AI Communication Mode Selection for Faster Responses
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Solution Overview
Problem
The complexity in deciding the best communication mode with another party, especially in inter-organizational communications, often leads to inefficiencies and delays in response times.
Innovation Solution
A machine learning model trained on historical communication data across multiple platforms suggests the best mode of communication, including platform selection and timing, to facilitate quicker and more positive responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple communication platforms are used to communicate with another party, then communication flexibility and options increase, but decision complexity and time to determine the best communication mode increase
Solution Approach 1:
The system automatically analyzes historical communication data and platform availability to generate communication mode suggestions without requiring manual decision-making. The AI model self-serves by processing data and providing recommendations based on learned patterns from historical usage across multiple platforms.
Solution Approach 2:
The AI communication mode suggestion system acts as an intermediary between the user and multiple communication platforms. It processes information about platform availability and historical effectiveness, then mediates by suggesting the optimal communication mode, thereby simplifying the decision-making process while maintaining access to multiple platforms.
2Adaptability or versatility
If multiple communication platforms are used to communicate with another party, then communication flexibility increases, but response time and communication efficiency decrease
Solution Approach 1:
The system performs preliminary analysis of historical communication data and platform availability before a communication attempt is made. By pre-processing this information and generating suggestions in advance, the system enables faster decision-making when communication is needed, rather than analyzing options in real-time when urgency is high.
Solution Approach 2:
The system uses feedback from historical communication outcomes to continuously improve its suggestions. By analyzing which communication modes have resulted in successful and timely responses in the past, the AI learns and adapts to provide increasingly accurate recommendations that reduce response time while maintaining communication flexibility.
3Productivity
If manual analysis of communication history is performed to determine best communication mode, then communication effectiveness improves, but time and computational resources increase
Solution Approach 1:
The system replaces manual analysis of communication history with an automated AI machine learning model. Instead of human users manually reviewing communication patterns and platform availability, the AI model automatically processes historical data and generates suggestions, thereby maintaining communication effectiveness while eliminating the time and effort required for manual analysis.
Data Source
AI summary
A method, computer system, and a computer program product for generating a communication mode suggestion are provided. A first computer may receive a communication request from a first user to communicate with a second user. The first computer inputs the received communication request to a first machine learning model. The first machine learning model was trained with historical usage of the second user for communication of responses across multiple communication platforms. The trained first machine learning model generates the communication mode suggestion in response to receiving the received communication request as an input. The first computer transmits the communication mode suggestion for presentation to the first user.