5 Stages are Needed for an AI Plan to be Successful

As an individual passionate about AI, I recently sent some comments as such regarding this AI item:

Request for Information on the Development of an Artificial Intelligence (AI) Action Plan

In my view 5 Stages are needed for an AI plan to be successful:

Exploring phase - where having an understanding of AI basics is learned. Most end users are not aware that prompts they enter into https://www.chatgpt.com or https://copilot.microsoft.com are generative prompts. For any kind of core and key automation, plugins along with a series of carefully crafted prompts are needed as well. Also, end users need to know that prompts they enter can be deleted from a said user's profile when applicable. Additionally, AI is made-up of the core concepts which should be part of any education: algorithms, autonomous systems, machine learning, supervised learning, unsupervised learning, reinforcement learning, deep learning and fuzzy logic. Finally, knowing the capabilities, limitations and ethical considerations of the AI based system being utilized is paramount.

Planning phase - actively accessing, defining and planning so that specific measurable objectives are met. Knowing what one wants to measure regarding how time is saved from AI is a major part of this phase. Additionally having key performance indicators and meeting them is key as well. Example: how does AI help regarding defect rates helping with quality, how does AI help regarding a planned to done ratio for predictability and finally how does AI help with happiness for stability.

Formalizing phase - socializing and executing on the AI strategy plan. Have concepts structured and documented into official actionable plans. Currently AI is still evolving but even so, it needs to have core aspects more standardized especially around the use of templates, checklists and protocols.

Scaling phase - delivering both incremental and new values regarding AI aspects. No matter what, an AI plan is going to have to include the handling of a larger workload and workforce. It needs to have the proper infrastructure improvement as needed as well as the proper process optimization for the automating of repetitive tasks, workflows and new practices that evolve.

Realizing phase - having consistent AI value across the environment. Be able to handle the execution of plans accounting for resource utilization, monitoring and control and finally quality assurances. If AI does not have consistency or have value, then it will not fulfill its usefulness.

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