another post about

"chatgpt changed my analysis workflow."

another screenshot of claude writing complicated sql. and you're sitting there with your 6 years of experience wondering if your tableau dashboards just became worthless.

let me tell you something.

using chatgpt to clean data doesn't make you ai ready. asking claude to write your sql queries doesn't either.

everyone thinks that

being an analyst in the ai age means learning more tools. cursor for sql. julius ai for visualization. claude for analysis.

wrong. it means understanding 3 things.

1/ which problems actually matter in an ai world.

2/ which metrics make sense for probabilistic systems.

3/ which insights drive decisions when the ground truth keeps shifting.

tools are commodity.

your judgment about what to measure isn't.

you're a bridge builder. business has questions about ai systems. data has answers hidden in token logs and confidence scores.

you build the bridge between "why is our chatbot weird today?" and "the model's perplexity increased 23% after yesterday's update."

the core equation every analyst should know

<aside>

**value =

uncertainty quantified × decisions enabled × risk mitigated × trust built**

</aside>

let's break this down:

uncertainty quantified =

probabilistic thinking × confidence intervals × distribution analysis

measuring not just what happened,

but how confident we are it happened

understanding when 95% accuracy

means 5% catastrophic failure

decisions enabled =

speed to insight × actionability × stakeholder alignment

from "the model is behaving strangely" to "increase temperature parameter by 0.2"

connecting model behavior to business outcomes

risk mitigated =

early detection × impact assessment × prevention mechanisms

catching distribution drift before customers notice

quantifying the cost of hallucinations in rupees, not percentages