If you’re a BI analyst in 2025, you’re living in a weird, wonderful in-between: half data plumber, half storyteller, and increasingly the person who turns chaos into something leadership can actually use. The surprise for me hasn’t been that AI can do impressive tricks. It’s that it can take the low-glamour parts of the job (rewriting the same explanation, checking logic, naming things consistently, turning a fuzzy thought into a clean outline) and do them fast enough that my brain stops feeling stuck in the mud.
When it’s working, it feels less like replacement and more like symbiosis. I’m still the one who knows the context, the people, the risk, and the “why.” The machine is the tireless assistant: it drafts, refines, tests, and reorganizes, so I can spend my human energy on judgment. That extra headroom is where the creative spirit lives. Not just art-creative, but clarity-creative: the ability to frame the right question, tell the truth cleanly, and build something that helps someone make a better decision.
I still have hesitation, though, especially about the business side of AI. Data centers are real buildings with real energy and water needs, and the costs don’t always show up where they should. If AI is going to behave like a modern utility, I want the “citizen utility” part to be honest: less hidden subsidization, less environmental hand-waving, and more accountability for what we’re building and who it serves.
At the same time, I don’t think this pattern is new. Big technologies often start inefficient, then become smarter and more energy-efficient as innovation catches up. The industrial revolution, electrification, computing, the internet: messy first, optimized later. So I’m choosing a two-handed posture: optimism about the tool, skepticism about the incentives. My personal rule is simple: keep the human in the loop, use AI to amplify taste and clarity, and never outsource responsibility.