The Autonomous Patient: Is MarTech AI the Future of Healthcare Engagement?

NEW DELHI, India – November 25, 2025 – In a move that signals a significant technological convergence, digital transformation leader Comviva has unveiled a Generative AI-driven version of its MobiLytix® Real Time Marketing (RTM) platform. While the announcement targets enterprise marketers with promises of higher conversion and retention, its underpinnings—autonomous AI agents, real-time journey orchestration, and hyper-personalization—have profound implications far beyond retail and e-commerce. For a healthcare industry grappling with a chronic patient engagement crisis, this evolution from marketing automation to marketing autonomy could represent a disruptive, albeit complex, new frontier.

The press release speaks of empowering marketers to “design smarter, faster, and high engagement campaigns.” But replace “marketer” with “healthcare provider” and “campaign” with “patient care pathway,” and the potential becomes clear. The challenge for health systems is no longer just about delivering world-class clinical care within their walls; it's about influencing patient behavior, ensuring adherence, and providing continuous support outside of them. This is a communication and engagement problem, and the technology industry is now offering a powerful, AI-driven solution.

From Automation to Autonomy in Patient Outreach

For years, healthcare providers have used basic automation for appointment reminders and generic wellness newsletters. These systems are functional but lack the sophistication to drive meaningful behavioral change. Comviva's announcement represents a paradigm shift, joining a chorus of major tech players like Salesforce and Adobe who are embedding GenAI into their platforms.

The core innovation is the move toward what the company calls “marketing autonomy.” This isn't just about scheduling messages; it's about creating an intelligent ecosystem of AI agents that can independently manage and optimize communication. According to the announcement, these agents are designed to “continuously learn from campaign performance, optimize creative, offers and timing in real time, and operate under marketer-defined governance.”

“Tomorrow's marketing teams won't just run campaigns; they will command an intelligent ecosystem of AI agents that plan, optimize and execute in real time,” said Manish Singhal, Head – MarTech Solutions at Comviva. “We are moving from marketing automation to marketing autonomy.”

Imagine this applied to healthcare. A post-discharge AI agent for a cardiac patient could analyze data from a wearable, notice a drop in activity levels, and proactively send an encouraging, personalized message with a link to a specific cardiac rehab exercise video. It could then test different message tones—empathetic, direct, encouraging—to learn which one elicits the best response from that individual patient. The MobiLytix platform’s claim of using over 120 predictive and prescriptive AI models to personalize interactions based on a “live 360° customer profile” could, in a healthcare context, evolve into a 360-degree patient profile, creating a dynamic and responsive communication channel that adapts to the patient's health journey in real time.

A New Prescription for Engagement and Adherence

The potential use cases for this level of autonomous engagement in healthcare are vast and transformative. Chronic disease management, a massive cost driver for health systems, relies heavily on patient self-management and adherence. An autonomous platform could orchestrate a deeply personalized support journey for a diabetic patient, delivering tailored dietary tips, medication reminders that adapt to the patient's daily schedule, and alerts based on glucose monitor readings, all while maintaining a consistent and encouraging dialogue.

This technology could also revolutionize preventative care and population health initiatives. Instead of generic flu shot reminders, a health system could deploy AI agents to identify at-risk populations based on demographic and historical health data, then craft culturally-sensitive and highly relevant messages to encourage vaccination. The platform's ability to instantly generate message variations and tailor content for different segments would allow providers to move beyond one-size-fits-all communication, addressing the specific barriers and motivators of diverse patient communities.

By automating this complex orchestration, these platforms promise to free up overburdened clinical and administrative staff. Instead of manually managing outreach lists and sending bulk messages, care managers could transition into a role of strategic oversight—defining the clinical goals, setting the guardrails for the AI, and intervening only when a human touch is necessary. This allows healthcare organizations to scale high-touch engagement models that were previously too resource-intensive to be feasible.

Navigating the Competitive and Ethical Minefield

Comviva is not alone in this race. The MarTech industry's giants are all making aggressive plays. Salesforce's Einstein GPT and Adobe's Sensei GenAI are already being integrated into their respective clouds, offering similar capabilities for automated content generation and journey personalization. The competitive pressure ensures this technology will become more accessible and powerful at a rapid pace. However, its application in healthcare introduces a unique set of ethical and regulatory challenges that demand extreme caution.

Data privacy is paramount. While MobiLytix leverages a “live 360° customer profile,” a similar patient profile would involve Protected Health Information (PHI), governed by stringent regulations like HIPAA. Any platform used in this capacity must demonstrate enterprise-grade security and an architecture that ensures strict compliance. The risk of a data breach is not just financial; it's a catastrophic erosion of patient trust.

Furthermore, the “black box” problem of AI—where it is difficult to understand why a model made a certain decision—is particularly dangerous in a clinical context. If an AI agent de-prioritizes follow-up communication for a certain patient demographic due to biases learned from historical data, the consequences could be life-threatening. Algorithmic bias could lead to the unintentional neglect of already underserved populations, widening existing health disparities. Robust governance, continuous auditing for fairness, and a 'human-in-the-loop' approach with clinical oversight are not optional features; they are fundamental requirements for responsible implementation.

The very concept of “autonomy” must be redefined for healthcare. While an AI agent can operate with a degree of independence in a retail setting, in healthcare it must always function as a tool under the direct supervision of a clinical strategy. The goal is not to replace care providers, but to augment their ability to connect with patients at scale.

Ultimately, the arrival of autonomous engagement platforms marks a pivotal moment. It pushes the boundary of how healthcare organizations can build and maintain patient relationships. These AI-driven systems offer a tantalizing glimpse into a future of proactive, continuous, and deeply personalized patient support. If deployed with rigorous ethical oversight and a steadfast focus on patient well-being, this disruption from the world of marketing technology could provide a powerful new instrument for building a more efficient, resilient, and patient-centered healthcare system.