By Hasan Salahuddin

As Pakistan seeks to modernise healthcare delivery, China’s integration of artificial intelligence (AI) into mainstream health services offers a practical policy reference for improving diagnosis, continuity of care, and efficiency in an already strained system.

In healthcare, AI refers to digital tools that analyse medical data, support diagnosis, assist clinical decision-making, and improve patient monitoring and service delivery.

In an official report released in November 2025, China’s National Health Commission called for wider use of AI in healthcare, setting a 2030 target for intelligent diagnosis and treatment support across primary-care institutions, including community and village clinics.

In Pakistan, the Ministry of National Health Services’ National Digital Health Framework 2022–2030 aims to establish an interoperable digital health ecosystem by 2030. The ministry’s 2025 telemedicine tender also sought experience in AI-enabled telemedicine and AI-guided clinical decision-making. This shifts the debate from whether AI will enter healthcare to how Pakistan can shape its use in a practical and responsible way.

Experts say the relevance is not theoretical. Speaking with Wealth Pakistan, Fahd S. Kakakhel, Founder and CEO of Pak Health Consultants, said Pakistan can draw lessons from China’s use of AI to enhance diagnostic accuracy, streamline patient management, and optimise hospital workflows.

He said these gains are tangible. AI-assisted tools in areas such as CT scan interpretation can help clinicians make faster and more reliable decisions, while digital systems for chronic disease tracking can improve long-term patient monitoring. He also highlighted operational benefits, noting that AI can help hospitals manage processes more efficiently in a system where time, staff attention, and clinical resources are already constrained.

However, he emphasised that adoption depends on basic readiness. Pakistan still faces gaps in IT infrastructure and connectivity, limited availability of high-quality health data, a shortage of trained human resources, and the absence of clear regulatory frameworks for AI use and data security. In this context, he framed AI as a systems reform issue rather than a simple technology acquisition.

Sana Khan, Founder and CEO of Femfit, shifted the focus to primary care and continuity of care. She said Pakistan does not need to replicate any single foreign healthcare model, but it should closely examine how AI has been used to address challenges of scale, access, and efficiency.

She described AI as a “force multiplier for weak systems.” In Pakistan, she said, the greatest opportunity lies not only in large hospitals but at the primary care level, where delayed treatment, inconsistent providers, and fragmented service pathways often worsen outcomes. AI-supported screening, symptom assessment, and risk profiling — particularly in chronic care and women’s health — can help detect issues earlier and make first-contact care more reliable. This approach aligns with China’s policy push to extend AI-enabled support to frontline institutions.

She also highlighted the importance of standardisation. With diagnosis and treatment quality varying widely across regions, AI-assisted decision support can help create a more consistent baseline for frontline care. In addition, AI can strengthen patient retention through follow-ups, reminders, and basic monitoring in a system where long-term engagement is often weak.

However, she cautioned that readiness and equity remain critical concerns. Without clear policies on data protection, interoperability, and ethical use, adoption may remain fragmented. If driven solely by private-sector innovation, AI could widen rather than reduce healthcare disparities. She emphasised the need for a systems-first approach that strengthens public and community-level care, making any learning from China adaptive and aligned with public interest rather than purely technology-led.

Saad Saboor, Country General Manager Pakistan at Boston Health AI, focused on implementation pathways. He said Pakistan should begin where service gaps are widest — at the primary care level.

In lower- and middle-income settings, he said, AI delivers the most value by extending diagnostic support to areas with limited access to specialists. This mirrors China’s approach of expanding AI-enabled services beyond top-tier hospitals to lower-level facilities.

He also stressed the importance of clinician trust. AI should support, not replace, doctors by assisting with documentation, decision-making, and follow-up while keeping clinicians in control. This “human-in-the-loop” model, he said, is more practical for Pakistan and more likely to gain acceptance among healthcare providers.

Saboor identified telemedicine as an immediate entry point. Rather than building standalone AI platforms, Pakistan can integrate AI into existing consultation workflows through real-time decision support, automated visit summaries, and follow-up prompts. He also pointed to the importance of multilingual tools and the role of community health workers in extending services to underserved populations.

On the policy front, he highlighted the absence of a dedicated regulatory pathway for AI in healthcare, including issues of validation, liability, and data governance. He also noted structural constraints such as paper-based records, non-interoperable systems, connectivity gaps, and limited AI education in medical and academic institutions.

Taken together, experts suggest that Pakistan’s challenge is not adopting AI, but building the digital, regulatory, and human foundations required to make it effective in diagnosis, follow-up, and frontline care, with China offering a practical model for adaptation rather than replication.

Credit: INP-WealthPk