Business analysis has always been about ๐ต๐ฒ๐น๐ฝ๐ถ๐ป๐ด ๐ผ๐๐ต๐ฒ๐ฟ๐ ๐๐ผ๐น๐๐ฒ ๐๐ต๐ฒ๐ถ๐ฟ ๐ฝ๐ฟ๐ผ๐ฏ๐น๐ฒ๐บ๐. Yes, in the โBA vs AIโ conversation, there was a lot of emphasis on WIIFM:
What can AI do for me?
Can AI do my mundane tasks?
Is AI going to replace me?
Sure, you can get ChatGPT to help with research and summarize information, generate a starter list of user stories and suggest boxes to be included in a diagram.
Yet, all this missed the most important points:
What will these user stories be about?ย
What is the project?
What is the client paying for?
Where will the money to pay you for business analysis work come from?
If you are a business analyst who wishes to remain relevant and needed, you must learn how to analyze requirements for data science and AI projects.
How are the projects changing?
What and how much analysis is needed for an embedded analytics initiative?
What is the role of a business analyst when embedding analytics insights into a business process?
Check out my new video on this, and letโs change the perspective and think about what we can do for our organizations that do not want to be left behind in the race to harness AI for their business advantage.
If you want to learn more about analytics and AI applications, my new ๐ โ๐๐ผ๐๐ป๐ฑ๐ฎ๐๐ถ๐ผ๐ป๐ ๐ผ๐ณ ๐๐๐๐ถ๐ป๐ฒ๐๐ ๐๐ป๐ฎ๐น๐๐๐ถ๐ฐ๐: ๐๐ป ๐๐ฝ๐ฝ๐น๐ถ๐ฒ๐ฑ ๐๐ฝ๐ฝ๐ฟ๐ผ๐ฎ๐ฐ๐ตโ is coming out at the end of May.
If you would like to discuss a specific embedded analytics or AI project, reach out to discuss your needs and how they can be supported by effective business architecture and analysis.
More resources:
Data Management & Analytics Fundamentals (course)
What is Embedded Analytics? Explained in 15 Minutes with Examples (video)
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