We’ve found some very exciting, yet also practical applications of AI for our buyside work with clients. A typical buyside process has three stages - sourcing, engaging, and closing. A key to the success of our buyside work is our ability to combine efficient and thorough sourcing research with thoughtful, personalized target engagement, maximizing the pipeline by casting a wide net while optimizing response rate. In the sourcing stage, we are working on techniques to accelerate the discovery of a richer field of acquisition targets using AI.
At its core, sourcing can be a grind. Sure, targets want to be found but the specifics of what they actually DO can be muddled by jargon or marketing embellishment. We work hard to zero in on the best fit, however, it is a surprisingly manual high touch process. If we could point an intelligent sourcing tool at the same public and private datasets, could we improve our target yield?
To test our innovations we directed our investment banking teams that are running existing buyside engagements to apply our “Explainable AI” search tools. As opposed to other tools where you get an output but can’t readily explain how/why your model arrived at that answer, Explainable AI is a specific field of AI where the results are explainable.
The results were pretty spectacular, and we’ve highlighted three takeaways below:
In summary, the application of AI techniques in M&A has shown real promise in our sourcing work for clients. Leveraging tools to infuse AI into the process, we can now take efficient and thorough sourcing to the next level, allowing our teams to focus on the personalized engagement that is so critical to success.
Stay tuned as we continue to expand the application of AI techniques in the M&A process… the upside is truly exciting!

