Telehealth services are seeing a major shift in the Asia-Pacific (APAC) region, with artificial intelligence playing a central role. From automated patient monitoring to real-time diagnostics, AI addresses critical healthcare challenges across clinical practices. But how instrumental is AI in helping improve patient outcomes in the region, and where do APAC countries stand in its implementation?

The state of telehealth in APAC

With the APAC telehealth industry reaching $8.07 billion in 2024 and forecast to grow at a compound annual growth rate of 18.1 percent through 2030, the stage is set for tech innovators and entrepreneurs to shape the future of healthcare in the area.

The region’s healthcare sector faces a complex range of issues, such as talent shortages, increasing demand for chronic care solutions, and unequal access to medical expertise.

According to the 2024 Philips Future Health Index Report, 71 percent of health care leaders in APAC have concerns about delays caused by the lack of staff, noting that 50 percent of their manpower experienced burnout, stress, and low morale. Notably, 98 percent of hospital leadership say they are investing in or planning to invest in generative AI technology within the next three years. The same study says the region is ahead globally in terms of tech adoption and investment.

Consumer sentiment is aligned with these plans. Bain & Company’s “Asia-Pacific Front Line of Healthcare” study reveals a growing preference for AI-assisted services. In 2023, over 50 percent of patients said they felt comfortable receiving AI-powered assistance, whether from AI-enabled providers or entirely AI-run systems, especially for preventive care and less severe conditions.

AI-driven innovations in APAC telehealth

The APAC region is riding the shift from traditional clinical care and in-person visits to AI-guided and digital-first channels. Here are some examples.

1. Conversational AI

AI-powered virtual assistants and chatbots are becoming key components of clinical workflows. These tools handle routine health inquiries and administrative tasks, freeing up healthcare staff and improving patient satisfaction.

For example, Singapore’s SingHealth system uses “Note Buddy” — an AI assistant that transcribes doctor-patient consultations and summarizes them in real time across multiple languages. This ability reduces paperwork and enhances attentiveness during clinical visits. Meanwhile, the National University Health System’s OneNUHS chatbot allows patients to send in their vital signs, which the AI tool flags for clinical review if anomalies are present.

2. Remote patient monitoring and predictive analysis

Changi General Hospital has been using an AI-powered remote patient monitoring system with wearable sensors that track vital signs since 2022. The data is analyzed in real time to predict deterioration and ensure timely interventions. Singapore General Hospital uses AI to analyze patient histories, as well, predicting post-surgical complications with over 90 percent accuracy.

3. AI-assisted surgical procedures

To reduce patients’ knee pain, a team from the Alexandra Hospital Department of Orthopaedic Surgery in Singapore developed an AI model to help surgeons plan the best positions for knee replacements. Procedures using the algorithm were able to finish nearly 50 percent faster than humans alone, partially thanks to the time for optimal gap balancing decreasing from 15 minutes to 0.1 seconds. The hospital says the increased accuracy promotes better implant function and longevity, as well as reduces the risk of instability, loosening, or wear.

4. AI-powered diagnostics and imaging

Radiology is among the most AI-integrated fields. Another Philips study in 2024 showed that 80 percent of radiologists in Singapore, Australia, and South Korea believe AI will soon be embedded in their current workflow. Teleradiology aided by AI has also grown rapidly, with 60 percent of these professionals turning to remote platforms to enhance diagnosis.

A good example is Vietnam’s VinBrain, which developed DrAid — an AI platform trained on 2.5 million X-ray images to assist in diagnostics. DrAid integrates learned language with imaging data to deliver diagnoses and provide insights. It is already in use in hospitals across Myanmar, New Zealand, and the U.S.

Thanks to AI’s ability to consume and interpret large volumes of patient data, it can detect unusual patterns that human-led clinical processes may overlook. A good case is the diagnosis of Alzheimer’s disease, where deep learning AI showed a 99.95 percent accuracy in classification.

5. AI in mental health services

AI enhances mental health care by using speech and behavior analysis and automated screenings to detect conditions like depression and anxiety. An example is Adayu Mindfulness by Fortis Healthcare in India. Adayu is a digital mental health tool that provides assessments and 24/7 support through Stella — an AI assistant trained to deliver psychological first aid.

The road ahead for AI in APAC telehealth

While AI’s potential is limitless, so are its risks. There remain concerns about accuracy and data bias in AI models, which could widen health care gaps. To address this, facilities must invest in training tools to read diverse datasets, set governance guidelines, and enable cross-functional teams that address both the tech and ethics sides of development.

As Bain & Company’s data makes clear, consumers are now more receptive to AI in health care. The future of this industry in Asia-Pacific will be shaped not just by technology but also by how responsibly and inclusively it is deployed. Those who build AI-driven solutions with trust, accuracy, and equity at the core will be best positioned to lead the next wave of innovation in the region.

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