“The complexity behind simplicity is a paradoxical but fundamental truth: achieving simplicity requires profound effort, thought, and mastery. Simplicity is not the absence of complexity but the result of understanding, organizing, and refining it to make it invisible to the user. This principle applies to design, communication, leadership, and countless other fields, underscoring its universal importance.” (Source: ChatGPT)
I agree with the above statement regarding the complexity behind simplicity.
However, regarding ProcureTech development and implementation, I often see confusion about who (or what) represents the complex and what represents the simple. In many instances, when asking this question, the complexity is the technology, and the simple is the outcome for humans.
I will stop here to state that over the past several decades and various iterations of technology breakthroughs, 80% of all ProcureTech initiatives have and are continuing to fail. By some estimation, the current AI has the highest failure rate ever at 88%.
Why?
Reverse Positions
Complexity and technology are often seen as being one and the same.
The simplicity part of the equation is often represented by the convenience and speed technology creates for people, e.g., technologies such as RPA and various progressive genres of AI freeing humans up to focus on more strategic activities.
However, the people, and more to the point, how they as agents operate independently and collectively in the real world precedes the creation of technology. Once you harness this understanding by utilizing an agent-based model by leveraging industry experience and expertise, creating the technology becomes the “simpler” part.
Here is a high-level example of agent-based ProcureTech solution development and implementation:
The Risk Of Abdicating Human Input To TechnologyUnderstanding
Artificial intelligence’s greatest promise and benefits also represent the greatest risk procurement professionals and corresponding ProcureTech initiatives face by creating a false sense of inherent or organic understanding and competency.
In the above video, the self-learning algorithms within the nascent AI framework were based solely on human knowledge. In short, knowledge is not part of self-driven AI capability but the ability of AI to utilize human-directed input to produce greater efficiencies and performance output.
Unfortunately, with Generative AI and now Agentic AI, there is a misconception that human input can be “automated” to the point that technology can handle critical thinking with minimal human engagement. The 88% failure rate of AI initiatives challenges this thinking.
Procurement Insights
People And ProcureTech: The Complexity Behind Simplicity
Posted on December 5, 2024
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“The complexity behind simplicity is a paradoxical but fundamental truth: achieving simplicity requires profound effort, thought, and mastery. Simplicity is not the absence of complexity but the result of understanding, organizing, and refining it to make it invisible to the user. This principle applies to design, communication, leadership, and countless other fields, underscoring its universal importance.” (Source: ChatGPT)
I agree with the above statement regarding the complexity behind simplicity.
However, regarding ProcureTech development and implementation, I often see confusion about who (or what) represents the complex and what represents the simple. In many instances, when asking this question, the complexity is the technology, and the simple is the outcome for humans.
I will stop here to state that over the past several decades and various iterations of technology breakthroughs, 80% of all ProcureTech initiatives have and are continuing to fail. By some estimation, the current AI has the highest failure rate ever at 88%.
Why?
Reverse Positions
Complexity and technology are often seen as being one and the same.
The simplicity part of the equation is often represented by the convenience and speed technology creates for people, e.g., technologies such as RPA and various progressive genres of AI freeing humans up to focus on more strategic activities.
However, the people, and more to the point, how they as agents operate independently and collectively in the real world precedes the creation of technology. Once you harness this understanding by utilizing an agent-based model by leveraging industry experience and expertise, creating the technology becomes the “simpler” part.
Here is a high-level example of agent-based ProcureTech solution development and implementation:
Additional reading resources:
The Risk Of Abdicating Human Input To Technology Understanding
Artificial intelligence’s greatest promise and benefits also represent the greatest risk procurement professionals and corresponding ProcureTech initiatives face by creating a false sense of inherent or organic understanding and competency.
In the above video, the self-learning algorithms within the nascent AI framework were based solely on human knowledge. In short, knowledge is not part of self-driven AI capability but the ability of AI to utilize human-directed input to produce greater efficiencies and performance output.
Unfortunately, with Generative AI and now Agentic AI, there is a misconception that human input can be “automated” to the point that technology can handle critical thinking with minimal human engagement. The 88% failure rate of AI initiatives challenges this thinking.
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