# How AI Changes the Role of Applied Scientists

DevFeed: [How AI Changes the Role of Applied Scientists](<https://devfeed.tech/articles/how-ai-changes-the-role-of-applied-scientists-20106.md>)

Original publisher: [Read original article](<https://tech.instacart.com/how-ai-changes-the-role-of-applied-scientists-895192d5e114?source=rss----587883b5d2ee---4>)

Author: Tilman Drerup

Published: 2026-05-22T17:40:32Z

Content type: article

Language: en

Sources: [Instacart](<https://devfeed.tech/sources/instacart.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Data Science](<https://devfeed.tech/topics/data-science.md>), [AI, ML & Data Engineering](<https://devfeed.tech/topics/ai-ml-data-engineering.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [analysis](<https://devfeed.tech/tags/analysis.md>), [applied-science](<https://devfeed.tech/tags/applied-science.md>), [artificial-intelligence](<https://devfeed.tech/tags/artificial-intelligence.md>), [changes](<https://devfeed.tech/tags/changes.md>), [coding](<https://devfeed.tech/tags/coding.md>), [economics](<https://devfeed.tech/tags/economics.md>), [machine-learning](<https://devfeed.tech/tags/machine-learning.md>), [math](<https://devfeed.tech/tags/math.md>), [statistics](<https://devfeed.tech/tags/statistics.md>)

## AI overview

Instacart's Economics Team examines how artificial intelligence is changing the work of applied scientists. The article frames the role as a bundle of tasks and proposes analyzing changes in the team's project portfolio from 2023 onward, with potentially larger effects on coding than on causal inference.

## Source excerpt

Levi Boxell, Tilman Drerup, Alexandr Lenk The Economics Team at Instacart is an applied science team that operates at the intersection of machine learning engineering and economics. Similar to other applied science teams, our work involves a good chunk of engineering, steeped in statistics, math, theory, and strategy. And while that is still at the heart of what we do today, the surprisingly rapid emergence of artificial intelligence has also fundamentally altered our work in ways that we did not see coming. With this post, we want to provide a brief check-in and share an analysis of the patterns we are seeing from a distinctly economic perspective. To do so, we analyze the empirical dynamics of our project portfolio between 2023 and today, looking at the evolution of both the nature and quantity of our work over time. To start, let's have a quick refresher of what economists at Instacart do and provide a theoretical framework to think about the impact of technological change through AI. Background & Theoretical Framework At Instacart, economists spend their day-to-day on a diverse portfolio of tasks and activities. Similar to other applied science teams within the company, our work relies on a blend of skills, including economics, statistics, math, machine learning, data manipulation, coding, and AI. Due to this versatility in tasks, the team's work provides a particularly rich testing ground for predictions derived from economic theories concerning the impact of technological change. But what does economic theory actually tell us? A useful theoretical abstraction for an applied scientist's role is to frame it as a bundle of tasks (Autor, Levy, and Murnane, 2003), with each task characterized by its own production function (Acemoglu and Autor, 2011). Slightly simplified, a production function tells us how much output we can produce for a given level of input in a specific task. Comparisons of production functions across tasks in turn determine how we allocate our t