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For all kinds of tasks, we usually follow a plan knowingly or unknowingly. The steps taken to complete a task
              from the beginning to its end are called Project Cycle. These steps help us complete the task effectively.

              Similarly, if we have to develop an AI project, we need to follow the AI project cycle that provides us with an
              appropriate framework to lead us towards our goal. The AI project cycle is a roadmap to plan, develop and
              deploy AI solutions. The AI project cycle provides us with a framework for planning, organising, executing and
              implementing an AI project to accomplish a task. It is a structured approach to move from the conception of an
              AI idea to its practical implementation and sustained operation.

              Following a well-defined AI project cycle ensures that every stage of the AI project is methodical and minimises
              unforeseen issues. The following figure shows six stages of the AI project cycle:

                                                              Problem
                                                              Scoping



                                                                                  Data
                                            Deployment
                                                                               Acquisition






                                                                                 Data
                                            Evaluation
                                                                              Exploration



                                                              Modelling


              The description of these six stages is as follows:


               Stage 1   Problem Scoping

              The first stage of an AI project cycle is Problem Scoping, where the problem is clearly identified, and a vision
              for addressing the same is developed. It is a crucial step where the focus is thoroughly on understanding the
              problem by considering the various factors that influence it, and determining how AI technology can provide a
              solution.
              To achieve a comprehensive understanding, this phase emphasises the use of the 4W’s: Who, What, Where,
              and  Why.  This  approach  ensures  that  all  critical  components  of  the  problem  are  clearly  defined,  aligning
              stakeholders and team members.
                 • Who: This step identifies who will be affected from the AI solution, as well as any stakeholders involved in the
                 project. It considers the target audience, users, and decision-makers.

                 • What: This step defines the specific problem or challenge that needs to be addressed with AI. It outlines the
                 goals and the desired outcome of the project.
                 • Where: This step focuses on where the AI solution will operate or be implemented. It could refer to the technical
                 environment, the geographical location, or the specific domain.
                 • Why: This step explores the reason behind solving the problem. It looks at the value and impact that solving
                 the problem will have for the business, users, or society.



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