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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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