for entirely new business models and revenue opportunities.

Accelerating value and synergy realization in post-deal environments

Another way genAI stands to play a transformative role in M&A is with post-deal integration, especially in optimizing cost structures and realizing synergies.

With its ability to analyze large volumes of structured and unstructured data (contracts, organizational charts, spend data, communications), genAI can be leveraged to uncover hidden synergies, such as overlapping vendor contracts, duplicative roles, or cross-selling opportunities. It can also continuously track synergy realization against targets.

Post-merger, organizations typically look to streamline processes (procurement, finance, IT) to remove inefficiencies. GenAI-powered process mining and automation tools can map current workflows, suggest process redesigns, and even generate automation scripts to accelerate integration and cost reduction.

For companies hoping to take advantage of what AI and genAI have to offer, and looking to increase their capabilities, there are some specific opportunities and challenges they should consider, including:

• Do you have the right talent to support your AI strategy? Identifying internal talent or accessing external expertise, or both, to assess AI and genAI targets will be critical to evaluating the quality of the underlying technology and impact to existing assets. Such resources may also be valuable in examining sources of new potential threats that may arise from genAI disruption.
• Is your data ready to match the pace of AI? Data readiness is critical for harnessing the potential of AI applications. Yet, data quality and availability continue to be the biggest constraint to successful AI implementations as many companies wrestle with inflexible legacy systems and technology infrastructures that are incapable of feeding notoriously data-hungry AI models.
• Are you ready to invest to accelerate transformation? As always, cost is an important issue; especially given the high levels of investment that AI technology and infrastructure are likely to require. Findings from the most recent “Fortune/Deloitte Global CEO Survey: Spring 2025” reveal that despite operating in an environment of uncertainty, surveyed CEOs recognize opportunities for growth, innovation, and resilience for the road ahead and plan to continue to invest in and reap the rewards of AI, with almost two-thirds reporting that genAI has delivered value to their organizations.

From streamlining processes and uncovering insights during deal sourcing and due diligence to enabling smarter, faster decisions when acquiring assets, and ultimately helping organizations realize synergies and drive value post-deal, genAI is emerging as a powerful tool to help reshape M&A. Those who embrace and make moves to increase AI capabilities may be better positioned to unlock greater efficiency, mitigate risk, and achieve outcomes in the evolving world of mergers and acquisitions.