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Ethan Mollick research: AI agent shopping choices are unpredictable

By PulseAugur Editorial · [1 sources] ·

New research from Ethan Mollick explores the unpredictable nature of AI agentic shopping behavior. The study found that even minor variations, such as the order in which AI agents view web pages or their stored memories, significantly influenced their choices in ways that were difficult to predict or manipulate through marketing tactics. AI

IMPACT Highlights the challenges in controlling or predicting AI agent behavior, impacting future AI application design and marketing strategies.

RANK_REASON Research paper published on SSRN and discussed on Bluesky. [lever_c_demoted from research: ic=1 ai=1.0]

Read on Bluesky Jetstream — AI desk →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Ethan Mollick research: AI agent shopping choices are unpredictable

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19 / 100
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Research paper published on SSRN and discussed on Bluesky. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. Bluesky Jetstream — AI desk TIER_1 English(EN) · emollick.bsky.social ·

    🚨Our new research examines agentic shopping: can you consistently predict (or, using marketing, influence) what an agent chooses?

    🚨Our new research examines agentic shopping: can you consistently predict (or, using marketing, influence) what an agent chooses? Nope. We found that even small differences (viewing order of pages, memories) changed AI preferences in unpredictable ways. papers.ssrn.com/sol3/pap…

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