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AI in CPQ and CLM: Hype vs Reality in 2025

3/28/2025
6 min read

AI is everywhere in the conversation about CPQ and CLM, but the truth is a mix of progress and overpromises. Here’s where it really helps, where it struggles, and what’s coming next.

AI in CPQ and CLM: Hype vs Reality in 2025


I get asked about AI in CPQ and CLM almost every week. Everyone wants to know what’s real, what’s hype, and when the big breakthroughs are coming. The truth sits somewhere in the middle. There’s progress, but also a lot of noise and unrealistic expectations.

Where AI Helps Today

CPQ: Helpful, but not magic


AI can recommend configurations, catch pricing mistakes, and suggest next steps. It helps, but it’s not running the show. CPQ is complicated. Every company has its own rules, exceptions, and odd cases. Sales teams deal with contract-based pricing, previously sold assets, ramps, uplifts, and custom discounts. AI needs a lot of guardrails to work well here. Right now, it’s an assistant, not a pilot.

CLM: Data extraction that actually works


For contracts, AI is already useful. It can pull out terms, dates, clauses, and risks, and it speeds up review and migration work. Tools can even answer questions like “What’s the renewal date?” or “Does this contract have X?” for a single document.


It’s good progress, but not perfect. Table extraction still breaks when formats get messy or span multiple pages. Page numbers and hidden e-signature data sometimes creep into results. Image-based clauses are still a problem. And asking AI to search across an entire contract library sounds simple, but it’s a much bigger technical challenge than most expect.

The Big Challenges


How do you make thousands of contracts searchable without losing context? That’s the hard part. It’s not just storing the data. You have to:


  • Build reliable indexing
  • Keep relationships between clauses, parties, and metadata
  • Create summaries that AI can use without losing meaning
  • Choose the right setup, whether that’s vector databases, data lakes, or something else

  • These problems aren’t solved yet, but the industry is working on it.

    What’s Next


    The next breakthroughs may come from better retrieval, smarter indexing, or models that handle longer context and more complex relationships. Will it all come together in the next year or two? Maybe, but don’t count on overnight change. Progress is happening, just not at the pace the hype suggests.

    The Human Factor


    One thing is clear: AI isn’t replacing people here anytime soon. The folks who learn how to use it to speed up their work will have an edge. Those who ignore it, or trust it blindly, will fall behind.


    AI is best as a tool that helps you move faster and focus on the decisions that matter.