Auto-managing Requestor Communications for Pending Activities
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Solution Overview
Problem
Requestors face challenges in managing activities across diverse actors with different communication styles, leading to incomplete tasks and time-consuming follow-ups, as they need to consider various factors such as actor availability, workload, and relationship dynamics.
Innovation Solution
A system and method that utilize actor context data to auto-generate communications and communication strategies, taking into account emotional states, priority levels, and preferred communication modes to increase the likelihood of task completion and maintain positive relationships.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If requestors manually follow up on activities with diverse actors, then task completion can be monitored, but requestors spend excessive time and cognitive effort on communication management
Solution Approach 1:
The system enables automated self-service communication management where the AI assistant autonomously generates and sends follow-up communications to actors based on task status and actor context, eliminating the need for requestors to manually track and communicate with each actor
Solution Approach 2:
The AI assistant serves as an intermediary between requestors and actors, handling all communication tasks including initial task assignment, status updates, and follow-up reminders, thereby shielding requestors from direct communication overhead while ensuring reliable task monitoring
2Reliability
If requestors send frequent follow-up communications to ensure task completion, then task completion rate improves, but actor relationships may deteriorate due to excessive communication
Solution Approach 1:
The system dynamically adjusts communication frequency and timing based on real-time actor context data including responsiveness patterns, current workload, and preference settings, sending communications only when necessary to nudge task completion without overwhelming the actor
Solution Approach 2:
The AI assistant changes communication parameters such as tone, urgency level, and channel type based on the actor's emotional state and context, adapting messages to maintain positive relationships while still driving task completion
3Reliability
If requestors customize communications for each actor's preferences and context, then task acceptance increases, but communication management complexity increases
Solution Approach 1:
The system automatically collects and processes actor context data from multiple sources including communication history, calendar availability, and preference settings, then uses this data to self-generate personalized communications without requiring requestor intervention
Solution Approach 2:
The AI assistant pre-analyzes actor context and prepares personalized communication templates in advance based on learned preferences and patterns, so that when task assignment or follow-up is needed, the customized communication is already ready to send immediately
Data Source
AI summary
Aspects of the present disclosure relate to assisting a requestor to manage activities a cross a plurality of diverse actors. In examples, a system is provided that includes at least one processor, and memory storing instructions that, when executed by the at least one processor, causes the system to perform a set of operations. The set of operations include receiving a request for a task to be completed, from the requestor, receiving actor context data, recording an assignment of the task to an actor, based on the actor context data, generating a communication to request that the actor complete the assigned task, and sending the communication to the actor.