In this video, I share 3 data analyst skills that I think are most likely to become “high-risk” (or even obsolete) by 2030 because of AI. I wanted this to be practical and grounded in reality, so I didn’t just guess—I went job searching, pulled up a real sustainability data analyst job posting (not entry-level), went line by line, grouped responsibilities into themes, and then asked: do AI tools already exist that automate this? If yes, I labeled it high-risk; if the tool exists but still needs human guidance, it’s medium. Then I layered on my 11 years in data science to make the final predictions. The three areas I cover are: (1) basic reporting and dashboarding, because tools like Power BI Copilot, Tableau GPT, and Looker with Gemini can generate visuals, summarize insights, and explain trends; (2) cookie-cutter SQL/Python, because tools like Databricks Genie, BigQuery with Gemini, Snowflake Cortex, and ChatGPT Advanced Data Analysis can write/debug common queries and scripts; and (3) storytelling with data—especially the first draft—because tools can already generate summaries, decks, and reports from dashboards. My advice is simple: your edge is business understanding, critical thinking, analytical reasoning, and decision-making—plus AI literacy. The analysts who can validate AI outputs and commercialize insights clearly get promoted, not replaced.