Knowledge System

AI knowledge system

A Knowledge System is always designed to solve tasks. Either an analysis task, a management task, or a communication task. The curtain van example contained both a communication task (book an appointment with a new customer) and management tasks (send mail out, etc.).


A Knowledge System thus also creates business value by dealing with complexity just as you do today in a company when an employee is performing a job.


So it makes sense to place a Knowledge System in the creation row in the illustration because AI is creating value for the same reasons that you deploy people, processes or IT in your business.


However, there is a significant difference between solving a task as a job, a process, or with AI. The difference is scalability. Unlike the usual way of dealing with complexity, there are no capacity constraints in a Knowledge System.


As you probably remember from the beginning of this section, I told you that AI has the potential to scale value creation exponentially by going through the two stages:


  • Phase 1: AI as a solution to a problem
  • Phase 2: Scaling the value creation


We return to the redress example to understand how AI can be used to scale your value creation processes.


The first phase will focus on solving a specific task that creates value for your business.


In this example, it is the use of Computer-Generated Images (CGI) to create marketing material. It solves a problem here and now, as it is cheaper and more flexible than the alternative, which is an expensive photo shoot.



A consequence of our phase one implementation would be that jobs and processes would change. After all, you no longer had to work with (so many) photo models, and the job of having a photoshoot will gradually disappear.


So the fact that we now use Computer generated images affects the conditions on with our promotion pictures, and our promotion materials can be created.


As you remember from the case, you still take some photos in a studio. Thus, some of the old conditions for how you create value is maintained. As a consequence, you will still have scalability constraints in your processes and jobs. Therefore, you do not reach the realization of the full potential of technology at this stage.


In Phase 2, the goal is to redefine the premise of how your value is created, thus creating the conditions for exponential growth and value creation.


As you may remember from the photoshoot example, there is great value in being able to reach a state where you do not have to take any pictures at all.


By not having to take the pictures physically, it would mean that you could have marketing material ready as soon as your concept was complete. You might be able to have your production batches at shorter intervals, and maybe you could also handle more production batches in smaller sizes because your marketing cost will be reduced.


The achievement of the gains that I just mentioned can all be traced back to the capacity problems of your jobs and processes. You want to remove them, because the result of this will be a higher degree of flexibility in your production.


The goal is now another one than in the first phase. In phase one, you made a solution to solve a specific problem. Now you are focusing on creating a set up where you utilize what you have created in phase one to do things differently. So, you challenge the conditions for how you create value.


Succeeding in Phase Two means creating the foundation for exceptional growth in your business. So, a much more attractive value proposition that what you could achieve in the first phase.


The goal now is to have some of the tasks that are solved by processes and jobs today removed. The consequence of achieving this will be an organization that has unlimited capacity because all the components of the tasks now can be solved by a Knowledge System.


If you succeed in bringing the organization to such a state, then you will have the unlimited capacity in the number of tasks you can handle.



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