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THRIVE™ · VALUE

Individual AI projects succeed. AI programmes fail.

Sustainable AI adoption requires strategic intent, investment, governance, and operational coherence. Value readiness assesses whether your institution can make AI work as a programme rather than a series of disconnected pilots.

Assess your readiness

Healthcare organisations run AI pilots. Some succeed. None scale. The pattern repeats because the problem was never the pilot — it was the absence of strategic alignment, governance structures, evidence standards, and workflow integration required to sustain AI beyond the champion who ran the pilot. When that person leaves, the programme collapses.

The question isn’t whether AI can work. It’s whether your organisation is structured to make it work — repeatedly, sustainably, at scale.

THRIVE™ Value assessment evaluates your leadership alignment, governance structures, vendor evaluation capability, investment readiness, evidence maturity, and operational scaffolding — the programme-level infrastructure that determines whether AI scales or stalls.

What we assess

Core capabilities

01

Multi-Level Organisational Alignment

EXPANDED

Shared understanding of AI strategy spanning executive leadership, middle management, clinical leads, and operational staff.

IAEAFDA
02

AI Governance Structure

Formal committees, policies, accountability frameworks, and oversight mechanisms for AI adoption and incident response.

IAEAWHOREADI
03

Vendor Evaluation Capability

Structured capacity to assess AI products critically before procurement across technical, clinical, regulatory, and commercial dimensions.

IAEA
04

Investment Readiness

Budget allocation clarity, cost modelling, and business case maturity to sustain AI programmes beyond initial deployment.

IAEA
05

Clinical Evidence Maturity

Institutional standard for requiring real-world outcome evidence, not just regulatory clearance, before committing to AI deployment.

FDAWHOREADI
06

Procurement Lifecycle Readiness

Structured approach to vendor selection, contract design, service level management, and end-of-life provisions.

IAEAFDA
07

Vision Clarity

Defined institutional goals for AI beyond pilot with a credible roadmap, measurable outcomes, and clear accountability.

IAEAWHO
08

Performance Metrics Definition Capability

Capability to define clinically appropriate performance thresholds for each AI use case before procurement.

IAEAFDA
09

Workflow Integration

MOVED

Degree to which AI systems fit within established clinical processes and documentation workflows.

IAEAREADI
10

Change Management

MOVED

Organisational capacity to plan, communicate, and sustain practice changes that AI deployment requires.

IAEAREADI
11

Clinical Champions

MOVED

Presence of engaged internal advocates with credibility and authority to drive AI adoption.

IAEA
Platform integration

How Value connects

THRIVETHRIVE
V ↔ T

Vendor evaluation capability (V) depends on technical readiness (T) to set evidence standards. Without T, procurement defaults to vendor assertions.

V ↔ H

Organisational alignment (V) without human readiness (H) means mandating AI use by a workforce that isn’t equipped for it.

V ↔ R

Procurement lifecycle readiness (V) must encode regulatory obligations (R) into contracts — not just functionality requirements.

Evidence base

What the literature says

“The clinical benefits and risks related to the product are well understood, used to derive clinically meaningful performance goals for testing, and support that the product can safely and effectively achieve its intended use.”

— FDA, Good Machine Learning Practice (2021)

“Appropriate regulatory oversight mechanisms must be developed to make the private sector accountable and responsive to those who can benefit from AI products and services, and can ensure that private sector decision-making and operations are transparent.”

— WHO, Ethics & Governance of AI for Health (2021)

“While bringing potential benefits to healthcare, the application of AI systems also introduces new challenges and potential risks.”

— IAEA PC9134 (2025)
FAQs

Common questions

Executive sponsorship is necessary but is one of eleven dimensions. Most AI programme failures aren’t caused by lack of leadership support — they’re caused by the absence of governance structures, evidence standards, procurement discipline, and clinical champion networks that translate sponsorship into sustained operational change.

Because it spans both strategic alignment (vision, governance, investment) and operational execution (workflow integration, change management, clinical champions). Most frameworks separate these. THRIVE™ combines them because strategy without operational scaffolding is just a presentation — and operations without strategy is just a series of unconnected pilots.

Investment readiness is one of eleven dimensions, not the dominant one. The more common failure mode isn’t underfunding — it’s funding AI without the governance, evidence standards, or operational infrastructure to make that investment translate to clinical benefit.

Ready to assess your Value readiness?

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