AI is MAGIC. Or is it?
At least, that's what everyone seems to believe right now.
✨ I've been building AI into Hermix for years. Using it daily. Testing it across dozens of real procurement scenarios with real companies. And I can tell you: Arthur C. Clarke had it right. Sufficiently advanced technology really is indistinguishable from magic.
The problem is when people stop there.
Because AI is also not magic. And in public procurement, confusing the two is expensive.
✔️ Here's what I've actually seen work. GPT models reading 300-page tender documents and producing structured summaries in minutes. Machine learning cleaning up years of fragmented procurement data across 250,000+ European authorities. AI Chat answering "which experts are required?" or "what's the minimum turnover?" directly from the document, in seconds. GraphRAG and Deep Reasoning handling the complex multi-hop analysis that standard models get wrong. SearchGPT building buyer profiles that would take a junior analyst two days to assemble manually.
This is real. The numbers back it up. 87% reduction in market research time. 75% reduction in tender analysis time. 60% less time writing proposals. Our users at Capgemini, Accenture, Unisys, Fujitsu, and 50+ other companies work this way every day.
❌ But here's what I've also seen fail.
Relying on AI to generating "original" ideas. AI missing cultural, technical or commercial subtext - that changes the entire meaning of evaluation criteria. Non-supervised AI producing output confident enough to submit and wrong enough to lose a bid. These failures are real too. And they happen more often when teams treat AI as a black box rather than a tool that requires judgment and supervision. Then comes disillusionment.
AI in procurement compresses effort dramatically. It does not replace strategic thinking.
The companies winning consistently in public sector are not the ones using the most AI. They are the ones using AI for the right tasks, at the right stages, with human judgment at the decision points that matter.
Finding the right tenders. Understanding buyers before the RFP drops. Qualifying opportunities with real competitive data. Reducing the manual burden of documentation. These are the jobs AI does well.
Deciding whether to bid. Understanding what the buyer actually wants versus what they wrote. Building a differentiated technical approach. These remain human work.
❓ There is also a question worth sitting with. If AI writes the procurement. Writes the proposal. Evaluates the submission. What exactly are we measuring? I don't have a clean answer. But I think it matters that we're asking it.
I've written a longer piece on this. What works, what doesn't, the specific techniques we use at Hermix (GraphRAG, Deep Reasoning, SearchGPT, citation support), and the adoption barriers nobody talks about honestly.
https://hermix.com/ai-is-magic-or-is-it/
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