It's not about using LLM for calculation, it's about automation and agentic. The integration and deployment in enterprise will be a matter of time. Hiring fresh out of school used to be labor and training, but knowing in 5 years the industry will shrink while the senior staff will keep the boat floating aided by AI, the cutoff time is now. There is no need to keep sending young generation to industries that're bound to be automated enmass. And these are in the immediate near term.
Other industries are yet to see how AI will impact, it may or may not ever. But in some science fields, new graduated PhDs are seen the same hiring freeze. The complete outsourcing of school knowledge to LLM is coming to our life real soon, the only factor not making it faster is the data center and energy, which are being worked on to resolve in a couple years. These are the reason AI is not yet as cheap as search and ready for consumer market. But it's cheap or will be cheaper enough in two years for enterprise at a cost lower than human resource. The answer is obvious when looking at it on a 5 year horizon.
>>"But most importantly, SAP’s software was designed to be extensible from the start. For SAP’s original contract with ICI, SAP didn’t build software from scratch, as was the norm at the time, and instead built on top of a previous project. When SAP released their financial accounting software in 1974, their intention was to build additional software modules on top of it and sell them in the future. This extensibility was SAP’s defining feature. The interoperability across client contexts was considered radical at the time because other approaches started from scratch for every client."
SAP's success can be attributed to something similar to what Facebook and Google did, locking the data and knowledge base to itself. The much bragged "extensibility" is limited to SAP own software modules or will be acquired.
Therefore the extensibility is both the strength and the weakest point of SAP. Unlike most of modern software system, there isn't an open ecosystem for competition at its periphery, resulted in a lackluster UI and unfair challenges to non-SAP software to take advantage of those domain knowledge buried inside the SAP.
SAP's integration doctrine is originated from 1960-1970s. With limit evolution this doctrine has largely ignored the changes in computing for several decades, yet it's still growing its dominance.
Other industries are yet to see how AI will impact, it may or may not ever. But in some science fields, new graduated PhDs are seen the same hiring freeze. The complete outsourcing of school knowledge to LLM is coming to our life real soon, the only factor not making it faster is the data center and energy, which are being worked on to resolve in a couple years. These are the reason AI is not yet as cheap as search and ready for consumer market. But it's cheap or will be cheaper enough in two years for enterprise at a cost lower than human resource. The answer is obvious when looking at it on a 5 year horizon.