AI & Digital Health

AI & Digital Health

Artificial intelligence has entered the clinical core of healthcare, changing how disease is detected, how medicines are discovered and how care is delivered outside the hospital. This sector examines where capital is flowing across diagnostics, clinical software, drug discovery and remote monitoring.

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Adoption Now Turns on Evidence

The constraint on digital health is no longer technical. Wearables, imaging archives, electronic records and multi-omic datasets allow a patient to be modelled over years rather than at a single appointment, and the models reading them are moving from demonstration into procurement. What separates a funded platform from a stalled one is clinical validity and a reimbursement route. Capital is concentrating where both can be documented.

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Key Thematic Areas

• AI-assisted diagnostics and medical imaging
• Clinical decision support at the point of care
• AI in molecule design and trial simulation
• Digital twins and in-silico modelling
• Remote patient monitoring and virtual wards
• Workflow automation and clinical documentation
• Health data infrastructure and governance

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Features & Activities

• Deal Room – structured negotiation of licensing, distribution and deployment agreements for clinical-grade software.
• Clinical Validation Panels – regulators, clinicians and developers on the evidence needed to move an algorithm into routine care.
• Technology Demonstrations – live showcases of diagnostic, monitoring and discovery tools already in clinical use.
• Policy Roundtables – closed-door discussions on approval pathways, liability and cross-border health data rules.
• Closing Declaration – a collective statement on the standards required for safe deployment of clinical algorithms.

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Who Will You Meet?

• Regulators and health technology assessment bodies
• Chief medical information officers and clinical IT leads
• Payers, insurers and reimbursement decision-makers
• Medical imaging and device manufacturers
• Corporate venture arms and specialist health technology funds
• Clinical AI founders, researchers and data scientists

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The Future of Digital Health Investment

• Scale of the Opportunity – analysts broadly expect the market for AI in healthcare to multiply several times over within the coming decade.
• Shorter Discovery Cycles – machine learning in target identification and trial design is compressing the costliest stages of drug development.
• Care Moving to the Home – continuous monitoring shifts spending from acute facilities toward prevention and community care.
• Sovereign Data Programmes – national investment in secure health data infrastructure is enabling deployment at population scale.
• Consolidation by Incumbents – providers, insurers and pharmaceutical groups are buying capability rather than building it.
• Assurance and Liability – model monitoring, audit and indemnity are forming a service market of their own.

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Key Benefits

• Evidence Partners – engagement with health systems prepared to host validation studies and commercial pilots.
• Regulatory Clarity – first-hand guidance from the authorities shaping approval and data governance frameworks.
• Payer Access – direct contact with the insurers and public purchasers that decide what gets funded.
• Market Intelligence – the Forum's annual signature report on where health technology capital is moving.
• Adjacent Capital – exposure to biotechnology, diagnostics and infrastructure investors convened on the same agenda.