Technology is already reshaping M&A origination, learning how to use it quickly is becoming a competitive necessity

In M&A, much of the attention naturally goes to execution: negotiation, financing, due diligence, and the ability to close complex transactions. These are, of course, critical parts of the process. But for many professionals in the industry, the real bottleneck has always come much earlier: origination. Identifying relevant, differentiated and genuinely actionable opportunities remains one of the hardest parts of the job.

For years, origination has relied heavily on experience, personal networks, sector knowledge, and a highly manual process of research and filtering. That is still true today. But something is clearly changing. New technology is no longer a distant prospect or a theoretical discussion. It is already becoming part of day-to-day workflows and reshaping the way opportunities are identified, prioritised and pursued. Bain reported in early 2025 that 21% of surveyed M&A practitioners were already using generative AI in M&A, with the most common use cases centred on finding and validating deals.

The evolution has followed a logical path, although the stages have often overlapped. The first wave came through more packaged and standardised solutions: platforms designed to improve company search, market mapping, comparable analysis and first-pass screening. These tools helped teams broaden coverage, organise information more efficiently and reduce manual work. Over time, as firms became more familiar with what these technologies could actually do, the market began to move towards more specific applications: targeted scouting solutions, more tailored analytical workflows and, increasingly, AI tools embedded into particular stages of origination and research. McKinsey reported in January 2026 that, among respondents with moderate to high gen-AI adoption, a majority were already using it for target identification and due diligence.

That shift matters because origination is a function where even small improvements can have a significant effect. Expanding the target universe, identifying relevant signals more effectively, prioritising with greater accuracy, or reducing time spent on repetitive tasks can all translate into a tangible advantage. And in M&A, that advantage often comes down to timing. Reaching a company first, developing an investment thesis first, opening a conversation first, or spotting a change in direction before others do can make the difference between originating a proprietary opportunity and entering a process that is already competitive. Bain is explicit on this point: firms that master gen AI in M&A are expected to identify targets faster than their competitors.

Along that path, different types of tools are already playing different roles. Comparables.ai describes itself as an AI-powered platform for market intelligence and company analysis, with specific applications in valuation and M&A sourcing. Inven presents itself as an AI-native deal-sourcing platform for private markets, including predictive “intent to sell” signals designed to help identify companies that may be preparing for a sale. Tracxn offers broad coverage of private companies across sectors and geographies, together with market maps, sector intelligence and transaction data. And Claude, while not a deal-sourcing platform in itself, can be a useful research and analysis tool for synthesising information and reviewing large volumes of material more efficiently. These tools are not interchangeable, but they illustrate how much of the initial value proposition was first delivered through more standardised products.

There are now also clearer examples of more specific adoption. In April 2025, the Financial Times reported that Rogo, an AI start-up founded by former Lazard analyst Gabriel Stengel, was already being used by firms including Moelis, Nomura, Tiger Global and GTCR. The report said the platform could quickly assess a company’s market position, pull basic valuation comparisons and analyse competitors. These are precisely the kinds of tasks that can support origination and early-stage screening when combined with senior judgement.

McKinsey has also described (in its Jannuary 2026 piece) a case in which a fast-growing software company used a third-party AI-powered scouting platform to accelerate target identification, screening more than 500 potential targets in less than a day and narrowing them down to a short list of priority opportunities.

None of this removes the complexity of origination, but it does address some of its most persistent inefficiencies. And that is precisely where the early adopter advantage becomes most apparent. In a market where many participants still rely on similar methodologies, the first teams to integrate these tools properly do not simply gain internal efficiency. They also gain the ability to cover a broader market, reach certain profiles earlier and allocate their commercial effort more effectively. Over time, these capabilities will become more widespread. But in the meantime, the firms that learn faster are likely to enjoy a meaningful, if temporary, edge.

Naturally, it would be a mistake to interpret this evolution as the beginning of fully automated origination. Relationships, judgement, an understanding of shareholder motivations, a sense of timing and the ability to build trust remain irreplaceable. Technology does not replace those capabilities; it amplifies them when used with sound judgement. That is why the real risk today is probably not overestimating these tools, but underusing them or adopting them too superficially.

At CDI GLOBAL, we are already incorporating new procedures with considerable success, generating significant efficiencies in both market research and origination. The experience confirms something essential: the pace of development in this area is extremely fast. What looks innovative today may become standard within a matter of months. That is why the challenge is no longer whether to engage with these tools, but how to incorporate them pragmatically, intelligently and with the right support. In origination, technology is not here to replace judgement or relationships, but it can significantly expand the capabilities of those who learn to use it well. And in an activity where access to differentiated opportunities remains decisive, that learning curve can still be a real source of competitive advantage.

By: Eduardo González-Gallarza