AI tools can now write SQL, build a chart from a spreadsheet and summarize a dataset in plain English. For data analysts, that raises an obvious worry: if anyone can ask a chatbot for the numbers, who needs an analyst? The evidence points to high task exposure but strong demand, and a job moving from producing numbers toward framing questions and checking answers.
The short answer: AI is changing data analysis a lot, but today's data does not point to the role disappearing. The ILO's 2025 index places statistical and mathematical associate professionals, and statisticians, in its significant-exposure band. US projections expect data scientist and operations research analyst jobs to grow much faster than average, with AI adoption itself named as a source of demand. Routine reporting is moving to AI; judgment about what the data means stays with people. No projection is certain.
How exposed data and analysis jobs are
How to read the table: the mean task score runs from 0 to 1, and the band is the ILO's grouping, from not exposed through minimal exposure to gradient 4, the highest (ILO Working Paper 140, 2025). More on the method in will AI take my job?
| Occupation (ISCO-08) | ILO category | Mean task score (0 to 1) |
|---|---|---|
| Statistical, Mathematical and Related Associate Professionals | Gradient 3 | 0.57 |
| Database Designers and Administrators | Gradient 3 | 0.57 |
| Mathematicians, Actuaries and Statisticians | Gradient 3 | 0.56 |
| Systems Analysts | Gradient 2 | 0.49 |
| Management and Organization Analysts | Gradient 2 | 0.46 |
| Financial Analysts | Gradient 4 (highest) | 0.62 |
| Data Entry Clerks | Gradient 4 (highest) | 0.70 |
Analyst roles sit mostly in gradient 3: many tasks exposed, but not all. Data entry, the job of getting numbers into systems, is far more exposed than analysis, the job of deciding what they mean.
What the BLS projects
The BLS does not have a separate "data analyst" category; the closest groups are data scientists and operations research analysts. It projects employment of data scientists to grow 35 percent from 2025 to 2035, with about 24,800 openings a year, citing the growing volume of data and that firms are expected to continue to integrate AI-based systems into their workflows (BLS, data scientists). It projects operations research analysts to grow 12 percent, with about 7,500 openings a year (BLS, operations research analysts).
The World Economic Forum lists big data specialists among the fastest-growing jobs, names analytical thinking the most sought-after core skill, and puts AI and big data at the top of fastest-growing skills (WEF Future of Jobs Report 2025). Entry-level reporting roles may still feel pressure even while the field grows.
Tasks moving to AI
- Writing and fixing SQL queries and spreadsheet formulas.
- Cleaning and reshaping data.
- Producing standard charts and dashboard drafts.
- Summarizing results in plain language.
- Answering routine "what were the numbers last month" questions.
What stays with the analyst
- Framing the question: turning a vague business ask into something the data can actually answer.
- Knowing the data: where it comes from, what is missing, and which definitions differ between teams.
- Checking the result: Generative AI can state wrong things fluently; NIST names this risk confabulation (NIST AI 600-1). A plausible chart built on a wrong join is still wrong. See checking AI output.
- Causation and context: telling correlation from cause, and knowing what else changed.
- Recommendations people trust: explaining findings, their limits and what to do next.
- Data care: deciding what data an AI tool may see. See AI agents and personal data.
What this means for the job
For many analysts, AI is becoming a fast assistant for queries and first drafts, and the job shifts toward being the person who decides what to ask, checks what comes back and owns the conclusion. Analysts are also often asked to measure AI tools themselves; see measuring AI agent performance. The work under most pressure is repetitive reporting that nobody questions.
See also will AI take my job?, will AI replace software engineers? and digital collar skills.
Pay and how to get in
The US Bureau of Labor Statistics puts the median annual pay for data scientists at $120,230 in May 2025, against $50,980 for all workers. Across the 2 BLS occupations this page covers, median pay ranges from $88,940 to $120,230. The typical education needed to enter is: bachelor's degree. See how this job compares in AI exposure by pay and AI exposure by education level.
Questions and answers
Will AI replace data analysts?
Not on current evidence. The BLS projects 35 percent growth for US data scientists and 12 percent for operations research analysts from 2025 to 2035. Routine reporting is shifting to AI.
How exposed are data analysts to AI?
The ILO places statistical and mathematical associate professionals and statisticians in gradient 3, significant exposure, with mean task scores of 0.57 and 0.56.
Will AI replace data scientists?
US projections expect strong growth, partly because firms are integrating AI-based systems into their work, which creates more data work rather than less.
What data analysis work can AI not do?
Framing the right question, knowing the data and its gaps, checking results, separating correlation from cause and making recommendations people trust.
Is data analytics still a good career?
Demand is projected to grow, and the WEF names analytical thinking the most sought-after core skill. Skills in checking AI output and explaining results are increasingly important.