AI-Assisted IT Error Guidance for User-Led Network Management
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Managing computer networks requires significant IT professional involvement, leading to overhead costs and workflow bottlenecks when professionals are unavailable.
Innovation Solution
An AI-assisted system that allows users, including administrators and single-computer users, to manage network resources and troubleshoot issues through a user-friendly interface, utilizing AI/ML logic for non-technical summaries and recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If IT professionals manage network resources manually, then network management can be performed, but overhead costs increase and workflow bottlenecks occur when professionals are unavailable
Solution Approach 1:
The system enables end users to perform IT management tasks independently through the AI assistant interface. Users can request IT operations, receive automated responses with non-technical summaries and recommended actions, and execute tasks without IT professional intervention, thereby eliminating workflow bottlenecks and reducing overhead costs.
Solution Approach 2:
The AI assistant serves as an intermediary between end users and IT operations. It translates user requests into actionable IT tasks, provides non-technical summaries of error conditions, and recommends appropriate actions, thereby mediating the interaction and eliminating the need for direct IT professional involvement in routine tasks.
2Reliability
If IT professionals are used for network management, then technical issues can be resolved, but dependency on professional availability increases
Solution Approach 1:
The system provides continuous availability for IT issue resolution without dependency on professional schedules. The AI assistant operates autonomously to identify error conditions, generate non-technical summaries, and execute recommended actions, ensuring reliable issue resolution at any time regardless of IT professional availability.
3Measurement precision
If technical information is presented to users, then accurate IT management can be performed, but user accessibility decreases due to technical complexity
Solution Approach 1:
The system transforms the presentation parameters of technical information by converting complex error conditions into non-technical summaries through AI processing. This parameter transformation maintains the accuracy and precision of error identification while presenting information in accessible language that end users can understand and act upon independently.
Data Source
AI summary
Embodiments herein may relate to a process to be performed by an electronic device. The process may include identifying an error condition related to a first computing device of a plurality of computing devices. The process may further include generating, based on a machine learning (ML) model, an indication of the error condition that is provided to a user, wherein the indication includes: a non-technical summary of the condition; and a recommended action to remedy the error condition. Other embodiments may be described and/or claimed.


