Sciences et santé

Scaling intelligent health in constrained systems

Health and life sciences Market insight report Header

Executive summary

Health and life sciences organizations that unify patient journeys and prove outcome-based AI at scale will define how care is delivered, and capture the funding, trust, and market position that comes with it.

Challenges and opportunities arise at three levels:

Brand: Health and sciences organisations now must compete on proven outcomes, not promises. Trust grows when impact on access, experience, cost, and clinical results is demonstrated, and when data protection and usage transparency are treated as core to the brand.

Experience: Patients, members, and trial participants expect connected, consumer-grade experiences. Fragmented interactions must become continuous journeys, compounding value for people, teams, and organizations.

Technology: AI only scales on stable, interoperable foundations. Core systems and infrastructures must be stabilized; data unified and governance, security, and interoperability embedded from the start.

The market reality: Rising costs, clinician shortages, and AI pressure — all at once

Health and life sciences are facing a critical inflection point

Costs are rising and clinician shortages are growing.
Populations are aging and patient expectations are higher than ever.
AI, digital tools, and complex regulations are reshaping the industry.
Pressure to accelerate R&D and clinical trials without compromising safety or compliance is increasing.

Most leaders in Health and life sciences agree: AI and digital tools will reshape their organizations, but few have moved beyond pilots to enterprise-scale impact. Meanwhile, payers and health systems are accelerating the shift from volume-based to outcome-based reimbursement — raising the stakes for organizations that cannot yet measure or prove their impact.

The next wave of leaders will be those who turn transformation fatigue into momentum: connecting fragmented systems, earning patient trust through careful data handling, and designing experiences as seamless as consumer tech.

Capacity constraints stall digital progress before it starts

Healthcare leaders face a widening gap between digital ambition and their capacity to execute. This threatens patient outcomes, clinician experience, and competitive position.

73% of healthcare technology leaders say capacity constraints are the top reason they hesitate on new tech investments—9 points above the cross-sector average.
57% report that flaws in foundational systems disrupt daily operations every week.
35% warn that transformation fatigue will slow their digital agenda, up from 28% last year.

When systems can't absorb innovation, patients, clinicians, and market position all suffer

When capacity is limited, innovation stalls. Patient trust suffers. Clinician morale drops. Market share declines. More than 40% of healthcare professionals in regions like the US and Europe are at or near retirement age, and shortages in primary care and key specialties are looming. Organizations that fail to automate repetitive tasks and stabilize core systems will fall behind competitors who do.

Here’s the hard truth: adding more AI pilots, digital tools, or experience layers without fixing core capacity first usually makes things worse, not better. The clock is ticking—AI-driven efficiency and interoperable platforms are moving from “nice-to-have” to essential requirements.

Most organizations don’t fail because they lack ideas. They fail because brand, experience, and technology decisions happen in isolation—compounding capacity constraints instead of relieving them.

Read on to explore how health and life sciences organizations can align brand, experience, and technology to overcome these challenges.

The new brand imperative: Move from innovation claims to proven results

The challenge: AI promises without measurable outcomes erode patient trust and clinician confidence

Many healthcare brands lead with bold “AI-powered” or “digital-first” claims without connecting them to measurable results. But generic narratives of “innovation” risk disengagement and make partnerships and cross-organizational initiatives harder to execute.

When brands make promises that outpace experience or technology, it erodes patient trust and clinician morale, and reduces retention. This makes both patients and providers increasingly skeptical. Since trust is no longer assumed, it must be earned through demonstrated impact on access, efficiency, cost, and health outcomes.

Globally, 48% of consumers would share personal health data to improve care, and 38% to receive tailored services, but trust hinges on transparent data use.
68% of healthcare marketers cite maintaining a consistent brand voice across channels as the top barrier to conversational engagement.
In 2024, 35% of Medicare Advantage and 24% of Medicare fee-for-service spending already flowed through alternative payment models.
83% of insurers and health systems anticipate alternative payment model activity will increase; 96% agree it will lead to higher-quality care.

Solutions to explore

From features to outcome-driven stories

Health brands must connect messaging to measurable results: shorter wait times, better adherence, fewer readmissions. Use real-world evidence and testimonials. Move from “we built this” to “this delivered X% improvement for Y patients.” In life sciences, organizations need to tie narratives to clinical evidence and real-world outcomes. This is no longer just a trust issue, but also a financial one as reimbursement models increasingly reward demonstrated outcomes over activity.

Data protection as a brand foundation

Transparency builds loyalty and engagement. Organizations must clearly communicate how patient data is used, protected, and contributes to better care, and address AI explainability, bias mitigation, and privacy.

Brand as ecosystem coordinator

The strongest healthcare brands position themselves as coordinators, not isolated product sellers. Brand narrative should emphasize connecting patients, providers, insurance companies, devices, and data, to enable continuous, seamless care experiences.

What should leaders do next?

Ensure that every major innovation claim is backed by at least one measurable outcome and explicit commitment to responsible data management. Identify two or three partners across the care ecosystem and make those relationships visible in brand communications, not just in strategy documents.

The new experience imperative: Turn fragmented interactions into continuous care journeys

The challenge: Episodic, fragmented touchpoints slow down outcomes and drive patient frustration

Patients now expect experiences like consumer tech: seamless, omnichannel, personalized, and proactive. Yet healthcare delivery remains fragmented. Episodic touchpoints fail to anticipate needs, and digital portals, apps, and telehealth tools often function as bolt-ons, creating friction and inequity, especially for patients with lower digital literacy or access.

Fragmented experiences slow down diagnosis-to-treatment timelines, reduce adherence, and increase patient frustration. They also overload clinicians and investigators who struggle with multiple logins, inconsistent interfaces, and disjointed reporting.

Only 32% of US patients feel cared for after their last interaction—a drop of 10 points since 2021.
72% of global healthcare leaders list “improve consumer experience, engagement, and trust” as a top priority.
Only 36% of healthcare organizations offer self-service beyond basic scheduling, though 48% report improved adherence using conversational UIs.
In the UK, newly diagnosed cancer patients starting treatment within two months fell from 85% to 65%, leaving ~100,000 patients waiting longer than they should.
Across the US, UK, Germany, China, India, and Brazil, ~25% of consumers avoid care due to cost or hassle
Patients spend only about 1/3 of their healthcare time actually interacting with a doctor.
47 to 83% of patients in these countries are open to telehealth or online portals for chronic disease management, checkups, or common mild illnesses.

Solutions to explore

Journey design across "find care, get care, stay well"

Map and optimize end-to-end patient journeys—not isolated interactions. Integrate digital tools (portals, apps, wearables, telehealth) with in-person care. Use data to anticipate needs and trigger timely touchpoints. For example, AI can identify cardiac patients at risk and proactively deliver coaching and medication reminders. Scaled digital solutions for triage, scheduling, and care coordination can reduce backlogs and unlock system-level efficiency.

Personalized, loyalty-style engagement

Move from reactive care (“come when you’re sick”) to proactive care (“we reach you before issues escalate”). Unified patient data enables tailored content, wellness programs, and incentives—similar to retail loyalty programs. Patients who feel understood are more likely to adhere to treatment and stay loyal.

Multi-channel accessibility and equity

Digital transformation risks increasing health inequalities. People with low digital skills, limited internet access, or disabilities can get left behind. Combine virtual, in-person, voice-assisted, and community health worker touchpoints. Follow accessibility standards (e.g., WCAG) and inclusive design for every interaction.

What should leaders do next?

Consolidate overlapping digital entry points into a small number of journey-based “front doors” for each key stakeholder group—patients, members, clinicians, investigators, and trial participants. Back these with shared data and experience platforms, rather than separate, bespoke systems for every use case.

The new technology imperative: Secure and unify your data foundations first, before AI adds risk

The challenge: Layering AI onto fragmented, insecure systems adds operational risk instead of relieving capacity

Healthcare infrastructure often lags other industries. Many organizations still rely on manual workflows and fragmented platforms that don’t communicate. Small AI experiments are often layered on top of these unstable systems without coherent architecture, governance, or funding. Security is treated as an afterthought, leaving organizations vulnerable to ransomware, attacks, and breaches.

Meanwhile, cloud-native HealthTech and life sciences companies face the same challenge: connecting securely to diverse hospital systems and reusing fragmented data across studies and therapeutic areas.

The result: poor ROI, limited impact, and tech that adds operational and cybersecurity risks rather than freeing up capacity.

Only 18% of healthcare organizations have rolled out a company-wide Customer Data Platform.
57% of healthcare tech leaders report that flaws in enterprise IT systems disrupt operations weekly.
Healthcare is the sector least likely to target tech investments at the highest pain points identified by customers and employees (35% vs 44% cross-sector average).
66% of healthcare tech leaders report generating value from AI use cases, but deployments are often ad hoc and not yet delivering full returns

Solutions to explore

Modernize data and core infrastructure first

Consolidate and clean data, integrating EMRs, claims, wearables, and genomics into unified platforms. Ensure robust governance, privacy controls, and interoperability. Cloud migration enables the computing power, storage, and elasticity required for AI at scale, but must be paired with clear regulatory guidance on data security and cross‑border data use.

DevSecOps and security-by-design

Embed security from day one. Use DevSecOps frameworks to integrate security into every stage of development, minimize vulnerabilities, accelerate release cycles, and build cyber resilience. Include vendor security criteria, regular audits, and centers of excellence.

AI for operational efficiency and clinical advantage

Deploy AI strategically to automate repetitive back-office tasks (claims, scheduling, transcription) and enhance clinical care (diagnostics, predictive risk scoring, personalized treatment). Clinicians and staff should be trained to use AI as an assistant, not a replacement. Clear guidance on AI’s role, limits, and oversight ensures adoption, strengthens patient trust, and turns AI into a scalable competitive advantage.

What should leaders do next?

Pause new AI pilots that sit on unstable, non-interoperable systems. Only scale AI once there is a funded modernization roadmap and a security-by-design architecture that can support long-term growth.

AREA 17 helps you face this new paradigm

Healthcare is at a breaking point: costs are rising, clinicians are exhausted, and AI pilots are adding burden rather than relieving it. The organizations that heal their own systems first will earn the trust of patients, payers, and partners that competitors will struggle to displace.

The ones getting there are those that align brand, experience, and technology as one system — competing on proven outcomes rather than innovation claims, designing continuous care journeys instead of fragmented touchpoints, and securing their foundations before scaling AI rather than the other way around.

AREA 17 combines strategic consulting with hands‑on product development, working with health and life sciences organizations to think, design, and build the platforms that:

Turn innovation claims into outcome-driven brands: connecting every AI and digital promise to measurable impact in matters of access, efficiency, cost, and clinical results, and using data stewardship and real-world evidence to establish the foundation of trust.

Transform fragmented touchpoints into continuous care journeys: Designing end-to-end patient experiences that integrate portals, apps, wearables, and in-person care, replacing episodic interactions with proactive, loyalty-building engagement that compounds value for patients, clinicians, and organizations.

Scale AI on stable, secure, interoperable infrastructure: Modernizing fragmented data platforms and embedding governance, security, and interoperability from day one, enabling AI to relieve capacity constraints rather than adding operational burden.