Modeling Agentic Technical Debt and Stochastic Tax: A Standalone Framework for Measurement, Simulation, and Dashboarding
2026-05-26 • Artificial Intelligence
Artificial IntelligenceComputers and Society
AI summaryⓘ
The authors explain how AI systems that make decisions and take actions can create two types of costs: Agentic Technical Debt and Stochastic Tax. Agentic Technical Debt is like a buildup of design problems and management issues over time, while Stochastic Tax is the ongoing extra work caused by AI's unpredictable behavior. They show that although these costs are related, they are different, and both can be measured using data from how the AI system operates. The authors also provide a simple model and an example using accounts payable to help managers understand and estimate these costs.
Agentic AIProbabilistic reasoningTechnical DebtStochastic processesOperational costsGovernanceWorkflow integrationSimulation modelAccounts payable
Authors
Muhammad Zia Hydari, Raja Iqbal, Narayan Ramasubbu
Abstract
Agentic AI systems combine probabilistic reasoning with delegated action through tools, context, memory, orchestration, and external workflow integration. This note develops a formal and managerially usable model that distinguishes Agentic Technical Debt from Stochastic Tax. Agentic Technical Debt is a stock of accumulated design and governance liability. Stochastic Tax is a recurring flow of operating burden that arises when stochastic agents are used in business workflows. The two constructs are related, but they are not the same: debt can amplify the tax, while the tax can remain positive even when debt is minimized. The note starts from a compact dashboard expression, expands it into a fuller structural model, defines all variables and parameters, shows how each cost category can be estimated from operational data, and illustrates the framework with an accounts-payable simulation and companion spreadsheet.