In March 2026, Singapore's Ministry of Health and Health Sciences Authority released the revised Artificial Intelligence in Healthcare Guidelines (AIHGle 2.0), providing updated regulatory and governance frameworks for AI-enabled medical technologies. The guidelines offer practical clarity on when AI solutions qualify as medical devices requiring registration under the Health Products Act 2007, addressing ambiguities that have emerged since the first guidelines were published in 2021.

This update arrives alongside HSA's recognition by the World Health Organization as having achieved Maturity Level 4—the highest classification for national regulatory authorities overseeing medical products—making Singapore the first WHO Member State to reach this level for medical device regulation. For healthtech companies, investors, and healthcare providers across Southeast Asia, these developments signal that regulatory clarity is no longer aspirational but operational, shaping where companies choose to develop, test, and scale AI healthcare solutions.

Eric Lai, Managing Director & Founder of Elix Law, shares insights into how these regulatory developments are influencing healthtech investment appetite, what liability and compliance concerns businesses are prioritising when deploying AI-driven tools, and why regulatory clarity has become a decisive factor in determining Singapore's role as a regional launchpad for healthcare innovation.

ALB: How are Singapore's updated AI healthcare guidelines shaping investment appetite for healthtech in Southeast Asia?

Eric Lai: The revised Artificial Intelligence in Healthcare Guidelines ("AIHGle 2.0"), released in March 2026 by the Singapore Ministry of Health and the Health Sciences Authority ("HSA"), provide timely clarification on regulatory and governance considerations arising from AI developments since the first guidelines were published in 2021.

Notably, AIHGle 2.0 provides practical examples distinguishing AI solutions that are regulated as medical devices under the Health Products Act 2007 from those that are not – for example, a transcription tool that generates diagnoses or treatment recommendations is classified as a medical device, while the same tool without that function is not. This clarity is significant for early-stage companies, because classification drives the entire regulatory timeline – it determines whether a product requires HSA registration. Founders can now scope their products and regulatory strategy with greater clarity, which accelerates the go-to-market process and makes these companies more attractive investment or acquisition targets. It signals that Singapore's regulators intend to support deployment alongside putting up constructive guardrails.

The guidance provided by AIHGle 2.0 across an AI solution's entire life cycle – from planning and development to end of life – allows investors to price regulatory risk with greater certainty. That matters, because applying complex frontier technologies such as machine learning and deep learning to healthcare carries amplified risks given their complexity, opacity and scalability.

We expect this to drive greater integration of AI solutions into healthcare services and correspondingly stronger investment appetite for them. In particular, we expect to see more early-stage healthtech companies seeking Singapore regulatory clearance as their first commercial milestone before pursuing regional and global expansion, alongside rising M&A activity as established healthcare players acquire AI capabilities.

ALB: What are the key regulatory and liability concerns when deploying AI-driven healthcare tools?

Eric Lai: A threshold question we frequently receive from clients concerns classification – whether their AI-enabled solution is a medical device requiring registration with HSA, or whether it falls outside the ambit of the Health Products Act 2007. This is not always straightforward given how rapidly AI-enabled solutions are evolving. Determining the correct classification early is a key priority, because it dictates the applicable regulatory framework, including deployment timelines, validation standards and ongoing obligations.

Liability allocation is another major concern. AIHGle 2.0 clarifies the respective responsibilities of developers, deployers and users – a welcome development – but in practice much still turns on the contractual arrangements between the parties. A key consideration is where liability sits when a healthcare professional relies on an AI recommendation that proves incorrect. Vendors typically prefer broad disclaimers, while users often insist on indemnities. Underlying all of this is patient confidence. Adoption ultimately depends on patients trusting that someone remains accountable when things go wrong. Contracts, however, can only go so far – healthcare professionals remain accountable to their patients regardless of any AI involvement, and statutory obligations sit with the regulated party.

Compliance with the Personal Data Protection Act 2012 is a further key consideration, given that data processing is central to AI-enabled solutions. AIHGle 2.0 encourages developers to collaborate with relevant stakeholders from the outset to define intended use cases, validate the relevance and fairness of training datasets, and set performance benchmarks. This early collaboration serves a legal function as well as a technical one – whether the inclusion of personal data in training data sets is reasonably appropriate and necessary, and on what consent basis it may be used.

ALB: How important is regulatory clarity in determining whether companies choose Singapore to develop and scale AI healthcare solutions?

Eric Lai: In our experience, regulatory clarity ranks among the top considerations, often the decisive one, especially where healthcare intersects with frontier technology.

Healthtech and AI-enabled healthcare companies selecting a regional base are typically assessing where they can obtain a credible regulatory approval and leverage that approval in other markets as part of their expansion plans. A clear, healthcare-focused AI regulatory framework allows them to undertake meaningful risk assessments to better formulate their commercial and expansion strategy.

The Singapore Health Sciences Authority's ("HSA") recognition by the World Health Organization ("WHO") in March 2026 as having achieved Maturity Level 4 – the highest classification in WHO's system for national regulatory authorities overseeing medical products – is significant. Singapore is the first WHO Member State to attain this level for medical device regulation. This positions HSA as a global reference point for other regulators. An AI solution developed and tested in Singapore and approved by HSA is likely to be viewed favourably by regulators in other jurisdictions, potentially smoothing the path to approval in subsequent markets.

Regulatory clarity can also accelerate user adoption. The purchasers of AI healthcare solutions are often healthcare institutions, which are understandably cautious about deploying such tools if liability and other obligations are uncertain. AIHGle 2.0 addresses this by setting out what is expected of deployers – governance structures, pre-deployment validation, staff training and monitoring – giving institutions greater confidence to procure and deploy. For solution providers, this potentially translates into shorter sales cycles and an earlier clinical track record. A solution proven in Singapore's tightly governed regulatory environment is likely to carry weight with other stakeholders across the region. Regulatory clarity creates the conditions for greater adoption and scale-up.

Author: Eric Lai

This publication was originally published at: https://www.legalbusinessonline.com/other-news/friday-debrief-redefining-healthcare-horizons