AI tools are becoming more common in day-to-day work at Iowa. It’s reasonable to expect that they might save time. In practice, that isn’t always how it feels. Some tasks go faster. Others take just as long, only with more reviewing and cleanup.
The difference is usually about what kind of work AI is being asked to support, not how “skilled” someone is with AI.
Where AI tends to save time
AI is most helpful when it replaces “setup” work. By setup, we mean the part where you’re getting from a blank page to a workable first draft, outline, or structure.
Starting from a blank page is often the slowest part of a task, especially when you already know what the final result should look like. In those situations, AI can help you get to the draft stage more quickly, and then you still review for accuracy and revise tone, content, and details.
Common examples include drafting a first version of a familiar email, turning rough notes into a short outline, or creating a starter table or checklist you can adjust. In these cases, AI helps you begin, not decide.
Here’s a simple prompt pattern that tends to work well for “setup” work:
“Draft a first version of a [email/update/summary] for [audience]. Goal: [what you need it to do]. Keep it to [length]. Format it as [bullets/sections/table]. Include a short list of ‘questions to confirm’ if anything is unclear. Source notes: [paste notes].”
Where AI often doesn’t
AI is less helpful when accuracy is the main work. If a document needs exact names, dates, numbers, or formal wording, the time saved generating a draft can disappear during review. You still need to verify details against a trusted source.
For tasks like these, starting from an existing template or a prior example is often just as efficient, and sometimes faster. (A “prior example” can be a message you sent last semester, a past report, or an approved template your unit already uses.)
Structure matters more than content
AI works better when the shape of the output is clear. When you can describe what you need in one sentence, such as a three-paragraph update, a five-bullet recap, or a table with specific columns, the first draft is more likely to be useful.
When structure isn’t clear, AI fills in gaps with generic patterns. That’s when results tend to feel “almost right” and take longer to fix.
AI can help you think, but it won’t think for you
AI can be helpful for brainstorming, generating options, or acting like a thought partner. But it shouldn’t be the final decision-maker, especially when context, trade-offs, or accountability matter.
If you’re still deciding what you want to recommend, what matters most, or how to frame an issue, starting with AI can push you toward a polished answer too early. In those moments, a quick outline or a few notes often move thinking forward faster. Once the direction is clear, AI is more effective for drafting and organizing.
Reuse changes the payoff
AI delivers the most value when the result can be reused. Templates, standard emails, recurring reports, and common summaries are good examples. One-off tasks can still benefit, but the return is less predictable because the “setup” and review effort stays the same.
A simple way to decide
Before using AI, it can help to identify the task in one sentence:
- If you need a first draft, structure, or rewrite, AI may save time.
- If you need to verify facts, resolve ambiguity, or make a decision, AI may add work.
If AI hasn’t been saving you time, it often means the task isn’t a good fit yet, or the work needs clearer structure before AI can help.
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