AI-Powered Email Deliverability and Intelligent Outreach Optimization: Challenges, System Design, and Experimental Analysis

Abstract

Email deliverability is a major challenge in modern digital communication, where a significant number of emails fail to reach the recipient’s inbox. This issue arises due to strict spam filters, poor domain reputation, and incorrect configuration of authentication protocols such as SPF, DKIM, and DMARC. As a result, even legitimate business emails are often marked as spam, leading to reduced communication efficiency and financial losses. This paper presents an AI-Powered Email Deliverability and Intelligent Outreach Optimization System (AEIOS) aimed at improving inbox placement and overall email performance. The system integrates domain intelligence, authentication validation, and machine learning-based spam detection. A Gradient Boosting classifier achieves 96.2% spam detection accuracy with an AUCROC of 0.97. End-to-end deliverability experiments show an inbox placement rate of 93.6%, representing a 122% improvement over the unauthenticated baseline and a 25% improvement over commercial tools. The system further provides real-time analytics, risk scoring, and actionable remediation guidance to support smarter email outreach strategies.