All

Early LLM-based Tools for Enterprise Information Workers Likely Provide Meaningful Boosts to Productivity. Microsoft Research Report – AI and Productivity Team. With Alexia Cambon, Brent Hecht, Donald Ngwe, Sonia Jaffe, Amy Heger, Mihaela Vorvoreanu, Sida Peng, Jake Hofman, Alex Farach, Margarita Bermejo-Cano, Eric Knudsen, James Bono, Hardik Sanghavi, Sofia Spatharioti, David Rothschild, Daniel G. Goldstein, Eirini Kalliamvakou, Peter Cihon, Mert Demirer, Michael Schwarz, and Jaime Teevan.

This report presents the initial findings of Microsoft’s research initiative on “AI and Productivity”, which seeks to measure and accelerate the productivity gains created by LLM-powered productivity tools like Microsoft’s Copilot. The many studies summarized in this report, the initiative’s first, focus on common enterprise information worker tasks for which LLMs are most likely to provide significant value. Results from the studies support the hypothesis that the first versions of Copilot tools substantially increase productivity on these tasks. This productivity boost usually appeared in the studies as a meaningful increase in speed of execution without a significant decrease in quality. Furthermore, we observed that the willingness-to-pay for LLM-based tools is higher for people who have used the tools than those who have not, suggesting that the tools provide value above initial expectations. The report also highlights future directions for the AI and Productivity initiative, including an emphasis on approaches that capture a wider range of tasks and roles.

Studies I led that are included within this report:

• Measuring the Impact of AI on Information Worker Productivity
• Sound Like Me: Findings from a Randomized Experiment
• Randomized Controlled Trial for Microsoft Security Copilot

Sound Like Me: Findings from a Randomized Experiment. SSRN Working Paper 4648689. With Donald Ngwe.

A new version of Copilot for Microsoft 365 includes a feature to let Outlook draft messages that “Sound Like Me” (SLM) based on training from messages in a user’s Sent Items folder. We sought to evaluate whether SLM lives up to its name. We find that it does, and more. Users widely and systematically praise SLM-generated messages as being more clear, more concise, and more “couldn’t have said it better myself”. When presented with a human-written message versus a SLM rewrite, users say they’d rather receive the SLM rewrite. All these findings are statistically significant. Furthermore, when presented with human and SLM messages, users struggle to tell the difference, in one specification doing worse than random.

(Also summarized in What Can Copilot’s Earliest Users Teach Us About Generative AI at Work? at “Email effectiveness.” Also summarized in AI and Productivity Report at “Outlook Email Study.”)

Measuring the Impact of AI on Information Worker Productivity. SSRN Working Paper 4648686. With Donald Ngwe and Sida Peng.

This paper reports the results of two randomized controlled trials evaluating the performance and user satisfaction of a new AI product in the context of common information worker tasks. We designed workplace scenarios to test common information worker tasks: retrieving information from files, emails, and calendar; catching up after a missed online meeting; and drafting prose. We assigned these tasks to 310 subjects tasked to find relevant information, answer multiple choice questions about what they found, and write marketing content. In both studies, users with the AI tool were statistically significantly faster, a difference that holds both on its own and when controlling for accuracy/quality. Furthermore, users who tried the AI tool reported higher willingness to pay relative to users who merely heard about it but didn’t get to try it, indicating that the product exceeded expectations.

(Also summarized in What Can Copilot’s Earliest Users Teach Us About Generative AI at Work? at “A day in the life” and “The strain of searching.” Also summarized in AI and Productivity Report at “Copilot Common Tasks Study” and “Copilot Information Retrieval Study.”)