M&A - Transaction processes are being transformed by AI
In view of the increasing use of AI, the M&A market appears to be going through a phase of profound changes. Technologies that were considered experimental additions just a few years ago are shaping up to be an integral part of the professional preparation for a transaction. The M&A sector must therefore brace itself for structural adjustments that could, among other things, significantly impact transaction speed, the quality of decision-making bases as well as valuation parameters.
Current situation
While in many business areas the use of generative AI has already increased considerably, the M&A sector is still at a relatively early stage of implementation. According to recent surveys, only a small proportion of M&A professionals have hitherto used generative AI or AI agents productively in their day-to-day work. Although, many organisations are currently involved in pilot projects, or are preparing for a wider roll-out. This has resulted in a transitional situation where operators who are now already using AI strategically are able to gain a significant edge in terms of knowledge and speed. However, in the medium term, the use of AI will emerge as a fundamental requirement for professional transaction analysis - similar to the introduction of digital data rooms.
The impact of AI on the transaction process
One of the most obvious advantages of using AI includes the drastic reduction in manual research work. Previously, information had to be painstakingly gathered from Commercial Registers, the Federal Gazette, industry reports and internal systems, now however, AI-based tools can be used to aggregate and analyse it within a few minutes. This makes it possible not merely to process the information substantially faster. For the buy-side this means being able to assess potential targets more swiftly, a broader and more objective data basis as well as earlier identification of additional acquisition options.
However, this does not mean that human expertise will no longer be required. Rather, the focus is shifting to less time for laborious work and more time for interpretation, strategic assessments and preparations for negotiations. Consequently, the pressure simultaneously increases for the sell-side to improve its data quality. Companies whose processes and reporting structures are not properly documented or digitalised are increasingly falling behind.
AI tools with clear application benefits
To use the relevant AI features it is frequently not necessary to use any specialised tools because the general systems, such as, Microsoft Copilot or Google Gemini are sufficient for this. Furthermore, there are however also AI solutions that are geared specifically to M&A processes that promise more substantial improvements in quality and efficiency. One example of this is the tool “Rogo” from the eponymous US American company. Rogo is a specialised AI platform for, among others, finance and M&A professionals that is operated in completely separate dedicated environments and combines generative AI financial data integration and workflow automation.
The platform is designed to considerably speed up classic M&A and investment banking processes and to enhance their quality by automating work tasks, such as the creation of pitch decks, financial models, company profiles and market analyses, meeting preparation or document screening.
Changed perspective on business valuations
One of the most far-reaching developments manifests itself in the valuation of businesses. The question is increasingly no longer merely: how profitable is the business today? But instead: how future-proof is its business model in the AI era? Businesses that effectively integrate AI into processes and products will become attractive targets.
Then again, there is a risk of a new form of the valuation discount, namely that the value of businesses that fall back technologically, or whose business models are threatened by AI, could be eroded, even if their current financial situation seems to be stable. This shift is also changing the due diligence focus areas. Greater emphasis is being placed on data quality, the degree of digitalisation and AI competence in addition to the traditional financial and legal issues.
