5 Critical Mistakes When Implementing AI Pricing Engines in M&A

Learning from Failed Implementations Last year, a mid-sized investment bank spent seven figures building an AI pricing system for deal valuation, only to have their analysts refuse to use it. The problem wasn't the technology - it was the implementation approach. After months of friction, the system sat idle while the team reverted to traditional Excel-based modeling. I've seen this pattern repeat across the industry. AI Pricing Engines offer transformative potential for investment banking valuation workflows, but only when implemented thoughtfully.