The short answer
- On everyday writing tasks, randomised studies measure real gains: about 40% less time for work of equal or better quality.
- Those gains only hold for tasks inside what researchers call AI’s “frontier”. Outside it, quality drops, and that isn’t always obvious.
- The best personal uses: first drafts, summaries, weekly planning, turning messy notes into lists, logging an expense or a reminder in one sentence.
- Check every number, date, name, reference or advice you will act on. An AI assistant can make things up with total confidence.
- Don’t paste sensitive data (health details, ID numbers, passwords, work secrets) into a consumer chatbot.
What the controlled studies actually measure
Claims about AI productivity are everywhere. The most reliable numbers come from studies that compare people working with AI to similar people working without it, ideally assigned at random.
Professional writing. MIT economists Shakked Noy and Whitney Zhang gave occupation-specific writing tasks to 453 college-educated professionals, with half randomly given access to ChatGPT. In their 2023 paper in Science, average time fell by 40% and quality rose by 18%, as graded by experienced people from the same occupations.
Customer support. Erik Brynjolfsson, Danielle Li and Lindsey Raymond followed 5,172 support agents who received an AI assistant at different dates. In the Quarterly Journal of Economics (2025), issues resolved per hour rose by 15% on average and by about 30% for the least skilled and least experienced agents. For the most experienced, gains were small, with a slight dip in quality.
Consulting. Fabrizio Dell’Acqua and colleagues from Harvard, Wharton, MIT, Warwick and Boston Consulting Group ran a preregistered experiment with 758 BCG consultants on 18 realistic tasks. With GPT-4, consultants completed 12.2% more tasks, 25.1% faster, with more than 40% higher quality, according to the 2023 working paper.
The “jagged frontier”: where AI quietly costs you time
The same BCG study holds the most useful finding for your own day. Researchers also set one task chosen to sit outside what the AI could do well: a business problem where the right answer depended on spotting details buried in interview notes, not just the spreadsheet. Without AI, 84.5% of consultants got it right. With AI, only 60% to 70% did, an average drop of 19 percentage points. The authors call this a “jagged technological frontier”: two tasks that look equally hard can land on opposite sides of it.
Two more studies are worth knowing before you reorganise your week around a chatbot:
- Feeling faster is not the same as being faster. In a 2025 experiment by the research group METR, 16 experienced software developers worked through 246 real tasks with and without AI tools. With AI they took 19% longer. Afterwards, they still believed AI had sped them up by about 20%.
- Across a whole job, average gains are modest. Anders Humlum and Emilie Vestergaard surveyed about 25,000 workers in 11 AI-exposed occupations in Denmark. Chatbot users reported average time savings of 2.8% of their working hours (April 2025 version), with no measurable effect on earnings or hours.
These results don’t contradict each other. AI saves a lot of time on specific tasks and much less across a full day. Your job is to find the tasks that sit inside the frontier.
Six everyday uses that save real time
- First drafts. A note to your landlord, a reply to your child’s school, a listing to sell a bike. Give the context, tone and length. Editing a draft is much quicker than starting from a blank page.
- Summaries. Meeting notes, a lease, a long email thread. Ask for decisions, dates and next actions. Go back to the original for anything you’re agreeing to.
- Planning the week. “Here are my appointments and five tasks for the week; propose a schedule with buffers.” The AI proposes; you adjust to your real energy. Our time management guide covers the method, and our printable weekly planner gives you a page to fill in.
- Messy notes into clean lists. Talk through everything on your mind, then ask the AI to sort it into “to do”, “to buy” and “to call”. It’s the capture step from Getting Things Done, only faster.
- Breaking down a stuck task. For the form you keep putting off, ask for the first five 10-minute steps. Handy when you’re procrastinating.
- Logging an expense or a reminder in one sentence. This is where voice shines: you say it when it happens instead of trying to remember it at night.
I spent $38.60 on groceries at Trader Joe’s, and remind me to call the dentist Thursday at 9
Ready: a $38.60 expense in Groceries, paid today, and a reminder “Call the dentist” on Thursday at 9:00. Save them?
Nothing is saved until you confirm.
Try Binome360 for freeIn Binome360, the assistant prepares the expense or the reminder and waits for your confirmation. It’s a good rule with any AI tool: it proposes, you approve.
The real risk: trusting it too fast
A generative AI doesn’t “know” whether what it writes is true; it produces plausible text. Ask it for specific references and it may invent them. In a 2024 study in the Journal of Medical Internet Research, 28.6% of the references GPT-4 produced and 39.6% of GPT-3.5’s were hallucinated, meaning at least two of the title, first author and year were wrong. Models have improved since, but the mechanism hasn’t gone away. Our guide to the AI personal assistant explains why.
The second risk is subtler: we check less. A Microsoft Research survey of 319 knowledge workers (CHI 2025) found that higher confidence in AI went with less critical thinking, while higher confidence in one’s own skills went with more checking. It’s a self-report survey, not an experiment, but it fits the BCG result, where leaning on the AI outside its frontier led more consultants to the wrong answer.
- Numbers, dates, amounts: compare them with the source (bill, statement, email)
- Names, places, references: look them up yourself before reusing them
- Health, legal or money advice: treat it as a question to take to a professional
- Anything you send to someone: read it all the way through, out loud if it matters
Privacy: what never to paste in
The UK’s National Cyber Security Centre warned in 2023 that queries to a public chatbot are visible to the company running it and are likely to be stored. Its advice: don’t include sensitive information, and don’t ask anything that would cause problems if it were made public. In the US, the Federal Trade Commission reminded AI companies in January 2024 that they must keep their privacy promises, including promises not to use your data to train their models, and can’t quietly change their terms.
In practice, never paste into a consumer chatbot:
- full card numbers, bank details, passwords or one-time codes;
- your Social Security number, National Insurance number or passport details;
- identifiable medical information about you or someone else;
- confidential documents from your employer or your clients.
Before you adopt a tool, check three settings: can you delete your history, are your chats used for training, and can you opt out? If a company’s privacy policy doesn’t answer those questions clearly, treat that as your answer.
Measure your own gain in two weeks
Since the feeling of speed can mislead you, as METR found, measure it. The method fits on one sheet of paper:
- Pick three recurring tasks: say, replying to school emails, tracking spending and planning Sunday’s week ahead.
- In week one, do them without AI and note the time.
- In week two, do them with AI, checking included, and note the time.
- Keep AI only where the gain is real and the result is good enough.
Take Tom, a freelance designer in Manchester. Writing polite payment chasers took him 35 minutes a week. With an AI draft he then edits, it takes 15: 20 minutes saved. Reconciling his bank statement was different: checking the AI’s work took longer than doing it himself. He kept AI for the chasers and dropped it for the reconciliation.
Frequently asked questions
Does AI really make you more productive?
On specific tasks, yes: 40% less time on professional writing in Noy and Zhang’s 2023 experiment. Across a whole working day, average self-reported savings are small, 2.8% of work hours in a large 2025 Danish study. And on some tasks it makes you slower.
What should you not use AI for?
Anything where a mistake is costly and hard to spot: a medical decision, a contract, a tax return, an investment. Use AI to prepare your questions, then talk to a qualified professional.
Do I need a paid AI tool to be productive?
Not necessarily. Free versions are enough for drafting and summarising. A paid tool makes sense when it does one specific job you repeat, such as keeping your expenses and reminders in one place. Test for two weeks before committing.
Does using AI make you worse at thinking?
There is no long-term evidence of that yet. But research shows people check less when they trust the tool. Keep doing the first round of thinking yourself on anything that matters.
In short
AI saves real time on drafting, summarising, planning and quick logging, as long as you stay inside its frontier and check what you’ll act on. Your first step: pick one recurring task this week, time it with and without AI, and keep whatever actually works.
Sources
- Shakked Noy and Whitney Zhang, “Experimental evidence on the productivity effects of generative artificial intelligence”, Science, 381(6654), 187–192, 2023: doi.org/10.1126/science.adh2586.
- Erik Brynjolfsson, Danielle Li and Lindsey Raymond, “Generative AI at Work”, The Quarterly Journal of Economics, 140(2), 889–942, 2025: doi.org/10.1093/qje/qjae044.
- Fabrizio Dell’Acqua et al., “Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality”, Harvard Business School Working Paper 24-013, September 2023; published in Organization Science, 37(2), 403–423, 2026: doi.org/10.1287/orsc.2025.21838.
- Joel Becker, Nate Rush, Elizabeth Barnes and David Rein (METR), “Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity”, arXiv:2507.09089, July 2025: arxiv.org/abs/2507.09089.
- Anders Humlum and Emilie Vestergaard, “Large Language Models, Small Labor Market Effects”, Becker Friedman Institute Working Paper 2025-56, April 2025: bfi.uchicago.edu.
- Hao-Ping Lee et al., “The Impact of Generative AI on Critical Thinking: Self-Reported Reductions in Cognitive Effort and Confidence Effects From a Survey of Knowledge Workers”, CHI 2025: microsoft.com/en-us/research.
- Mikaël Chelli et al., “Hallucination Rates and Reference Accuracy of ChatGPT and Bard for Systematic Reviews: Comparative Analysis”, Journal of Medical Internet Research, 26, e53164, 2024: doi.org/10.2196/53164.
- National Cyber Security Centre (UK), “ChatGPT and large language models: what’s the risk?”, 14 March 2023: ncsc.gov.uk.
- Federal Trade Commission, Office of Technology, “AI Companies: Uphold Your Privacy and Confidentiality Commitments”, 9 January 2024: ftc.gov.
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