What do you actually use AI for in your everyday life or work — and where does it genuinely save…

AI tends to save real time when the task has clear inputs and outputs and the result is cheap to review: summarising, drafting variants, extracting structured data, triaging messages, searching a bounded knowledge base, or generating code that can be tested.

There is some field evidence, but it is not a universal “AI makes everyone 10× faster” result. In a study of 5,179 customer-support agents, access to an AI assistant increased issues resolved per hour by about 14% on average, with the largest gains among less-experienced workers. See Generative AI at Work. That result came from one specific workflow, so it should not be treated as a guarantee for writing, research, or software development.

My test is end-to-end: does the task take less time after verification, correction, and context setup? If the generated text needs so much checking that the review costs more than the drafting saved, AI has not helped. The best use cases are repetitive but not fully automatic: let the model produce a first pass, then keep a human or deterministic test as the acceptance step.

I would measure minutes to an accepted result, not minutes to the first plausible-looking answer.