AI-Powered Digital Experience Platforms: Architecting for Scale, Speed, and Intelligence

Abstract

Personalized, scalable, and responsive user experiences are central to the value of Digital Experience Platforms (DXPs). However, many legacy DXPs struggle to deliver real-time personalization, maintain performance at scale, and adapt dynamically to user behavior. This paper explores the integration of advanced AI capabilities—specifically large language model (LLM) copilots, reinforcement-driven personalization, and agent-based orchestration—into modern DXPs across retail, B2B SaaS, and government services.

Through simulation and pilot deployments, the proposed AI-enabled DXP architecture achieved significant improvements: session duration increased by 75%, click-through rate by 52%, and personalization accuracy by 37.7%, while P95 latency dropped from 870 ms to 388 ms. Additional gains included faster deployment cycles, higher A/B testing throughput, and reduced content authoring time. Governance frameworks combining federated learning with explainable AI (XAI) delivered the highest GDPR compliance (96%) and user trust scores (8.9/10).

The results demonstrate that AI-powered DXPs represent not just an incremental enhancement, but a transformative platform model capable of delivering intelligent, compliant, and adaptive experiences at scale. The paper concludes with a reference architecture and performance benchmarks to guide enterprise adoption of AI-driven digital experience platforms.