AI, robotics & blockchain: ​​​Key investment considerations​

Key takeaways:

• AI, robotics and blockchain are influencing parts of healthcare as providers explore tools for diagnostics, surgery, data management and operational efficiency, but adoption remains uneven.
• Innovation matters because healthcare systems face ageing populations, chronic disease, workforce pressure and rising costs, creating demand for scalable tools that may support care delivery.
• AI is being used in some healthcare settings for image analysis, triage, workflow planning and drug discovery, though outcomes depend on data quality, clinical validation, reimbursement and adoption.
• Robotics can support surgery, rehabilitation, logistics and care tasks, while blockchain is being explored for patient records, pharmaceutical supply chains, claims processing and data integrity.
• Healthcare tech investment considerations include clinical uncertainty, regulation, ethics, integration costs, reimbursement models, public funding and system readiness.

Healthcare is no longer just about doctors, hospitals, and pharmaceuticals. It is becoming a sector increasingly influenced by data and technology, where algorithms assist in diagnostics, robotic arms carry out surgeries, and decentralised systems are being explored for patient data management in some settings. These developments are influencing parts of care delivery and attracting investor attention.

From imaging tools trained on millions of scans to blockchain platforms ensuring patient data integrity, digital tools are being adopted across parts of healthcare, although adoption remains uneven. And as public systems struggle with rising costs, ageing populations, and workforce strain, demand for some tech-enabled solutions is growing, though adoption and revenue models vary by country and provider.

Why innovation matters in healthcare today

Healthcare systems are under increasing pressure. Ageing populations, rising rates of chronic disease, and widespread workforce shortages are straining capacity and resources. At the same time, costs are mounting, both for providers and for governments tasked with maintaining public health infrastructure.

Innovation is no longer a future-facing concern. It is becoming central to how modern health systems operate. Technologies designed to support diagnostics, treatment coordination and administrative workflows are gaining attention. Tools that once belonged in research labs, like AI-enabled triage or predictive analytics, are now being deployed in some hospitals and clinics.

From an investment perspective, this shift may create new growth areas, but outcomes depend on regulation, reimbursement, and implementation. Companies offering tools aimed at addressing inefficiencies in care delivery, resource management, or clinical operations are attracting attention in some markets The focus is shifting from pure scientific breakthroughs to practical, scalable solutions that help healthcare systems operate more efficiently.

AI and healthcare: From diagnostics to drug discovery

Core areas of healthcare already incorporate artificial intelligence:

• Some radiology teams use machine learning tools to support image analysis, although performance depends on clinical context, data quality and approved use.
• Chat-based triage tools may help route patients or collect initial information, depending on how they are designed and used.
• Behind the scenes, AI models are being used in some settings to support workflow planning and estimate bed demand.

These tools are not theoretical; they are in active use.

AI is also being used to support parts of drug discovery and development. Instead of testing thousands of potential drug formulas individually, machine learning may help identify candidates for further testing by analysing vast amounts of data. This approach may help prioritise candidates earlier, but development timelines remain uncertain and clinical validation still drives cost and time.

Interest in companies using AI in diagnostics, early-stage research, patient engagement, and operational efficiency is growing. With cost pressures rising, technologies that may support decision-making, targeting or workflow quality are attracting attention, but commercial success depends on validation, reimbursement and adoption.

Robotics in surgery and care delivery

Robotics in healthcare is now used in some hospitals and healthcare settings for surgeries, rehabilitation, and even logistics. In operating rooms, robots assist with precision tasks in orthopaedics, cardiology, and urology, which may support precision in certain procedures; outcomes such as blood loss or recovery time can vary by procedure, surgeon experience and patient factors.

Beyond surgery, robots support medication delivery, patient lifting, and guided physical therapy. Some hospitals also use automated systems to transport supplies and maintain hygiene, designed to reduce some manual tasks for clinical staff.

Investor interest is growing in companies that offer both robotic hardware and supporting software, although high costs, training needs and system integration can limit adoption. The focus isn’t just on surgical tools but also on robotics integrated with sensors, AI monitoring, and hospital IT systems.

However, scalability remains a challenge. Adoption of robotic technologies is more prevalent in well-funded urban centres, while factors such as cost, training requirements, and system integration pose obstacles in other regions.

Blockchain for data integrity, payments, and transparency

Healthcare systems rely on trust between patients, providers, and insurers. Blockchain is being explored as a way to support data integrity in some use cases by improving traceability and integrity in some designs, although privacy, governance and integration risks remain, and security depends on implementation. Unlike traditional databases, blockchain records are time-stamped, encrypted, and distributed across a decentralised network, making some changes easier to audit, depending on system design and governance.

One potential application is in patient record management. Blockchain-based systems could support permission-based sharing of medical data across hospitals, insurers, and clinics, although implementation varies. Blockchain in healthcare enables accurate, permission-based sharing. In theory, patients can gain greater control over who accesses their medical data and for what duration, although the actual implementation in practice still varies.

Blockchain is also being tested to track pharmaceuticals through supply chains, helping verify drug authenticity and reduce fraud. In insurance and billing, smart contracts could streamline claims by automating approvals and reducing disputes, although adoption is still in its early stages.

While several startups and large healthcare players are piloting blockchain solutions, regulatory frameworks, cost, and system integration remain barriers to widespread use. Still, the possible uses in data integrity, traceability and claims processing continue to attract research, pilots and investor attention.