AI in M&A Procurement
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As we move to the new wave of AI, does anyone have any instances to share of new AI development or new projects they have been working on pertaining to streamlining M&A processes and strategy by incorporating AI?
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Hi Paige,
I have a slightly different response to your question than you were probably intending. I’m the functional workstream lead for our procurement workstream doing PMI, and a big component of my responsibility during due diligence is to operationalise the intended growth by joining up historical P&L components against supplier contracts, and identifying risks within those contracts against wider enterprise contractual positioning and the positioning we believe is required for growth. My company shells out lots of money to outside counsel and consultants during the DD phase, focused on risk identification and value realisation from a revenue standpoint, but before I took over, no one was really looking at the expense side of the equation. M&A is based on making more money, and I contend there are 4 ways to make more money: (1) you sell the same things to new logos at the current price point, (2) you sell new/additional things to the same logos at the current price point, (3) you increase the price point of all items you sell, and (4) you reduce your overhead required to sell your product/service(s). My focus is on (4). To help realise this, I evaluated several purpose-built AI tools on the market surrounding large-scale contract reviews and risk & cost identifications against a “playbook” or any defined standard. After an exhaustive search, I found a tool that did a fairly good job, but it wasn’t mature enough to segregate datasets (which would be a requirement since the intent was to use it in DD, and I need to keep one target’s data separate from another, and be able to delete and clear all data in the event a deal doesn’t close). What I ended up doing was putting together a segregated agent in Copilot that I trained on our standards and default positioning. I could then dump in contract sets from our targets to more quickly identify risks based on a scoring mechanism I put together. As our targets typically supply 100+ vendor contracts during DD, each of which may be between 5-50 pages long, this cut down my time from 10s of hours of reading and cataloguing contracts to a handful of hours cataloguing and reporting on risks. I was then able to further build out the toolset to make recommendations on opportunity cost for mitigating the risks, as well as the institutional cost of not mitigating, thus further advising on the true integration cost to realise value synergies for my workstream.
Again, I believe you’re asking more from a corp dev and pipeline development standpoint, but this is how I have been using AI to streamline the procurement integration workstream.
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