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WBS for Artificial Intelligence Projects
Building an AI Product could have more nuances compared to a simple SDLC based Agile Or Waterfall Project.
If anyone has recently executed an AI Product Development & Testing Project, can you please share a WBS for same for others to learn.
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Aditya -

Given the high degree of uncertainty and complexity with an A.I. product development project, I'd assume that it would follow an adaptive approach and as such, your WBS could likely only be developed to one or two levels deep.

It would also depend heavily on the nature of the AI product. If it is a machine learning-based approach, that will drive a certain set of deliverables and activities whereas a different type of AI would require others.

In my case, I am constantly running this type of project and I am using Agile based approach most of the time using Kanban or sometimes Scrum as the support method/framework. Please, do not think that I am saying that Kanban or Scrum are "agile methods/frameworks". Not at all. Just one fits for our flow based initiatives while the other fits for our batches based initiatives and one or another fits for AI and Data Science initiatives just in our case.
Here's ChatGPT's suggestioni:

I. Project Initiation
A. Define project scope and objectives
B. Conduct market research
C. Gather requirements and constraints
D. Develop project plan

II. Requirements Analysis and Design
A. Perform feasibility study
B. Develop high-level system architecture
C. Define system requirements
D. Design AI algorithms

III. Development
A. Implement AI algorithms
B. Develop User Interface (UI)
C. Integrate AI components with UI
D. Implement data storage and management

IV. Testing
A. Unit testing
B. Integration testing
C. System testing
D. User acceptance testing

V. Deployment
A. Deploy to production environment
B. Provide training to end-users
C. Monitor and maintain system performance

VI. Project Closeout
A. Evaluate project results
B. Document lessons learned
C. Close project

Note: This is a high-level example and may need to be adapted and refined based on the specific requirements and constraints of the AI product development project.

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