In yesterday’s post we told you that AI and Agents, being touted by all the new startups as the next generation of Procure-and-Fin-Tech applications that will replace your entire Procure-and-Fin-Tech workforce, is nothing new and any new startup saying otherwise is just shovelling sh!t your way as it clears out the marketing stable.

First of all, as we explained yesterday, this is all old tech. In some cases, very old tech.

1) AI, which really means “algorithmic improvement”, and which has been slapped onto every algorithm that was slightly more advanced than the algorithm that came before since 1956, is at least 69 years old. Old enough for one of the founders, Joseph Weizenbaum, to turn against it. (It became Weizenbaum’s Nightmare.)

2) There’s fundamentally no difference between Robotic Process Automation (RPA) and an agent. They both perform actions to produce an effect, so both satisfy the definition of an agent, and RPA dates back to the 1990s.

3) The other hype machine, “orchestration”, is not new either, not even on the web. Tim Berners-Lee invented the Web in 1989, and we had one of the first instances, CORBA, in 1991.

4) All automation is based on workflow, the concept of workflow management dates back to 1921, and workflow was a core capability of MRPs, which predated ERPs, in the 1970s.

And just slapping an LLM-powered chatbot interface on top of old tech (which is the only way you can build a reliable solution) is not innovative. In fact, it is sometimes exnovative and makes things worse!

But this isn’t the biggest problem. The problem is that, to keep up in the digital age (which you all knew was coming since 1995 when Alfred A. Knopf published Being Digital, which was followed by Bill Gates’ first book The Road Ahead later that year), you need to implement solutions that take over your time-consuming tactical, rote, and repeatable number-crunching processes that are best done by what computers were designed for, freeing up your team to focus on the strategic tasks, relationships, and, well, getting things done.

But getting things done is not something that will happen if you adopt a new technology that is nothing but a framework for building an application.

When these vendors claim their platforms can be trained to model your entire process and take over for your current workforce, what the vendors are really saying is they have cobbled together a low-code configurable platform that allows them to build whatever solution you need, provided you can accurately specify what you need.

In other words, you aren’t buying a solution. You’re buying a toolset you can use to build the solution, and if you don’t know what that is, in addition to spending a lot of money on the platform, you’ll be spending 10X as much on consultants to design the solution, configure the platform, and then spend months training the LLM-powered conversational interface to actually do what you want it to do. (The time required will be three times what you expected and the overall cost at least five times as much.)

Even with a low-code, AI-X’d (powered, backed, enhanced, driven, or whatever other meaningless adjective/modifier the vendor slaps on) platform, it will still take months to design and implement a basic solution and years to create a mature one.

Which, FYI, is what you should be paying for … and what you could get for a fraction of the price if you got off the AI hype train and focussed on solutions that were developed over years to solve your problems and work out of the box today.

After all, vendors who have focussed on solving Fin-Tech and Procure-Tech problems for over half a decade will use whatever technology is most applicable to the problem at hand, and if you want an LLM-powered chatbot interface, they’ll give you one, but chances are, for most tasks, the UX will have been streamlined to allow you to be 5 to 10 times more productive without it.

At the end of the day, you want a solution, not an experimental algorithm and marketing hype. And you definitely don’t want to be paying five times as much to be a guinea pig or to pay for the privilege of developing the vendor’s solution for them.