10 Ways to Use AI to Be More Productive at Work

Most "AI Productivity" Advice Is Useless

You've seen the listicles. "Use AI to 10x your output!" They're usually written by people who spent more time on the headline than actually using the tools. Let me share what's worked for me after a year of daily AI use at work.

These aren't theoretical. I've tested each of these in real work situations, tracked how much time they actually saved, and dropped the ones that didn't deliver. Here are the 10 that stuck.

1. Draft First, Think Second

The blank page is a productivity killer. Instead of staring at an empty document, dump your rough thoughts into an AI chat and ask it to organize them into a first draft. You'll spend your mental energy editing and refining, not trying to get started.

This works for reports, proposals, project briefs, and even Slack messages you've been putting off. The key is giving the AI enough context about your audience and goal. A prompt like "write a project update for my manager covering these three points" beats "write a project update" every time.

2. Summarize Before You Read

I paste long documents, email threads, and meeting transcripts into AI and ask for a summary with action items. This takes a 30-minute read and turns it into a 3-minute scan. If something in the summary needs more attention, I go back to the source.

Pro tip: ask the AI to flag anything that requires a decision or response from you specifically. That way you don't miss the parts that actually matter.

3. Use AI as a Rubber Duck

Developers know the rubber duck debugging technique: explain your problem out loud and you'll often find the answer. AI is a rubber duck that talks back. When you're stuck on a problem, explain it to an AI model and ask what you might be missing.

This works for more than code. I've used it for marketing strategy, hiring decisions, and figuring out why a project was stalled. The AI doesn't always give the right answer, but the act of explaining your problem clearly often gets you unstuck.

4. Build Templates, Not One-Offs

Stop asking AI to write individual emails. Instead, use it to build reusable templates with variables you fill in later. Create a template for client proposals, status updates, meeting agendas, and feedback requests. Then use the templates repeatedly with minor tweaks.

I have about 15 templates I created with AI that I use every week. Each one took 10 minutes to build but saves me 5 minutes every time I use it. The math works out quickly.

5. Data Analysis Without Spreadsheet Gymnastics

Paste a data table into an AI chat and ask questions in plain English. "What's the trend in Q1 vs Q2?" or "Which product category grew fastest?" You'll get answers in seconds instead of building pivot tables and formulas.

This doesn't replace proper data analysis for big decisions, but for quick checks and exploratory questions, it's dramatically faster. I use this daily when reviewing sales numbers and marketing metrics.

6. Compare Models for Important Tasks

Different AI models are better at different things. GPT-5 tends to write more naturally. Claude is stronger at analysis and nuance. Gemini handles multimodal tasks well. For anything important, run it through two or three models and pick the best output.

This sounds time-consuming, but tools like Admix let you access 350+ AI models from one interface. Send the same prompt to multiple models and compare results side by side. It takes an extra minute and the quality difference is often significant.

7. Automate Your Meeting Prep

Before any meeting, I paste the agenda and any relevant context into AI and ask: "What questions should I prepare for? What data should I bring? What decisions need to be made?" This 2-minute exercise has saved me from being caught off-guard dozens of times.

For recurring meetings, I feed in notes from the last few sessions and ask the AI to identify patterns and unresolved items. It's like having a meeting assistant that actually pays attention.

8. Learn New Tools Faster

Instead of watching a 45-minute YouTube tutorial, ask AI to explain a new tool's key features and give you a quickstart guide. Then ask follow-up questions as you go. It's like having a patient coworker who knows every software tool ever made.

I recently learned a new project management tool this way in about 20 minutes. The equivalent video course was 3 hours long.

9. Code Review and Bug Hunting

Even if you're not a developer, you might write scripts, formulas, or automation workflows. Paste your code or formula into AI and ask it to check for errors, suggest improvements, or explain what it does. This catches bugs before they cause problems.

For actual developers, AI code review is already a standard practice. But non-technical people writing Excel formulas, Zapier workflows, or SQL queries can benefit just as much.

10. End-of-Day Brain Dump

At the end of each workday, spend 3 minutes dumping everything in your head into an AI chat. What happened today, what's still pending, what you're worried about. Then ask the AI to organize it into tomorrow's priority list.

This does two things: it clears your head so you can actually stop thinking about work, and it gives you a ready-made plan for the morning. I've been doing this for six months and it's probably the highest-impact habit on this list.

The Real Productivity Gain

None of these tips will "10x your output." That's hype. But each one saves 5-15 minutes a day. Stack a few of them together and you're getting back an hour or more daily. That adds up to over 250 hours a year.

The biggest mistake people make with AI productivity is trying to automate everything at once. Pick two or three of these, use them consistently for a week, and see which ones actually fit your workflow. Then add more gradually.

If you want to try multiple AI models to find which works best for each task, Admix gives you access to 350+ AI models starting at $10/month (or $8/month billed annually), which is cheaper than any single AI subscription.