Agentomics: Economic Foundations for the Valuation, Attribution, and Pricing of AI Agents in Human-AI Workflows
arXiv:2606.14769v1 Announce Type: cross Abstract: Agentic AI systems are increasingly being deployed as productive resources in organizational workflows, yet existing evaluation methods primarily measure isolated technical performance rather than economic contribution. This paper introduces \emph{Agentomics}, a workflow-based framework for valuing, attributing, and pricing human and artificial agents. The framework models a workflow as a configuration of heterogeneous agents whose collective performance determines gross value, deployment cost, reliability, and expected failure loss. Workflow v
The proliferation of advanced AI agents in enterprise and consumer workflows necessitates a robust economic framework to quantify their value and integration, moving beyond isolated performance metrics.
This paper introduces a foundational economic model for AI agents, which is crucial for organizations to strategically deploy, value, and manage these new digital resources, impacting investment and operational decisions.
The focus shifts from merely technical AI performance to quantifiable economic contribution, enabling clearer ROI assessment and strategic allocation within human-AI collaborative systems.
- · AI agent developers
- · Organizations deploying AI agents
- · AI consulting firms
- · Economists
- · Companies relying on outdated AI evaluation metrics
- · Inefficient workflow managers
- · Jobs easily automated without economic justification
Companies will begin to implement more sophisticated economic models to justify and optimize their AI agent investments.
This improved valuation will accelerate AI agent adoption and integration into core business functions, leading to significant productivity gains for early adopters.
The widespread economic valuation of AI agents could lead to new forms of capital markets or financial instruments dedicated to valuing and trading agent performance units.
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Read at arXiv cs.AI