Intel / article

Finishing the Task Is Not Enough: Evaluating Agent Resilience and Considerate Participation under Accumulating Challenge

Source: arxiv.org
Author: Yuanchen Bai, Zijian Ding, Angelique Taylor
Date: Published Sep 12, 2026

Context

The authors of a study of 120 simulated healthcare trajectories, using two generative AI models and twelve tasks, report that as disruptions accumulate, agents shift from recovering on their own toward greater dependence on people. Their title argues that finishing the task is not enough to judge an that must keep working through repeated problems.

The authors propose evaluating both recovery from blocked work and the effects of that recovery on other participants. This includes whether an agent preserves progress, communicates its limits, respects role boundaries, and coordinates appropriately. From the simulations they derive deployment dilemmas, including persistence and escalation, which pose a question teams must specify for themselves: when should an agent keep trying, change the task, or involve another person?

Terms in this piece · Glossary

AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.

Read the source arxiv.org