I will add another dimension to yesterday’s post and the resulting discussion regarding native AI solutions. Here is an excerpt from today’s earlier Procurement Insights post – https://bit.ly/4m3oqXL
ONE FINAL THOUGHT: In 1998, with funding from the government’s Scientific Research & Experimental Development (SR&ED) Program, I developed the procurement industry’s very first nascent ProcureTech native AI platform. Based on my theory of strand commonality, the platform went into a production environment and successfully delivered tangible and measurable outcomes for crucial KPIs.
In this post, I will delve into what a native platform really is and how it is NOT solely based on technology.
As you read today’s post, one final thought to keep in the back of your mind: Generative AI Models require a centralized AI Operating System. A 4-Model Agent-based assessment tool that leverages my RAM 1998 to 2025 framework architecture logic provides a foundational framework for such an Operating System.
What Is A Native AI Platform?
A native AI ProcureTech solution is a procurement technology platform that is fundamentally built with artificial intelligence (AI) as an integral part of its architecture, rather than having AI added as an afterthought or enhancement. These solutions leverage AI to drive core procurement and supply chain processes—such as sourcing, supplier management, spend analysis, and contract lifecycle management (CLM)—in a seamless, embedded way. The “native” aspect means AI isn’t a bolt-on feature but a foundational element designed to optimize procurement outcomes from the ground up.
What About Legacy ProcureTech?
The ProcureTech space is evolving rapidly, with AI becoming a core component of modern solutions—cognitive systems are predicted to dominate by 2030 (Procurement Magazine, 2024). However, true native AI ProcureTech solutions are still emerging, as many providers (even leaders like SAP Ariba) started as traditional platforms and are retrofitting AI. This can lead to integration challenges, whereas newer platforms like ORO Labs are designed with AI at their core, offering a more cohesive experience. Data quality remains a hurdle—60% of procurement leaders cite poor data as a barrier to AI adoption (ProcureTech, 2024)—which native AI solutions must address through robust data architecture.
The Importance Of An Operating System For AI
We are fast approaching the intersection of the AI and ProcureTech solution offerings, the master AI Operating System. Companies that are well into the crossroads that you will want to check out include ConvergentIS Shaun Syvertsen, and Focal Point Anders Lillevik Matthew Buckingham Steven Buterbaugh.
There are, of course, others, but be cognizant of the following:
- What is likely to happen if you walk down a street with your head down, admiring your shiny new shoes? This is how most ProcureTech organizations are developing their “native AI” solutions.
- While an AI Operating System involves technology, it is not a technology-first undertaking. After 40-plus years in high tech, this and the previous point have remained constant.
30
BONUS CONTENT – The History of the Operating System
CP/M, while primarily a text-based operating system, CP/M could display images by utilizing specific hardware and software. While not natively supported, some systems and programs allowed for the display of graphics in formats like RLE, .PCX, .GIF, and .BMP.
- Text-Based Interface: CP/M’s main interface was text-based, meaning it didn’t have a graphical user interface (GUI) like modern operating systems.
DOS, MS-DOS (which stands for Microsoft Disk Operating System) is an operating system which first came out in 1981 and was designed to run on PC compatible computers. It was primarily used as the main operating system on PCs until 1995, when Windows 95 overtook it as the most popular OS of choice.
Windows OS (Operating System) is a software that manages computer hardware and software, providing a graphical user interface (GUI) for users to interact with their devices. It’s developed and marketed by Microsoft and is widely used on personal computers, smartphones, and even gaming consoles.
Generative AI uses a text-based interface as a common input method for Generative AI, especially for Large Language Models (LLMs). These AI models are trained on vast datasets of text and can generate new text, images, audio, and code based on text prompts. For example, a user might input a description of an image they want to generate or a question they want answered.
Reading the above, what is your takeaway?
Could it be the following? Have we come full circle?
CP/M (Control Program for Microcomputers) and Generative AI (Gen AI) interfaces may seem worlds apart given their origins—CP/M as a 1970s operating system and Gen AI as a modern AI technology—but they share some conceptual and functional commonalities, especially when viewed through the lens of computing history and their relevance to systems like those in procurement or supply chain contexts (e.g., Kaypro computers).
Procurement Insights
A Central AI Operating System For Generative AI
Posted on May 9, 2025
0
I will add another dimension to yesterday’s post and the resulting discussion regarding native AI solutions. Here is an excerpt from today’s earlier Procurement Insights post – https://bit.ly/4m3oqXL
ONE FINAL THOUGHT: In 1998, with funding from the government’s Scientific Research & Experimental Development (SR&ED) Program, I developed the procurement industry’s very first nascent ProcureTech native AI platform. Based on my theory of strand commonality, the platform went into a production environment and successfully delivered tangible and measurable outcomes for crucial KPIs.
In this post, I will delve into what a native platform really is and how it is NOT solely based on technology.
As you read today’s post, one final thought to keep in the back of your mind: Generative AI Models require a centralized AI Operating System. A 4-Model Agent-based assessment tool that leverages my RAM 1998 to 2025 framework architecture logic provides a foundational framework for such an Operating System.
What Is A Native AI Platform?
A native AI ProcureTech solution is a procurement technology platform that is fundamentally built with artificial intelligence (AI) as an integral part of its architecture, rather than having AI added as an afterthought or enhancement. These solutions leverage AI to drive core procurement and supply chain processes—such as sourcing, supplier management, spend analysis, and contract lifecycle management (CLM)—in a seamless, embedded way. The “native” aspect means AI isn’t a bolt-on feature but a foundational element designed to optimize procurement outcomes from the ground up.
What About Legacy ProcureTech?
The ProcureTech space is evolving rapidly, with AI becoming a core component of modern solutions—cognitive systems are predicted to dominate by 2030 (Procurement Magazine, 2024). However, true native AI ProcureTech solutions are still emerging, as many providers (even leaders like SAP Ariba) started as traditional platforms and are retrofitting AI. This can lead to integration challenges, whereas newer platforms like ORO Labs are designed with AI at their core, offering a more cohesive experience. Data quality remains a hurdle—60% of procurement leaders cite poor data as a barrier to AI adoption (ProcureTech, 2024)—which native AI solutions must address through robust data architecture.
The Importance Of An Operating System For AI
We are fast approaching the intersection of the AI and ProcureTech solution offerings, the master AI Operating System. Companies that are well into the crossroads that you will want to check out include ConvergentIS Shaun Syvertsen, and Focal Point Anders Lillevik Matthew Buckingham Steven Buterbaugh.
There are, of course, others, but be cognizant of the following:
30
BONUS CONTENT – The History of the Operating System
CP/M, while primarily a text-based operating system, CP/M could display images by utilizing specific hardware and software. While not natively supported, some systems and programs allowed for the display of graphics in formats like RLE, .PCX, .GIF, and .BMP.
DOS, MS-DOS (which stands for Microsoft Disk Operating System) is an operating system which first came out in 1981 and was designed to run on PC compatible computers. It was primarily used as the main operating system on PCs until 1995, when Windows 95 overtook it as the most popular OS of choice.
Windows OS (Operating System) is a software that manages computer hardware and software, providing a graphical user interface (GUI) for users to interact with their devices. It’s developed and marketed by Microsoft and is widely used on personal computers, smartphones, and even gaming consoles.
Generative AI uses a text-based interface as a common input method for Generative AI, especially for Large Language Models (LLMs). These AI models are trained on vast datasets of text and can generate new text, images, audio, and code based on text prompts. For example, a user might input a description of an image they want to generate or a question they want answered.
Reading the above, what is your takeaway?
Could it be the following? Have we come full circle?
CP/M (Control Program for Microcomputers) and Generative AI (Gen AI) interfaces may seem worlds apart given their origins—CP/M as a 1970s operating system and Gen AI as a modern AI technology—but they share some conceptual and functional commonalities, especially when viewed through the lens of computing history and their relevance to systems like those in procurement or supply chain contexts (e.g., Kaypro computers).
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