AI Agent Workflow Management for Context-Aware Access Control
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Solution Overview
Problem
Current systems lack effective methods for dynamically managing the execution of artificial intelligence agents, particularly in enterprises where users have varying access needs and trust levels based on contextual circumstances, leading to static and inflexible workflows.
Innovation Solution
A system that uses a second AI agent as a management controller to enforce device compliance, allowing dynamic management of AI agent workflows by applying policies based on device, user, and network conditions, and enabling flexible execution paths through a manifest file that tracks dependencies and compliance rules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If static pre-built workflows are used for AI agent execution, then implementation simplicity is improved, but adaptability to different user needs and contextual circumstances deteriorates
Solution Approach 1:
The patent implements dynamic workflow execution by allowing the system to adjust and modify AI agent workflows at runtime based on user trust levels, device compliance status, and contextual circumstances. The workflow engine evaluates compliance rules and dynamically determines which agent objects to execute and in what order, transforming static pre-built workflows into adaptive, context-aware execution paths that resolve the contradiction between implementation simplicity and adaptability.
2Reliability
If comprehensive device compliance checking is implemented, then security and control are improved, but system complexity and overhead increase
Solution Approach 1:
The patent applies preliminary action by performing device compliance checking and trust level assessment before AI agent execution begins. The system evaluates device status, network characteristics, and user credentials in advance, storing compliance results that can be reused for subsequent agent executions. This preliminary compliance verification reduces the need for repeated complex checks during each agent execution, thereby improving security and control while managing system complexity through caching and reuse of compliance data.
3Adaptability or versatility
If dynamic workflow management is implemented, then flexibility and adaptability are improved, but difficulty of managing execution increases
Solution Approach 1:
The patent introduces an intermediary compliance evaluation service that mediates between the complex requirements of dynamic workflow management and the users needing to execute AI agents. This service handles the complexity of evaluating compliance rules, determining trust levels, and selecting appropriate execution paths, presenting a simplified interface to users while maintaining flexible and adaptive workflow management capabilities underneath.
Data Source
AI summary
Systems and methods are described for dynamic execution of artificial intelligence (“AI”) agents. A server can receive, from a client device, an input associated with an AI agent. Based on a manifest file or user profile, the server can identify a management policy that applies to the AI agent. The server then dynamically configures access to the agent objects based on applying the management policy. The management policy is applied to a device status of the client device, a user profile of a user of the client device, and/or a network configuration of the client device. The server then executes a modified workflow based on the dynamically configured access, wherein the modified workflow bypasses or changes operation of at least one of the agent objects. Based on the modified workflow, the server transmits an output to the client device.