AI Agents Are Arriving Faster Than Operating Models
Organizations can deploy agent capability faster than they can make delegated work accountable. AI agents are entering organizations as technology, but they are changing organizations as participants in work. Most executive conversations still begin with capability. What can the agent do? How quickly can it be deployed? Which platform should the organization choose? How many workflows can be…
AI agents are arriving in organizations faster than their operating models can adapt. While executives focus on the capabilities and rapid deployment of these AI agents, they are missing a crucial aspect: the impact on the organization's work system. An AI agent, once connected to relevant data sources, can produce a polished briefing in minutes.
However, the problems might still exist within the briefing, such as outdated expansion plans or misleading facts. The organization still needs to ensure accountability and proper review processes to prevent these issues from affecting its clients. The challenge lies in transitioning from managing software features to managing participants within a work system.
The organization must define what the work aims to accomplish, set explicit boundaries for participants, and ensure evidence travels with the work. Governance must accompany the decision-making process, reaching across data, analytics, architecture, and transformation work. Simply acquiring AI agent capability is not enough; organizations must also create a work system that can detect, challenge, contain, and learn from any errors or exceptions generated by these agents.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
