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Why Most AI Demos Don't Translate to Production

That impressive vendor demo was designed to impress. What it didn't show you, and the questions worth asking before you sign.
18 October 2023·3 min read
Isaac Rolfe
Isaac Rolfe
Managing Director
enterprise-aiprocurementdelivery
I've sat through more AI demos in 2023 than in the previous decade combined. Most of them are brilliant. Almost none of them show you what you actually need to see.
Here's what a typical AI demo shows: a clean document goes in, a beautiful analysis comes out, the audience gasps, and someone says "imagine this at scale."
Here's what it doesn't show:
The messy inputs. That contract was typed, formatted, and probably hand-selected. What about the scanned document with coffee stains? The email chain with five different reply formats? The handwritten notes stapled to a printed form? These aren't edge cases. They're Tuesday morning.
The integration. The demo runs on a laptop. Production means connecting to your document management system, your CRM, your policy database, your workflow engine, and whatever legacy system runs on a server that nobody's allowed to reboot. That integration is 60% of the real work and 0% of the demo.
The error handling. The demo got the right answer. What happens when it doesn't? What's the confidence score? Where's the escalation path? How does the user know the difference between a reliable output and a hallucination?
The governance. Who approved this model? What data was it trained on? How is it monitored? What happens when it encounters PII? The demo skips governance because governance isn't exciting. Production requires it because regulations aren't optional.
The cost at scale. Processing one document in a demo costs fractions of a cent. Processing 10,000 documents a day costs real money: compute, monitoring, error handling, in human review of the cases the AI can't handle.
Five questions to ask after every AI demo:
  1. "Can you show me this with our actual documents?" Not their curated examples. Your messy, real-world inputs.
  2. "What does integration with our systems look like?" If they wave vaguely at "APIs," they haven't thought about it.
  3. "What happens when it gets the answer wrong?" If the answer is "it doesn't," leave.
  4. "What does the total cost look like at our volume?" Including infrastructure, monitoring, human review, and ongoing model costs.
  5. "What does your team need from us to make this work?" The honest answer reveals the real complexity.
The demo is the beginning of the conversation, not the conclusion. Any vendor who expects you to decide based on a demo is selling you a demo, not a solution.