232: Why AI Hasn’t Replaced Data Analysts (According to an ex-Google Data Analyst)
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Watched an ex-Google analyst break down why AI hasn’t replaced data analysts. I show you where I agree and where I don’t.
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⌚ TIMESTAMPS
00:00 – AI didn’t kill the job
02:45 – Big Tech isn’t the real market
09:15 – The hype doesn’t match the data
16:45 – Where AI guessed wrong
19:03 – The analysts at risk
20:27 – What makes you irreplaceable
📺 Watch Sundas’ original video 👉 https://youtu.be/r4lEzAM3VOY
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Transcript
Avery Smith's screen-4: Than about your business.
Speaker:And the truth is that at any given company, the context is actually spread
Speaker:across a dashboard, documentation, code, Slack, conversations, and the memories.
Speaker:What is it called?
Speaker:There is a term for it.
Speaker:Tribal knowledge.
Speaker:Yes, years of tribal knowledge that lives in people's head.
Speaker:Buying an AI tool does not fix that foundation.
Speaker:And if your company has recently adopted AI to do data analysis
Speaker:work, let me know how that is going.
Speaker:The second reason why AI has r- failed to replace data analyst is human judgment.
Speaker:Yes, AI can produce an explanation that sounds reasonable.
Speaker:You still need to know whether it makes sense.
Speaker:Simple as that.
Speaker:I once used AI to understand why clicks from Google search had dropped, right?
Speaker:Simple question.
Speaker:The AI actually suggested failing search demand, uh, because of a
Speaker:ranking change, broken tracking and whatnot, and mix of queries.
Speaker:Like, that was a mumbo jumbo thing, but that was actually
Speaker:not the right explanation.
Speaker:All of those theoretically made sense, but somebody like me who actually
Speaker:had the business context, I actually knew the real cause why the traffic
Speaker:went down was because Google ended something called continuous scroll.
Speaker:So instead of, like, continuous scrolling through the search page,
Speaker:you actually had now page numbers.
Speaker:So a user had to specifically click on the next page to land on
Speaker:basically the next search results.
Speaker:And when you add more clicks, you actually, uh, increase user fatigue,
Speaker:and people are less likely to do it, and that was the cause of the traffic
Speaker:drop, which AI was not able to catch.
Speaker:This is an exam-
Speaker:Example of business context and human judgment.
Speaker:In the real world, you actually needed to have the business context.
Speaker:You needed to have the history, product history, and have to know
Speaker:Interface itself to basically figure out why traffic was down.
Speaker:So now you must be wondering which data analyst should
Speaker:actually be worried about AI.
Speaker:Let me just be very transparent.
Speaker:If your value comes from pulling a number after someone else has defined the
Speaker:question, you're just writing basic SQL, a refreshing dashboard, and summarizing
Speaker:changes, that work is becoming easier with AI and more likely to get automated.
Speaker:The more-
Speaker:A durable analyst defines the metric, challenges the request, understands the
Speaker:domain, validates the output, and connects the analy- analysis to a decision.
Speaker:Remember decision?
Speaker:We actually haven't talked about that.
Speaker:Let me know if I should cover that in a different video.
Speaker:This could be a product analyst who understands user behavior, a growth
Speaker:analyst who understands acquisitions and retention, or an analytics
Speaker:engineer who builds foundation AI needs
Speaker:Or a data analyst who actually is focused on defining business
Speaker:problem and decision-making.
Speaker:The common thread in all of these role is ownership, context, and judgment
Speaker:The role is
Speaker:Ownership, context, and judgment.
Speaker:So has AI replacing data analyst officially failed?
Speaker:I'm happy to share that it has failed to eliminate the role.
Speaker:It has succeeded at changing it, but it has not replaced it
Speaker:And this is true for majority of the tech roles.
Speaker:The pro-
Speaker:Coding only version of the job is, yes, under pressure, but the analyst who
Speaker:understands the business, use AI well, and knows when to answer is wrong, answer
Speaker:is wrong, is becoming more important.
Speaker:If you work in data analytics field, let me know what has been your experience.
Speaker:Do you agree with this?
Speaker:Do you think AI has failed to replace a data analyst, or we're not there yet?
Speaker:Let me know in comments.
Speaker:With that, I hope you're having a beautiful day.
Speaker:I'll see you in the next video.
Speaker:Have a good one.
Speaker:Bye.
Speaker:Than about your business.
Speaker:And the truth is that at any given company, the context is actually spread
Speaker:across a dashboard, documentation, code, Slack, conversations, and the memories.
Speaker:What is it called?
Speaker:There is a term for it.
Speaker:Tribal knowledge.
Speaker:Yes, years of tribal knowledge that lives in people's head.
Speaker:Buying an AI tool does not fix that foundation.
Speaker:And if your company has recently adopted AI to do data analysis
Speaker:work, let me know how that is going.
Speaker:The second reason why AI has r- failed to replace data analyst is human judgment.
Speaker:Yes, AI can produce an explanation that sounds reasonable.
Speaker:You still need to know whether it makes sense.
Speaker:Simple as that.
Speaker:I once used AI to understand why clicks from Google search had dropped, right?
Speaker:Simple question.
Speaker:The AI actually suggested failing search demand, uh, because of a
Speaker:ranking change, broken tracking and whatnot, and mix of queries.
Speaker:Like, that was a mumbo jumbo thing, but that was actually
Speaker:not the right explanation.
Speaker:All of those theoretically made sense, but somebody like me who actually
Speaker:had the business context, I actually knew the real cause why the traffic
Speaker:went down was because Google ended something called continuous scroll.
Speaker:So instead of, like, continuous scrolling through the search page,
Speaker:you actually had now page numbers.
Speaker:So a user had to specifically click on the next page to land on
Speaker:basically the next search results.
Speaker:And when you add more clicks, you actually, uh, increase user fatigue,
Speaker:and people are less likely to do it, and that was the cause of the traffic
Speaker:drop, which AI was not able to catch.
Speaker:This is an exam-
Speaker:Example of business context and human judgment.
Speaker:In the real world, you actually needed to have the business context.
Speaker:You needed to have the history, product history, and have to know
Speaker:Interface itself to basically figure out why traffic was down.
Speaker:So now you must be wondering which data analyst should
Speaker:actually be worried about AI.
Speaker:Let me just be very transparent.
Speaker:If your value comes from pulling a number after someone else has defined the
Speaker:question, you're just writing basic SQL, a refreshing dashboard, and summarizing
Speaker:changes, that work is becoming easier with AI and more likely to get automated.
Speaker:The more-
Speaker:A durable analyst defines the metric, challenges the request, understands the
Speaker:domain, validates the output, and connects the analy- analysis to a decision.
Speaker:Remember decision?
Speaker:We actually haven't talked about that.
Speaker:Let me know if I should cover that in a different video.
Speaker:This could be a product analyst who understands user behavior, a growth
Speaker:analyst who understands acquisitions and retention, or an analytics
Speaker:engineer who builds foundation AI needs
Speaker:Or a data analyst who actually is focused on defining business
Speaker:problem and decision-making.
Speaker:The common thread in all of these role is ownership, context, and judgment
Speaker:The role is
Speaker:Ownership, context, and judgment.
Speaker:So has AI replacing data analyst officially failed?
Speaker:I'm happy to share that it has failed to eliminate the role.
Speaker:It has succeeded at changing it, but it has not replaced it
Speaker:And this is true for majority of the tech roles.
Speaker:The pro-
Speaker:Coding only version of the job is, yes, under pressure, but the analyst who
Speaker:understands the business, use AI well, and knows when to answer is wrong, answer
Speaker:is wrong, is becoming more important.
Speaker:If you work in data analytics field, let me know what has been your experience.
Speaker:Do you agree with this?
Speaker:Do you think AI has failed to replace a data analyst, or we're not there yet?
Speaker:Let me know in comments.
Speaker:With that, I hope you're having a beautiful day.
Speaker:I'll see you in the next video.
Speaker:Have a good one.
Speaker:Bye.
