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ALKHOBAR: As Vision 2030 accelerates ����ֱ��’s health transformation, experts say success will depend on blending investment, innovation and patient-centered care.

The Kingdom’s healthcare sector is at a crossroads. Rising rates of chronic disease, surging patient numbers, and a shortage of medical professionals are straining capacity.

Billions of riyals are being poured into new hospitals and clinics, but leaders say bricks and mortar alone will not be enough.

Artificial intelligence is increasingly seen as the lever that could ease the burden. Yet experts caution the technology is no silver bullet. Its success depends on how it is deployed.

“Fragmentation of care, resource shortages, and rising costs driven by chronic diseases remain the Kingdom’s biggest challenges,” said Dr. Mansoor Khan, CEO of Persivia, a US-based healthcare AI company that partners with ����ֱ�� providers.

No country has deployed AI at large scale in healthcare yet. ����ֱ�� has the human and financial capital to lead on the global stage.

Dr. Mansoor Khan, Persivia CEO

“AI is not one thing — it’s a set of technologies that need to be used carefully, mapped to specific problems and workflows.”

From the market side, Dr. Gireesh Kumar, associate partner for healthcare advisory at Knight Frank, a global property consultancy with active presence in Riyadh, points to looming capacity gaps.

According to a Knight Frank analysis published in August this year, Riyadh alone will need 4,500 new hospital beds within five years — a SR7 billion ($1.86 billion) investment, 60 percent of it funded by the private sector.

By 2040, the shortfall could climb to 15,300 beds based on global benchmarks.

The strongest use cases for AI are in hospitals. Image recognition, predictive analytics, and workflow automation can help reduce bottlenecks and balance demand across networks.

Dr. Gireesh Kumar, Knight Frank associate partner for healthcare advisory

“The strongest use cases for AI are in hospitals,” Kumar said. “Image recognition, predictive analytics, and workflow automation can help reduce bottlenecks and balance demand across networks.”

Both experts agree predictive AI offers the clearest near-term value. By analyzing patient data, it can identify high-risk individuals and enable early intervention.

Globally, organizations adopting predictive tools report up to a 25 percent reduction in operating costs and a 15 to 20 percent decrease in readmissions.

In the US, some networks have cut readmissions by 14.3 percent after deploying AI-driven outpatient management. For ����ֱ��, where diabetes and cardiovascular conditions dominate, the gains could be transformative.

Still, Khan stressed nuance: “If you are going to risk-stratify a population, that is not a task for generative AI, but for predictive and prescriptive AI. Success equals empathy plus evidence plus workflow fit.”

Telemedicine is another growth engine. During the COVID-19 pandemic, the Kingdom’s SEHA Virtual Hospital emerged as a flagship. Today it is the world’s largest virtual hospital, linking more than 150 facilities and serving over 480,000 patients a year.

On the private side, the ����ֱ��-built Labayh mental health app has reached more than 2 million users with over 70 million minutes of counselling delivered, making it one of the region’s prominent digital health platforms according to Knight Frank’s report.

Kumar said digital access points ease pressure on hospitals and extend services into underserved regions. Khan added a caveat: “The human interaction is critical. AI should support that, not replace it.”

Vision 2030 is accelerating the shift from fee-for-service to value-based care. That transition, Khan argues, requires deep private-sector involvement — from funding to management.

Kumar frames public-private partnerships as the catalyst for AI adoption.

“The public sector brings infrastructure and regulation, the private sector brings agility and global expertise. Together, they can fast-track AI solutions across diagnostics, telemedicine and workforce training.”

Gartner research titled “AI in Value-Based Care” published in June this year, reinforces this point, calling AI the critical enabling technology for advanced value-based care.

The global market for value-based healthcare is projected to soar from $12.2 billion in 2023 to $43.4 billion by 2031, with AI driving much of that growth.

Kumar points to lessons abroad: Singapore’s academic pathways that integrate AI with clinical training, China’s use of AI in chest X-rays, and the UK’s adoption of AI dermatology tools.

The Kingdom, meanwhile, is already testing bold ideas such as the world’s first AI-powered doctor clinic in Al-Ahsa, where a digital doctor named Dr. Hua collects symptoms, analyses data, and proposes treatments under physician oversight.

For Khan, this pioneering spirit is the opportunity. “No country has deployed AI at large scale in healthcare yet. ����ֱ�� has the human and financial capital to lead on the global stage.”

Regarding risks, Kumar notes that the Saudi Data and AI Authority established a framework in 2024 to safeguard patient privacy and ethics.

Khan insists adoption must be co-designed with clinicians and patients, starting with narrow, high-value use cases. “AI should enhance, not overwhelm, the human experience,” he said.

Gartner warns that AI models must be continuously monitored for bias and aligned with workflows to avoid clinician fatigue.

By 2030, ����ֱ��’s healthcare system is projected to look very different.

AI will underpin a shift from reactive treatment to preventative care, empowering clinicians with predictive insights, automating routine tasks, and expanding access through digital platforms.

Yet for all the investment and innovation, the final measure will not be model accuracy but human lives improved, as Khan put it earlier.