AI can generate a polished valuation in seconds, but incomplete public M&A data, outdated deal information, and missing buyer context can make that estimate dangerously misleading.
In this special report, we'll go over why fewer than 15% of technology transactions disclose deal value, how an AI-generated valuation can anchor expectations and cost you millions, and why a competitive global M&A process can create value no spreadsheet, no algorithm and no AI can predict.
Learn where AI helps in tech M&A, where it falls short, and why your company is ultimately worth what a qualified buyer is willing to pay.
Key Takeaway
• AI valuations rely on a small, self-selected portion of disclosed technology transactions, leaving much of the relevant market evidence unseen.
• A valuation model is a starting point—not the final measure of what a qualified buyer may pay.
• The best buyer may be outside a seller's obvious shortlist and may come from another geography, a private equity platform, or a company entering the market.
• Relationships, deal structure, succession goals, tax considerations, and negotiation nuance cannot be captured fully by an automated model.
• AI is most effective as a competitive advantage within a professional M&A process—not as a shortcut that replaces one.
Chapters
00:00 Can AI Value Your Company?
00:54 Why AI Valuation Multiples Can Mislead
01:15 Real World Example
01:39 Where the Extra Value Comes From
02:26 Finding the Right Buyers
03:27 The Risk of Valuation Anchoring
03:47 Five More Ways AI Can Fail in M&A
04:35 Use AI as an Advantage, Not a Shortcut
