As any sports professional will tell you, success depends on anticipating where the receiver will be, not where they are now. The same applies to healthcare technology leadership. CIOs and CTOs must anticipate where innovation will intersect with patient needs and business goals, especially as personalized healthcare gains momentum.
This blog explores how healthcare leaders can prepare for the next 2–5 years, when personalized health technologies are expected to reach mainstream adoption. It outlines key enablers such as AI, data integration, and consent management, and emphasizes the importance of building a well-structured data infrastructure and privacy-first culture. It also recommends starting with low-risk, high-impact pilots to test systems and processes before scaling.
Ultimately, success will depend on a healthcare organization’s ability to balance innovation with trust delivering personalized care while protecting patient data through clear consent, strong governance, and scalable privacy programs.
Jump to:
- Understanding the technology lifecycle
- What is personalized healthcare?
- Key enablers of personalized healthcare
- Laying the foundation
Understanding the technology lifecycle
There are several frameworks that attempt to define the technology lifecycle and, using that lifecycle definition, track and predict technology. One of these frameworks is the Gartner Hype Cycle, which breaks out the technology lifecycle into these phases:
- Innovation trigger – the technology breakthrough that “kicks things off.”
- Peak of inflated expectations – early publicity with some, but not a lot of adoption.
- Trough of disillusionment – a dip in interest due to early failures.
- Slope of enlightenment – additional successes that lead to more funded pilots, with conservative companies still holding off.
- Plateau of productivity – mainstream adoption starts. Criteria for assessing vendors and technology and successes/applicability become clear.
In its recent Hype Cycle for Healthcare Providers, 2025, Gartner evaluated technology advancements related to healthcare operations and delivery of care according to this model, with interesting results. The whole report provides valuable healthcare technology insights and will be useful to read in total. However, following are a few key points for healthcare CIOs/CTOs to consider.
First, we should start with the assumption that a smart CIO/CTO will want to focus on high/transformative technology expected to reach the Plateau of Productivity within the next 2-5 years, given that it is too late to do much proactive thinking about those technologies that have reached/will reach the Plateau stage prior to that. Gartner suggests that, in the healthcare arena, the technologies that match up with these criteria include those centered around personalized healthcare.
What is personalized healthcare?
Personalized healthcare is “an overarching framework for proactive, personalized health care that provides individuals with a personal health plan to maximize their health and minimize disease. It utilizes predictive technologies to establish each individual’s health risks and facilitates patients’ engagement in their health along with the development of plans and a care delivery system designed to achieve the best health outcomes.” This approach revolves around each individual patient, anticipating and coordinating solutions to needs. Personalized health incudes proactive consideration of health and preventative measures in addition to reactive illness-driven activities.
Key enablers of personalized healthcare
Artificial Intelligence
AI enables real-time personalization, predictive insights, and automated workflows. It can power hyper-personalized patient portals, assist in care coordination, and trigger secondary processes based on complex rules.
However, AI also raises challenges around data privacy, quality, and security. These must be addressed early to ensure trust and compliance.
Integration, data sharing, and consent
Personalized care requires seamless data exchange across systems, apps, and organizations. But integration is a trust challenge as well as a technical challenge.
To earn and maintain that trust, organizations must:
- Implement robust consent and preference management systems
- Ensure patients can easily understand, grant, and manage their data sharing preferences
- Operationalize those consents across internal systems and external partners
This is where a Consent Management Platform (CMP) becomes essential – whether vendor-provided or homegrown. It must handle high volumes of granular, patient-specific consents and preferences, and ensure they are respected across the care ecosystem.
Laying the foundation
Build the right data and technology infrastructure
Investing now in the right data fabric and health data platform architecture will help a healthcare CTO/CIO be ready for that rapidly approaching 2-5 years window for personalized heath. This means carefully considering what the end-to-end structure will look like and how those components and layers will talk with one another. It also means investing in the data hygiene, accessibility, governance, integration, and management that make a sound data fabric possible.
Establish privacy and consent a non-negotiable requirement
Trust is the cornerstone of personalized healthcare, especially when sensitive data, AI, and cross-system data sharing are involved. For healthcare organizations, this means treating privacy and consent not as checkboxes, but as foundational principles.
Patients must be able to easily understand what data is being collected, how it will be used, and who it will be shared with. This requires:
- Transparent, user-friendly consent notices
- Mechanisms for patients to express and update their preferences
- Operational systems that respect and enforce those preferences across all touchpoints
Consent isn’t static. It must be actively managed across a complex, multi-entity environment. Healthcare organizations need to:
- Capture and store granular, patient-specific consents
- Apply those consents consistently across internal systems and external partners
- Exchange consent-related instructions with other entities in the care network
Given the individualized nature of personalized healthcare, the volume and complexity of consent data will grow significantly. Organizations should prepare now by implementing a Consent Management Platform (CMP) to handle this scale.
Beyond external consent, internal privacy controls are essential. Organizations must establish:
- Privacy review boards and Data Protection Impact Assessments (DPIAs)
- Documented policies and procedures for data handling
- Third-party risk management practices
- Privacy-by-design principles embedded in system development
- Ongoing staff training and awareness programs
In short, a healthcare organization preparing for personalized health must build a mature, scalable privacy program – one that supports both regulatory compliance and patient trust.
Start with low risk, high impact use cases
Finally, a phased approach to personalized health can be useful. To test out the integration, privacy, and other complex components, a company may wish to begin with early pilots using minimal risk (non-sensitive data, less complicated integrations) but high impact test cases. This launch-and-learn philosophy can help an organization smooth out any wrinkles without causing key issues.
Summary
Personalized health is a high-impact opportunity on the near horizon. To be ready, healthcare CIOs and CTOs must:
- Build a flexible, integrated data infrastructure
- Prioritize privacy, consent, and preference management
- Start with manageable pilots to refine and scale
By acting now, healthcare leaders can ensure they’re not just keeping up but leading the way.
