Will AI be the end of Data Analysts?

It’s the same story almost every single time and in every single situation.

You prepare for a board meeting, and you get your Data Analyst or data team to prepare the data. It’s all made to look lovely and presented in a PowerPoint or “slide deck.”

The data is scrutinized. Umm's and ahh's are exchanged. Then, out of the blue, a question is asked that wasn’t in your pretty PowerPoint. Nor was it even thought about.

At this point, you’re scrambling. “Don’t worry, we’ll get back to you on that one!” you answer. It’s a very familiar situation.

Now, there is a solution, and it lies in AI. Yawn, yes, I know. However, this isn’t a fad. Imagine an AI assistant at your fingertips, instantly pulling insights, answering your questions in real-time, and sparing you the need to “circle back.”

Does that mean data analysts are out of a job? Not exactly. AI, and more specifically AI Data Analysis, as we’re calling them, will change the role, but it won’t eliminate it. On the contrary, this new evolution will allow data teams to spend less time on data moving, cleansing, and answering basic questions and more on interpreting insights.

Let’s talk about the future of data analytics.

The death of the traditional analyst?

Right now, most data analysts spend 80% of their time wrangling data—moving it between systems, cleaning it up, and making sure it’s in the right shape before they even get to do the real meaningful stuff: the actual analysis. This isn’t what people imagine when they think of a “data-driven” role, yet it’s the reality.

This is where AI Data Analysts come in. These AI-driven systems can automate a huge chunk of that boring grunt work, making it possible for users at any technical skill level to ask an array of questions, from simple to complex, and get answers instantly.

Instead of spending a huge amount of time and effort questioning data, you can get precise, contextualized insights, all with visualizations.

However, this doesn’t mean that Data Analysts will be out of a job. Company data still needs to be managed and held by an individual(s) so they can have their hands around it and keep it in check. Yes, AI Data Analysis will help remove mundane everyday tasks, which will inherently mean they will get fewer data requests. However, this means that the 80/20 can be flipped, and analysts can spend 80% of their time analyzing, delving into trends, and making a difference and 20% on data wrangling.

So, what’s the catch?

AI Data Analysts aren’t perfect. They can suffer from “confabulation”—essentially, making up an answer that sounds convincing but isn’t quite right. But, us humans do the same thing. Decisions are often made based on gut instinct or assumptions rather than waiting weeks for an analyst to get back to you with a report. If AI Data Analysts can provide answers that are 80% accurate, that can already be a huge improvement in data-based decisions being currently made in a lot of organizations.

Secondly, there’s the security issue. Giving more people access to company data sounds great in theory, but it also raises questions about governance. If someone misinterprets the data or shares something sensitive with the wrong audience, it could be disastrous. That’s why adopting an AI Data Analyst isn’t just a technical challenge—it’s an organizational one.

Panintelligence’s AI functionality is grounded in security. As mentioned, there is a risk is unauthorized employees seeing data they shouldn’t, let’s say, salaries. Panintelligence is set up so that permissions are set on an organizational, departmental, and employee level, so users can only see the data they have access to. This is how AI data analysts should work going forward.

Looking forward: AI and humans working together

The role of a Data Analyst will evolve from data wrangler to strategic advisor, focusing on interpreting insights, ensuring data quality, and solving complex problems AI can’t handle.

AI will allow organizations to become more agile, making decisions in real time rather than waiting weeks for reports. Employees at all levels will feel empowered to explore data, leading to a more innovative and risk-taking environment.

Final thoughts

Will AI replace Data Analysts? No, but they will remove the tedious, manual parts of the job, which most analysts would probably argue isn’t enjoyable.

Instead, they’ll push analysts to evolve, focusing on higher-value work.

Share your thoughts

What's your opinion?

Do you think AI is taking over the Data Analyst role? Do you think the role will become redundant?

I would love to know what you think.