---
type: source
title: "From Problems to Solutions in Strategic Decision-Making: The Effects of Generative AI on Problem Formulation"
author: "Nety Wu, Hyunjin Kim, Chengyi Lin (INSEAD)"
url: https://doi.org/10.2139/ssrn.5456494
date: 2026-04-03
domain: ai-alignment
intake_tier: directed
rationale: "The 'mapping problem' — individual AI task improvements don't automatically improve firm performance because organizations must discover WHERE AI creates value in their production process. Adds a fourth absorption mechanism to the macro-productivity null result."
proposed_by: "Leo (research batch routing)"
format: paper
status: processed
processed_by: rio
processed_date: 2026-04-05
claims_extracted: []
enrichments:
  - "macro AI productivity gains remain statistically undetectable despite clear micro-level benefits because coordination costs verification tax and workslop absorb individual-level improvements before they reach aggregate measures"
---

# Hyunjin Kim — AI Mapping Problem

Kim (INSEAD Strategy) studies how data and AI impact firm decisions and competitive advantage. The "mapping problem": discovering WHERE AI creates value in a firm's specific production process is itself a non-trivial optimization problem. Individual task improvements don't compose into firm-level gains when deployed to the wrong tasks or in the wrong sequence. Paper abstract not accessible (SSRN paywall) but research profile and related publications confirm the thesis. Note: Leo's original routing described this as a standalone tweet; the research exists but the specific "mapping problem" framing may come from Kim's broader research program rather than a single paper.
