Business analysis has always been about 𝗵𝗲𝗹𝗽𝗶𝗻𝗴 𝗼𝘁𝗵𝗲𝗿𝘀 𝘀𝗼𝗹𝘃𝗲 𝘁𝗵𝗲𝗶𝗿 𝗽𝗿𝗼𝗯𝗹𝗲𝗺𝘀. Yes, in the “BA vs AI” 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?
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 let’s 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 📙 “𝗙𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻𝘀 𝗼𝗳 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀: 𝗔𝗻 𝗔𝗽𝗽𝗹𝗶𝗲𝗱 𝗔𝗽𝗽𝗿𝗼𝗮𝗰𝗵” 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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