Right now every vendor is pushing “AI”, and the vast majority of that “AI” they are pushing is a Gen-AI LLM, and often that is just a wrapper of a third party Gen-AI LLM, like Chat-GPT (which only the French know how to pronounce properly).

And they are pushing this as a cure-all for all your procurement ills. It’s the new magic elixir. The new panacea. But, in reality, it’s the ultimate silicon snake oil, because it almost works. And it makes you feel really good when you use it. In medical terms, it’s not a treatment, it’s a psychedelic that takes all your pain away (until it wears off that is). But, just like the spoonfuls of LSD that allowed Bender to become the Iron Chef, it will only last long enough for the vendor to win the contract from you, and then it will start to fade. Until it fades completely when you need it most and fails you utterly when you need to figure out how to deal with a border closing that just happened, a critical raw material shortage due to an unexpected natural disaster, or a trade war no one saw (but should have seen) coming.

This is because, as we keep telling you, Gen-AI, which was built as a predictor technology to predict what block of text, in natural language, should follow an existing block of text (using chain-of-compute), based on training across a very large corpus of existing documents. It’s no more, no less. That’s why it’s only good for tasks that can be reduced to large document search and summarization. (And natural language translation tasks, because it understands basic semantics and can easily be trained to translate to and from any machine language you train it to.)

However, this doesn’t help you with any task that requires actual computation! It’s not analytical data processing, it’s not optimization, and it’s definitely not advanced machine learning for advanced mathematical pattern detection. These are the majority of your tasks and the tasks you need to do to analyze a situation. Buys should be based on the lowest total cost of ownership at the maximum acceptable risk level. Sales predictions, and thus demand, should be based on tried and true mathematical trends, not hunches or market hype. Basic invoice processing should be against business rules for validation, approval, and payment, and that should be primarily based on rules-based automation.

Note that none of these core technologies you need to solve the majority of your problems are AI, as we pointed out in our recent article that said you don’t need Gen-AI to revolutionize procurement and supply chain management. Not to say that these technologies can’t be enhanced by the right application of AI — for example, AI could predict the optimization paths most likely to arrive at the optimal answer, the right curve fitting algorithms to match the trend lines, and the right outlier analysis to identify missing, off, or fraudulent information.

Real solutions come from real tried-and-true AI technology developed over years, or decades, that was designed to solve a specific type of problem, not generic text processing technology that was not designed for the problem, has no understanding of the problem, and will make stuff up in an attempt to solve the problem (which is referred to as a hallucination, but is not a bug, but a core feature of Gen-AI / LLM technology).

This is also why Agentric AI built on Gen-AI won’t work — you can’t automatically build an RPA sequence from a chain of compute that could be completely hallucinatory, and you certainly can’t rely on it to solve your problem.

This doesn’t mean there isn’t a use for Gen-AI, it can be trained to be a natural language interface to these other tools that will work reliably the vast majority of the time (say 95%+ if trained over time), but the use is definitely NOT what you are being promised.