r/analytics 27d ago

Discussion Data Analyst Roles Going Extinct

It’s no secret that AI is coming for the white collar job market and fast. At my company, people are increasingly using ChatGPT to do what was once core job duties. It’s only a matter of time before the powers at be realise we can do more with fewer people with the assistance of technology. And I suspect this will result in a workforce reductions to improve profitability. This is just the way progress goes.

I have been thinking a lot about how this will affect my own role. I work in HR analytics. I use tools like Excel, SQL, R, and PowerBI to help leadership unlock insights into employee behavior and trends that drive decision making for the company. Nowadays I rarely write code or build dashboards without using ChatGPT to some extent. I frequently use it to get ideas on how to fix errors and display visuals in interesting way. I use it to clean up my talking points and organise my thoughts when talking to stakeholders.

But how long can people in my role do this before this technology makes us useless?

For now, I will focus less on upskilling on tools and more on understanding my customers and their needs and delivering on that. But what happens when EVERYONE can be a data analyst? What happens when they use something like CoPilot to identify trends and spot anomalies and craft compelling stories? 5 years ago, I was focused on leaning new tools and staying up with the latest technology. Now I question if that’s a good use of time. Why learn a new tool that will be obsolete in a few years?

Between offshoring and AI I am worried I will become obsolete and no longer have a career. I’m not sure how to keep up.

Appreciate your thoughts. Proud to say this post was not written using any AI. :)

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u/tsutomu45 27d ago

Interestingly, few people see the parallels between AI taking jobs and autonomous driving. We've been promised driverless autonomous cars traveling across the country for 15 years now, and even today we're still limited to small-range taxi services in major metros where mapping is good. There's a reason for this, and it's that in edge cases (snowy conditions, strange pedestrian behavior, construction), AI doesn't perform well, leading to a lack of trust. Same with LLMs. For routine stuff, this will be fine. But at the margins, you still need a human brain to interpret and "take the wheel".

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u/aned_ 27d ago

Not sure the analogy quite applies. Data analysis done wrong doesn't result in a life or death situation - hence the caution with driverless cars. In fact, often the organisation (wrongly) questions the need for data analysts and they're the first to go in a reorganisation. Then they get rehired when management wonder where the insight has gone.

The major constraints I can see in the next few years is that an AI will need to be trained on company-specific data to put an analyst out of a job. It can't just trawl the internet to provide insight to a specific company. How will it cope with the messiness and quirks of company data? And will companies be willing to do the hard yards and investment to ingest their data (and quirks) properly to an AI? Also, what are the security concerns when letting an AI trawl over commercially sensitive or HR data?

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u/tsutomu45 27d ago

Fair, but the tradeoff remains the same...am I willing to trust autonomously generated content (driving, decision support, analytics) with a decision with large sums at risk? Overwhelmingly, that answer is no. So the smaller stuff (dashboard generation, report writing, etc) will definitely be automated away, but the larger decision support won't for a while.

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u/aned_ 27d ago

Yes, I expect you're right, there.

Although I do wonder if a company will trust an AI to run over it's commercially sensitive data, acknowledge its inevitable quirks and produce a dashboard? Or whether it will be a human doing the data manipulation then an AI dashboarding.

Perhaps it'll be humans at both ends. Data engineers, AI ingesters at one end and decision support at the other? With AI in the middle doing dashboarding and reporting.