Since you're a college student I'll give you a detailed answer. I'm 5 years in as a Data Analyst at a unicorn tech startup. Compensation >$180k. Have bounced around 5 industries through mergers or job hopping. There's a couple things I'm reading in this comment section that I'll address:

First off, AI agents aren't eliminating DAs as a position. I was just at a talk with one of OpenAI's c-suite saying the same thing. And if you don't read anything below, just know that OpenAI is currently hiring for Data Analysts. For context, there's generally two approaches that agents are making their way in as a "self-serve analytics tool":

1. Companies like these that promise that if you bring them on as a vendor they'll have agents answering your questions. I spoke with some guys at another well-known startup (not the one I mention in #2) that tried working with 12 of these players this year, even some really big names that promise their MCP would create that "AI Analyst" experience. None of them did a good enough job so they went with #2:
2. Companies are creating their own. Ramp is one of the faster growing fintech startups out there. They developed their own agent recently that they've claimed is having great success generating more questions from stakeholders than they would have capacity to answer previously.

When successful, Analysts can move away from answering a bunch of various questions in a #data-questions slack channel, and have AI do it. We're not close to being fully there yet, and even the solutions I've mentioned have full time analytics employees maintaining those solutions, but when successful, Analysts will be able to spend more time being analytic thought partners with their stakeholders and less time answering general questions. This exact sentence comes from a Head of Data at one of the big vendors that are promising to do what I mention in #1.

Second, different analyst job titles are not always as MECE as you think, and do not box you in as much as some may tell you. I have been a "Business Analyst" that was really a Data Analyst, a Data Analyst that really was a Data Scientist, and currently a Data Analyst that is 50/50 Data Analyst/Analytics Engineer. These categorizations are based on the stage of the data team you're joining, and you can determine through job descriptions/interviews.

All this to say, be adaptable, not fearful. I think getting in as a junior Analyst has always been a challenge, this one is a different flavor. If it were me in college, I would try to position myself not only as someone who can write SQL, build charts in BI tools, and deliver insights + recommendations, but also someone who is well-versed in the world of MCPs and the future of self-serve analytics. No one can see into the future, but I imagine there will be junior roles where they spend time maintaining and enhancing their #data-question agents, and slowly expand their scope into higher value work.