intelligence can draft a memo or summarize a meeting instantly. Deciding which memo matters, whether that summary is accurate, or what to do next still requires human knowledge.
That’s the premise of 
Personal Productivity in an AI-Enabled Workplace
In person at MIT Sloan
Focus AI-assisted research on your final product
Before asking AI to gather copious information and then asking questions, do the cognitive work of identifying the questions you need to answer, and then use AI to help get the answers quickly.
“Right now, the problem isn’t getting enough data. The problem is that you can overwhelm yourself with data on almost any subject,” Pozen said.
Pozen recommends “starting at the end”: developing tentative conclusions after a few rounds of targeted research, and revising them as new evidence emerges. For a three-month project, he suggests reassessing those conclusions every two weeks. This approach surfaces the hardest analytical questions early and suggests a direction for further research.
Fry pairs this approach with AI research exercises, keeping the emphasis on evaluating evidence and refining conclusions as the work progresses. Class participants work through case studies, using AI tools such as Perplexity and Claude to gather and approaches to any task:
- Keep it: If the task is high stakes and rarely repeated, you should do it yourself.
- Systematize it with review: If the task is low stakes and often repeated, you can set up a standing prompt or template and check the output each time.
- Use AI for a quick assist: This is usually best for one-off, low-stakes tasks where you can let AI draft your response and move on.
- Automate it: This is best for routine, low-risk tasks that can be easily handed off.
Even when AI does assist, the work isn’t finished, the instructors agree. Pozen’s “last 30%” principle describes AI as getting work to 70%, with human judgment needed to complete the rest. Employees remain responsible for checking the results and protecting data, including AI-assisted work received from others.
“Today, workers need to get hands-on, daily practice with AI tools, build the habit of verifying before relying on AI results, and protect confidential data with the right guardrails,” Fry said.
Like Pozen, Fry emphasizes preserving independent judgment as AI accelerates productivity. Workers still need to set priorities, evaluate AI outputs, and persuade others. Those are skills that AI cannot fully replicate.
(To that end, MIT Sloan senior lecturer Ben Shields joins the class to offer exercises on presenting and impromptu speaking that are aimed at helping students organize their ideas, tailor their messaging, speak persuasively, and respond confidently on the spot.)
“AI is collapsing the time it takes to produce the first draft of almost any knowledge work. That moves a professional’s value toward what the tool can’t do: setting priorities, judging whether the output is right, and persuading people,” Fry said.
That’s why the course offers strategic approaches to increasing personal productivity combined with selected AI tools to implement these strategies.
Robert Pozenis a distinguished senior lecturer at the MIT Sloan School of Management and a nonresident senior fellow at the Brookings Institution. Previously, he was executive chairman of MFS Investment Management, vice chairman of Fidelity Investments, and president of Fidelity Management & Research Co. Pozen is the author of “Extreme Productivity: Boost Your Results, Reduce Your Hours” and co-author of “Remote, Inc.: How to Thrive at Work … Wherever You Are.”
Renee Fryis the co-founder and CEO of Gentreo, an online provider of affordable, accessible, and easy-to-use estate planning tools. She is the former CEO of Sustainable Manufacturing Co. and a founder of Making Care Easier. Fry previously served in Massachusetts Gov. Mitt Romney’s cabinet, overseeing business and
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