Report

Health and life sciences

Delivering on the Promise of Intelligent Health

Health and life sciences organizations that secure their data foundations, unify fragmented patient journeys, and prove every AI promise with measurable outcomes will set the standard for care delivery — and capture the trust, funding, and market position that follow.

01 The State of the Market
02 Anchoring Brand Credibility in Transparency and Results
03 Designing Journeys as Seamless as Consumer Tech
04 Securing the Data Foundations Before Deploying AI
05 Conclusion

The State of the Market

An industry with strong potential, but under pressure

Rising costs, a shortage of human resources, and intensifying demand — the picture for health and medical research could easily look bleak. Yet the sector attracts a significant share of global investment, and the resources committed to digitalization are substantial.

So why does transformation remain so difficult, despite proven potential and needs that will only grow?

Incomplete transformation cycles are wearing organizations down

More than 40% of healthcare professionals in the United States and Europe are approaching or reaching retirement age: the shortage ahead makes the automation of repetitive tasks urgent.

The industry is attempting to address its structural challenges through innovation, but suffers from a lack of methodology in deployment — straining professionals and eroding patient trust.

35% of executives warn that organizational fatigue from successive transformations will slow their capacity to change, up from 28% the year before.

The problem is therefore not only technical: its causes and consequences are equally organizational and human.

In a sector where a growing share of payments and reimbursements are tied to outcomes, these gaps can quickly become a major strategic risk.

The impact on patients is equally real: a newly diagnosed cancer patient in the United Kingdom currently has a one-in-three chance of waiting longer than clinical guidelines recommend before beginning treatment. In France, 73% of patients report having foregone at least one medical procedure in the past five years due to delays, care pathway complexity, or cost.

Three recurring failures stand out across the sector: Investing in AI before stabilizing infrastructure, rethinking the experience before connecting the systems that underpin it and making brand promises the technology cannot yet fulfill.

At AREA 17, we approach these challenges as a unified system across three levels: the brand and its positioning in the industry, the user experience across channels, and the technological and organizational foundations that make it possible.

Anchoring Brand Credibility in Transparency and Results

AI-related promises erode the trust of patients and clinicians when they are not accompanied by concrete, measurable results. 48% of patients would be willing to share their data to improve their care — on one condition: transparency and security.

Without transparency on an ethical and secure approach to AI, adoption stalls, patient follow-up deteriorates, and research quality suffers as well.

Inconsistent brand expression and the absence of tangible proof remain the primary obstacle cited by 68% of healthcare marketing professionals.

But in a context where 35% of Medicare Advantage spending in the United States already flows through outcomes-based models, and where 83% of insurers anticipate further growth of these models, the inability to demonstrate impact becomes a financial risk as much as a reputational one.

Credibility cannot be declared — it must be demonstrated.

Every promise must be proven, and therefore measured, across accessibility, cost, and clinical outcomes. Transparency on data use is no longer a compliance detail: it is a lever for adoption and capital attraction.

Key takeaway

Consistent brand expression, data transparency, and access to concrete evidence across all channels are no longer optional. They are conditions for the engagement of patients, clinicians, partners, and investors.

Designing Journeys as Seamless as Consumer Tech

The industry faces a growing gap between patient expectations and what organizations are able to offer.

A majority of patients are open to teleconsultation and online portals for managing common conditions, yet only 36% of organizations offer self-service beyond appointment booking.

Yet 48% of those that have deployed digital monitoring and consultation tools report better patient adherence to treatment. The result: in the United States, only 32% of patients report feeling adequately cared for — a drop of 10 points since 2021.

While 72% of sector executives name improving the patient experience as their top priority, the gap between intention and lived reality has never been wider, driven by fragmented journeys and accumulating delays: patients today spend only one third of their care journey in direct interaction with a physician.

To be adopted and functional, digital care journeys must reach the level of seamlessness already offered by consumer technology.

They must also be designed so that AI handles routine interactions without removing control from patients or clinicians. Multiple portals and overlapping channels, when disconnected, reduce engagement and damage patient follow-up and research progress. Worse, they exclude those with lower digital literacy. Health must be inclusive.

Key takeaway

The organizations that stand out replace layered systems with a small number of coherent journeys by profile — patients, clinicians, investigators — powered by shared data platforms.

Securing the Data Foundations Before Deploying AI

While lack of resources is cited as the primary barrier to adopting new technologies, the health industry paradoxically remains the least likely to direct its technology investments toward problems identified by patients and teams — 35%, compared to a 44% cross-sector average.

57% of health executives report that failures in their core systems disrupt operations every week. One reason is straightforward: only 18% of organizations have deployed a unified data platform at enterprise scale, making any meaningful agility impossible.

Governed and interoperable “by design” foundations are imperative: AI deployed on fragile infrastructure amplifies problems rather than solving them.

Without clear governance over particularly sensitive data, patient trust and brand credibility are also at stake.

Key takeaway

Organizations building lasting advantage do not launch new AI pilots without a funded modernization roadmap and a secure architecture. Not the other way around.

Conclusion

The sector is at a tipping point: costs are rising, clinicians are burning out, and AI pilots are adding weight to organizations rather than relieving it. The organizations that clean up their systems first earn the trust of patients, investors, and partners — a position their competitors will soon find difficult to close.

At AREA 17, we combine strategy and craft to help health and life sciences organizations create lasting value across these three levers:

Turning every innovation promise into a demonstrable outcome — by linking every AI commitment to a measurable impact, and making data transparency the foundation of trust.

Designing intelligent, continuous care journeys — by integrating portals, applications, connected devices, and in-person care into a coherent experience where each interaction strengthens the next.

Deploying AI on stable, secure, and interoperable foundations — by laying the groundwork first: unified data, governance, security by design — so that AI relieves constraints rather than compounding them.

Facing these challenges? We'd love to talk.