Automated Email Assistant Using Generative AI
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Electronic messaging systems are inefficient due to the numerous actions required to respond to messages, including scheduling meetings and allocating tasks, which disrupt the workflow of the receiver.
Innovation Solution
A system utilizing generative artificial intelligence (AI) that automates responses by evaluating incoming messages to determine if a meeting is requested and tasks are needed, then generates a responsive message, schedules meetings, and allocates tasks using a large language model and user-defined rules, minimizing user intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual processing of electronic messages is used to respond to messages, schedule meetings, and allocate tasks, then the receiver can maintain control over the workflow, but the workflow of the receiver is disrupted and time is lost
Solution Approach 1:
An automated assistant system acts as an intermediary between the receiver and incoming electronic messages. The assistant processes messages, schedules meetings, and allocates tasks automatically, reducing the receiver's direct involvement while maintaining workflow control through predefined policies and user-configurable settings.
Solution Approach 2:
The system enables self-service by allowing the receiver to configure their preferences, availability, and task allocation rules once, after which the system autonomously handles message responses, meeting scheduling, and task distribution without requiring continuous manual intervention.
2Ease of operation
If automated systems are used to respond to messages, schedule meetings, and allocate tasks, then workflow efficiency is improved, but the system complexity increases
Solution Approach 1:
The automated system is segmented into distinct functional modules: message processing module, meeting scheduling module, and task allocation module. Each module handles specific aspects of workflow automation independently, making the overall system easier to manage and configure despite its comprehensive capabilities.
Solution Approach 2:
The automated assistant is designed as a universal system that can handle multiple types of electronic messages, schedule various types of meetings, and allocate different kinds of tasks through a single integrated interface, reducing the need for multiple specialized tools.
3Loss of time
If the receiver manually generates responses and schedules meetings, then the quality of personalization is maintained, but time is lost and productivity decreases
Solution Approach 1:
The system performs preliminary actions by pre-configuring response templates, availability calendars, and task templates based on user preferences. When a message arrives, the system quickly retrieves and adapts these pre-prepared elements, significantly reducing response time while maintaining personalization quality.
Solution Approach 2:
The system incorporates feedback mechanisms where the receiver can review and adjust automated responses, meeting schedules, and task allocations before final execution. This feedback loop ensures quality control while the system handles the time-consuming aspects of drafting and coordination.
Data Source
AI summary
A system for using generative AI to automate electronic communication responses includes receiving, from an initiating entity, an electronic communication at a receiving entity. The system provides the electronic communication to a large language model (LLM). The system provides instructions to the LLM, causing the LLM to evaluate the electronic communication to determine whether a meeting is requested, to produce a meeting indicator, to evaluate the electronic communication to determine if there are one or more tasks, to produce a task list, and to produce a responsive electronic communication based on user-defined rules. The system receives a dataset from the LLM. If a meeting is requested, the system identifies mutually available meeting times between the initiating and receiving entities. The system sends a meeting invitation at a mutually available meeting time. The system sends the responsive electronic communication. The system generates the tasks from the task list.