In today’s dynamic healthcare landscape, Patient and Member Engagement (PME) has become a strategic imperative for healthcare enterprises and service and platform providers. Historically overlooked and limited to administrative touchpoints, PME has evolved into a mission-critical function that impacts patient/member satisfaction and business outcomes, such as retention, medication adherence, care outcomes, and cost improvements. Rising expectations, omnichannel demand, regulatory pressures, and advanced technology have accelerated the transition toward seamless, intelligent, and personalized engagement across the care journey.  In this report, we analyze the PME’s evolving role in healthcare and its significance in driving better outcomes. The report assesses key adoption trends, identifies technology and organizational accelerators, and highlights the barriers that limit PME’s scaling across the industry. Focusing on real-world enterprise priorities, the report outlines how healthcare organizations are using gen AI, predictive analytics, and agentic AI to enable self-service, deliver personalized communication, and proactively retain members and patients.  Additionally, the report examines the emergence of Systems of Execution (SoE) and their potential to unify data, drive AI-led engagement, and convert insights into real-time execution across touchpoints. It also provides sourcing guidance and strategic recommendations for payers and providers, emphasizing the need for a PME lead to drive enterprise alignment and measure experience success. 

At SAP Sapphire 2025, SAP reinforced its ambition to lead in enterprise AI by unveiling a range of innovations under its Business AI umbrella. Key announcements include the launch of AI Foundation, positioned as the operating system for SAP’s AI strategy, enabling simplified operations, innovation acceleration, and democratized access to predictive capabilities. Expanding Joule into an omnipresent AI assistant, accessible across SAP and third-party applications, marks SAP’s move toward ambient, context-aware AI. By introducing AI Agent Hub and cross-system Joule agents, SAP is evolving toward agentic automation that spans business silos. Business Data Cloud underpins these capabilities by unifying SAP and non-SAP data to enable real-time insight and orchestration. Introducing modular business suite-as-a-service packages further supports composability and easier adoption.

Enterprise AI platforms are at the forefront of digital transformation, enabling businesses to innovate, compete, and operate efficiently. These platforms empower organizations to streamline processes, enhance decision-making, and accelerate their AI adoption journeys by unifying data governance, model training, deployment, and monitoring in a single ecosystem. Gen AI further amplifies this by enabling dynamic automation, content generation, and personalized customer interactions. In this report, we analyze enterprise AI platforms, including their architecture, core components, and technology advances. The report highlights key trends shaping these platforms’ adoption, including the rise of Small Language Models (SLMs) tailored to specific business needs, the growing importance of ethical AI governance, and the integration of real-time decision-making capabilities. It also examines enterprise challenges in scaling AI adoption. This research offers valuable insights for businesses harnessing AI platforms for sustainable growth and competitive differentiation. Scope Industry: cross-industry Geography: global Contents In this report, we examine: Introduction to enterprise AI platforms: overview of architecture, capabilities, and definitions Technology advances: insights into gen AI, agentic AI, and governance tools shaping platform capabilities Market trends and drivers: the role of SLMs, real-time analytics, and scalable AI solutions in adoption Ecosystem evaluation: leading players across big tech, data management heritage, native AI, and specialized AI providers Challenges and strategic solutions: addressing integration, data complexity, and cost management Membership(s) Artificial Intelligence (AI) Sourcing and Vendor Management