Hi Jon, Did you see that paper by GEP / CIPS? I didn’t read it, yet.
Thank you for sending it; I hadn’t seen it. Interestingly, GEP has been following me and my posts on LinkedIn in increasing numbers and frequency lately.
1999 Revisited (Video) – Real Agents Leveraging AI
GEP Autonomous Agentic AI Agents(High-Level Summary)
GEP is set to revolutionize procurement and supply chain operations by introducing autonomous AI agents into the Source-to-Contract (S2C) and Procure-to-Pay (P2P) processes. These AI agents are designed to work alongside employees, making informed decisions and executing tasks with precision across procurement and complex global supply chains.
Key Features of GEP’s Autonomous AI Agents:
Self-Reflective Learning: Unlike traditional AI models that require human prompts, these agents possess a memory engine that enables them to learn from past experiences and mistakes, enhancing their decision-making capabilities over time.
Integrated Reasoning with LLM Inputs: By combining reasoning abilities with inputs from Large Language Models (LLMs), the agents can interpret natural language directions from employees, autonomously pull relevant data, and interact directly with both internal systems and external stakeholders.
Anticipated Transformations in S2C and P2P:
Enhanced Efficiency: Automating routine tasks in the S2C and P2P cycles will streamline operations, reduce manual errors, and accelerate procurement processes.
Strategic Focus: With AI agents handling low-value, repetitive tasks, procurement teams can redirect their efforts toward strategic initiatives, such as supplier relationship management and category strategy development.
Improved Compliance and Risk Management: AI agents can monitor compliance with procurement policies and identify potential risks, ensuring adherence to regulations and mitigating supply chain disruptions.
GEP plans to integrate these autonomous AI agents into their solutions starting in 2025, aiming to provide clients with advanced tools that enhance agility, efficiency, and resilience in procurement and supply chain operations.
For a comprehensive understanding of how these AI agents will transform procurement and supply chain operations, GEP offers a detailed white paper on the subject.
The Initial Takeaway
To start, GEP seems to be moving (or trying to move) in the right direction. Many of the points their paper highlights as features, e.g., self-reflected learning and integrated reasoning, were successfully implemented in the late 1990s about which I have been writing since the mid-2000s:
Throughout the research period (partly funded by the Government of Canada’s Scientific Research and Experimental Development – SR&ED program), we consistently looked for ways in which a buyer could reliably procure commodities on a real-time basis outside of the confines of a centrally negotiated contract. To do this effectively, the buyer would have to simultaneously engage key stakeholders such as suppliers, courier companies, and customs brokers – enter the Metaprise.
Over the years, with each amazing breakthrough – and yes, spreadsheets and amber or green monochrome monitor graphics were amazing in their time, I was asked what I think about the “evergreen” evolution of high-tech computing. My answer has always been the same – it’s not about the technology but the problems the technology solves. In other words, as great as the tech may be, it means nothing if it doesn’t come after people and process understanding.
When organizations make the mistake of leading with technology, they are bending their people and processes around an equation-based model approach in which the tech is the driver for success.
When you lead with people and process understanding – an agent-based model, technology moves from a functional driver to a problem-solving tool that streamlines and delivers efficiencies and tangible results.
After watching the video and then reading the highlights from the new GEP paper, the biggest difference, and potentially the fatal flaw of the Agentic AI model GEP is championing, is that it is being built using a technology-led Equation-based model versus using a “true” Agent-based solution development and implementation model. In short, history is at risk of repeating itself because no matter how amazing the technology – and I have seen exciting breakthroughs in my 40-plus years in the high-tech and procurement industry when you lead with technology or put your trust in technology to do what humans do, initiative failure is inevitable as demonstrated by the high generational failure rate of ProcureTech initiatives.
You can use the following link to access my Procurement Insights archives on the difference between Agent-based solution development using advanced self-learning algorithms within a nascent AI framework and Agentic AI solution development models.
Over the Holiday, I will go through my physical archives to pull out the original patent document for my RAM platform and the actual application that was copied to master disks to share with you. I will also be digging deeper into the GEP white paper.
Procurement Insights
New GEP Paper: Agentic AI Versus Real Agents?
Posted on December 13, 2024
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Hi Jon, Did you see that paper by GEP / CIPS? I didn’t read it, yet.
Thank you for sending it; I hadn’t seen it. Interestingly, GEP has been following me and my posts on LinkedIn in increasing numbers and frequency lately.
1999 Revisited (Video) – Real Agents Leveraging AI
GEP Autonomous Agentic AI Agents (High-Level Summary)
GEP is set to revolutionize procurement and supply chain operations by introducing autonomous AI agents into the Source-to-Contract (S2C) and Procure-to-Pay (P2P) processes. These AI agents are designed to work alongside employees, making informed decisions and executing tasks with precision across procurement and complex global supply chains.
Key Features of GEP’s Autonomous AI Agents:
Anticipated Transformations in S2C and P2P:
GEP plans to integrate these autonomous AI agents into their solutions starting in 2025, aiming to provide clients with advanced tools that enhance agility, efficiency, and resilience in procurement and supply chain operations.
For a comprehensive understanding of how these AI agents will transform procurement and supply chain operations, GEP offers a detailed white paper on the subject.
The Initial Takeaway
To start, GEP seems to be moving (or trying to move) in the right direction. Many of the points their paper highlights as features, e.g., self-reflected learning and integrated reasoning, were successfully implemented in the late 1990s about which I have been writing since the mid-2000s:
2007 – Dangerous Supply Chain Myths (Excerpt):
Throughout the research period (partly funded by the Government of Canada’s Scientific Research and Experimental Development – SR&ED program), we consistently looked for ways in which a buyer could reliably procure commodities on a real-time basis outside of the confines of a centrally negotiated contract. To do this effectively, the buyer would have to simultaneously engage key stakeholders such as suppliers, courier companies, and customs brokers – enter the Metaprise.
2023 – Are you chasing solutions or solving problems? (Excerpt):
Over the years, with each amazing breakthrough – and yes, spreadsheets and amber or green monochrome monitor graphics were amazing in their time, I was asked what I think about the “evergreen” evolution of high-tech computing. My answer has always been the same – it’s not about the technology but the problems the technology solves. In other words, as great as the tech may be, it means nothing if it doesn’t come after people and process understanding.
When organizations make the mistake of leading with technology, they are bending their people and processes around an equation-based model approach in which the tech is the driver for success.
When you lead with people and process understanding – an agent-based model, technology moves from a functional driver to a problem-solving tool that streamlines and delivers efficiencies and tangible results.
After watching the video and then reading the highlights from the new GEP paper, the biggest difference, and potentially the fatal flaw of the Agentic AI model GEP is championing, is that it is being built using a technology-led Equation-based model versus using a “true” Agent-based solution development and implementation model. In short, history is at risk of repeating itself because no matter how amazing the technology – and I have seen exciting breakthroughs in my 40-plus years in the high-tech and procurement industry when you lead with technology or put your trust in technology to do what humans do, initiative failure is inevitable as demonstrated by the high generational failure rate of ProcureTech initiatives.
You can use the following link to access my Procurement Insights archives on the difference between Agent-based solution development using advanced self-learning algorithms within a nascent AI framework and Agentic AI solution development models.
Over the Holiday, I will go through my physical archives to pull out the original patent document for my RAM platform and the actual application that was copied to master disks to share with you. I will also be digging deeper into the GEP white paper.
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