Leveraging AI in M&A: Uses and Limitations, Interpreting Conflicting Results, Eliminating Bias, Mitigating Risks

This CLE webinar will examine applications of artificial intelligence (AI) in the M&A deal process. The speaker will discuss the uses of AI in evaluating potential targets, informing due diligence, customizing deal structures, and analyzing post-acquisition integration challenges and opportunities. The speaker will also address key risks in using AI during the M&A lifecycle and ways to navigate these challenges.

AI and data analytics continue to transform the M&A process. Data analytics can better gauge the value of a deal by broadening the number of factors considered. By analyzing both internally and externally generated data an acquirer can gain a more comprehensive overview of a prospective target.

Predictive tools can analyze data to quickly highlight worthy M&A deals and create an investment hypothesis based on the analysis. The findings can then direct the due diligence process and valuation of an identified target as well as serve as a roadmap for steps to take post-acquisition.

As AI technologies continue to evolve and improve, they present new opportunities for lawyers to streamline the M&A process. However, AI also has distinct limitations and risks. Data streams can be deceptive, and AI tends to trust data as binary. AI systems function better in closed environments—they are not trained to interact with other AI systems—but business and legal decisions can be very nuanced. Deal parties and their counsel must be able to interpret conflicting AI results and reconcile disparate data sets to form conclusions about how to proceed. They must also be on the lookout for yellow or red flags presented by the data and bias inherent in AI processes.

Listen as our authoritative speaker discusses the ways in which data analytics and AI can enhance the acquisition process and the limitations and risks of AI that must be taken into account in every deal.