In this monologue, Kedeisha Bryan critiques the growing reliance on AI for data analysis, arguing that it is fostering a generation of analysts who lack essential foundational skills. She references a Reddit thread describing analysts who cannot distinguish average from median and interns who generate SQL queries via AI without understanding them, highlighting how leadership’s AI hype prevents escalation of these issues. Bryan warns that unchecked AI-generated work can hide errors until they cause major failures, potentially leading to catastrophic financial damage. She contends that the data analyst job market suffers from a quality gap, not oversaturation, and that many self‑identified analysts are unqualified. The speaker urges viewers to develop core competencies—critical thinking, quality assurance, problem‑solving, and a solid grasp of statistical concepts and SQL joins—to validate AI outputs and become the valuable analysts that organizations need once the AI hype subsides.
Chapters
I just found a Reddit thread and I need you to see this because this is exactly what I have been warning about. So the original poster is basically saying that they have analysts on their team who don't know the difference between average and median and are working with the databases and doing analysis on their team. He further states one wrong join and you're getting a completely different number. And the worst part is he's not even sure who to complain to. So let's sit with that for a moment. These are the people getting paid as data analysts at a real company, Making real decisions with real data, and they cannot tell you the difference between an average and a median. Not a junior thing, and this is a learning curve thing. This is a foundation thing, and you cannot do this job without that. But then someone replied, and it gets better or worse, depending how you look at it. They said, hey, I'm facing the same issue. My intern is using AI for everything, even for the simplest queries. I cannot rely on that person for any task. But I can't even escalate it to anyone because leadership is all about hyping AI in all the meetings. So they have an intern that's winging every query with AI, leadership celebrating AI in every all-hands, and the one person in the room who actually sees a problem can't even say a word about it. Politics. You had one job, validate the data. One job. So let's talk about what's actually happening here, right? This is not just some one-off thing. This is not just a bad intern story. This is a pattern that is spreading across every organization right now. Companies are drunk off of AI. They are hiring people who look amazing on paper because they can generate a SQL query with a prompt. And no one is checking if those people actually understand the query that they did or why the numbers make sense. And someone in a comment on this thread said it plainly, a lot of fires are going to happen at companies before we figure out how to put the right guardrails in every situation. They are right. And I'm actually going to take it a step further. At some point, some rogue AI agent is probably going to do something so financially catastrophic at an organization where they simply cannot recover from it. Then and only then will we all actually learn when the damage is already done. If you think about it, imagine handing every first grader a calculator before they ever learn multiplication tables. Before they had to learn how to do all the math by hand and flip to the back of the composition notebook so they can use the multiplication tables. You just skipped the entire process that teaches the brain how to actually think through a problem. That is basically what is happening now with AI and data analytics and pretty much every single industry right now. People are getting the calculator before they even know how to do math by hand. And the scary part is they don't even know they can't do math. AI is only as smart as the person using it. And if you don't understand What a join is, or the difference between a median or average, the AI writing for you is not going to fix that. It just hides it until something breaks at the worst possible moment. I have said this for years, that the competition in the data analyst job market, it's not a quantity problem. It is a quality problem. And people always want to push back on that. They always want to say, oh, Kedeisha is being too mean. She's demotivating the community. I am not. I am just giving you the facts, you guys. They say the market is saturated, too many applicants, but not enough jobs. But if you look at this thread, and there's many more of them, the real analyst in this story cannot find a single person on their team that they can even depend on. So does that sound like saturation? No, this is a vacuum. There is a massive gap between people who call themselves data analysts and people who can actually do the work. Listen, there's a lot of fakes out there and phonies. They're not your competition. They are just noise. And noise gets removed the second a stakeholder asks a real question and they have no idea what they're talking about when they answer it. Now here's what I want you to take from this. Be the person in that thread who actually knows what they're doing. Not the one that's just generating stuff with AI that they cannot explain what's actually happening under the hood. Not the one who cannot tell you whether a median or the average is the right measure for the situation. Not the one whose analysis falls apart the moment someone actually digs in. Know what a join is and why it changes your numbers. Understand when something just doesn't look right. Build the critical thinking first. Quality assurance, problem solving, and knowing how to connect the dots is going to be the biggest differentiator in this AI job market. Very often does the numerical data and the anecdotal data not match up, and the AI is not going to be able to figure it out. You have to. That is a thing that will be standing when the AI hype settles and organizations start asking why their dashboards and report has been lying to them. So now you know which analyst you need to be. Go be that one. Again, the data analyst job market is not oversaturated. It never has been. It is oversaturated by unqualified people who are just not ready yet. And unfortunately, many don't even realize it yet. And that is the biggest opportunity for anyone watching this right now.
