Source note2 min read
Toward Continuous Assurance for the Democratization of AI Agent Creation in Industry
Source
arXiv
arxiv.org/abs/2607.21495v1
Source
- Source name: arXiv
- Source kind: paper
- Authors / organization: Natan Levy, Harel Berger
- Venue: arXiv: cs.AI
- Published: 2026-07-23
- Collected: 2026-07-24
- URL: http://arxiv.org/abs/2607.21495v1
- PDF: https://arxiv.org/pdf/2607.21495v1
- DOI: UNKNOWN
Plain-Language Brief
The paper proposes a solution for ensuring the reliability of AI agents created by non-engineering users within organizations, as the democratization of AI agent creation can lead to unforeseen dependencies causing silent degradation after deployment.
What the Document Says
- AI agents are being increasingly created inside organizations by non-engineering users through low-code, no-code, and conversational development environments
- This democratization enables rapid local innovation but creates a reliability gap as dependencies of these agents can cause silent degradation after deployment
- The paper proposes a lightweight continuous-assurance framework for citizen-created organizational agents
- The framework includes dependency mapping, readiness contracts, scheduled checks, diagnostics, and lifecycle governance
- An initial prototype auditor and scenario-based assessment are presented to demonstrate the practical application of the proposed taxonomy
Key Concepts Mentioned
- AI agents
- democratization
- reliability gap
- dependency mapping
- readiness contracts
- scheduled checks
- diagnostics
- lifecycle governance
Claims Made by the Document
- Democratization of AI agent creation enables rapid local innovation but creates a reliability gap
- The proposed lightweight continuous-assurance framework can assess whether an agent remains operationally ready under expected conditions
Evidence Used
- AI agents being created by non-engineering users inside organizations
- Dependencies of these agents causing silent degradation after deployment
- Proposal of a lightweight continuous-assurance framework for citizen-created organizational agents
Methods / Approach
UNKNOWN
Limitations Stated by the Authors
UNKNOWN
Limitations Noted by the Agent
Agent interpretation — not from the source.
UNKNOWN
Open Questions
UNKNOWN
Notes for Future Q&A
May include interpretation. Labeled where it does.
UNKNOWN
Raw Abstract / Excerpt
AI agents are increasingly created inside organizations by non-engineering users through low-code, no-code, and conversational development environments. This democratization enables rapid local innovation, but it also creates a reliability gap: agents that appear to users as simple productivity artifacts may depend on changing models, tools, retrieval sources, permissions, prompts, schedules, and external services. These dependencies can cause silent degradation long after deployment, even when no user directly modifies the agent. This paper identifies the reliability challenge created by democratized AI agent creation and proposes a lightweight continuous-assurance framework for citizen-created organizational agents. The framework combines dependency mapping, readiness contracts, scheduled checks, diagnostics, and lifecycle governance to assess whether an agent remains operationally ready under expected conditions. We also present an initial prototype auditor and scenario-based assessment showing how the proposed taxonomy can be translated into practical checks and actionable remediation guidance.
