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National Institute of Standards and Technology (NIST) (2023) AI Risk Management Framework (AI RMF 1.0). NIST.
https://www.nist.gov/itl/ai-risk-management-framework

has been cited by the following article:

• TITLE: The New Software Cost Curve under Agentic AI: Development Economics, Pricing, and Labor Impacts

  AUTHORS: Wasim Haque

  KEYWORDS: Agentic AI, Software Economics, Total Cost to Deliver, SaaS Pricing, Software Labor Market, AI Risk Governance, DevOps, SRE, T3D, Test and Defect Driven Development

  JOURNAL NAME: Journal of Software Engineering and Applications, Vol.19 No.1, January 28, 2026

  ABSTRACT: Agentic AI—software agents that plan, generate, test, and iterate across the software lifecycle—is bending the software cost curve. We merge two complementary analyses: 1) a development-focused comparison between a traditional human-centric Agile team and an agentic workflow, and 2) an extension from build cost to total cost to deliver (build, run, sell, and risk), including implications for SaaS and non-SaaS pricing and the software labor market. Using an illustrative benchmark, we show how build costs can collapse (irrespective of methodology you use, old or new ones like T3D [1]) by more than an order of magnitude while time-to-market compresses from quarters to weeks. The binding constraints then shift toward operations, distribution, and risk management. We propose a pricing pressure matrix and a practical playbook for packaging, governance, and workforce reskilling over a 1 - 7-year horizon.