Sheba Medical Center in Israel has become OpenAI's first international hospital partner, signaling a broader shift in how healthcare systems are integrating artificial intelligence into daily clinical operations. Rather than deploying AI as a point solution for a single problem, the medical center is building what its leaders call an "AI-powered" hospital by 2030, embedding AI tools across clinical, research, and operational workflows.

Why Is Sheba Taking This Different Approach to Hospital AI?

The partnership originated from a real need within the hospital itself. Sheba operates with a lower ratio of clinicians to beds than peer institutions, a challenge that mirrors a global healthcare crisis. Israel has 3.5 practicing doctors per 1,000 people, below the OECD (Organisation for Economic Co-operation and Development) average of 3.9, according to recent data. The World Health Organization projects the European region will face a shortage of nearly 1 million health workers by 2030, while the United States could see a shortage of up to 86,000 physicians by 2036.

"We really want to democratize AI tools for the campus, for the people working in the hospital, whether they are clinicians or other professions," said Ayelet Akselrod-Ballin, head and chief technology officer of Sheba's AI Center.

Ayelet Akselrod-Ballin, Head and CTO of Sheba's AI Center

Akselrod-Ballin, who spent years working on AI for radiology, frames the shortage as a "crisis in healthcare." AI, she argues, can help bridge the gap by reducing the time clinicians spend on administrative work and searching for information in electronic health records.

What Specific AI Projects Is Sheba Already Running?

Sheba is not waiting for the OpenAI partnership to mature before deploying AI. The hospital already has several systems in active use across its network. These projects demonstrate how the institution is thinking beyond single-use applications and toward integrated workflows:

• SmartER: An ambient "invisible" AI system in the emergency department, built with the clinical documentation startup ScribeMD, that assembles a patient's history, nursing intake, and diagnostic results before the physician enters the room, then transcribes the patient-physician conversation and generates a structured clinical summary.
• Project K: Developed with Microsoft Israel and KPMG, this system runs intake through an AI avatar and provides an automated, AI-reliant process for triage and initial assessment.
• Beyonder: A screening system that routes stable patients to Sheba Beyond, the hospital's virtual care platform, while flagging complex cases for in-person care.

These projects reveal a strategic pattern: Sheba is automating the administrative and logistical layers of healthcare delivery, not replacing clinical judgment. The goal is to free clinicians from paperwork so they can focus on patient care.

How Is Sheba Planning to Scale AI Across the Hospital?

The OpenAI partnership will provide clinicians across Sheba's network and on mobile devices with access to ChatGPT for Healthcare, with implementation beginning in the coming months. The hospital will also gain early access to OpenAI's latest healthcare models before they become broadly available.

But scaling AI is not just about adding new tools. Sheba's AI Center, which employs more than 50 people, is mapping problems that recur across the medical center and building reusable infrastructure and components. Akselrod-Ballin explained the approach: the hospital identifies workflows that appear in multiple departments and builds generalizable solutions that can be adapted as needed.

"We're trying to really make a generalizable approach. You build an infrastructure that is agentic, where you have different agents working on different tasks, and then you reuse as much as you can components that you've already built," said Akselrod-Ballin.

Ayelet Akselrod-Ballin, Head and CTO of Sheba's AI Center

Sheba has five emergency departments, including dedicated oncology and pediatric ERs. Rather than building separate AI systems for each, the hospital is designing solutions that can be adapted across departments, reducing redundancy and accelerating deployment.

What Does Success Look Like for AI in Clinical Settings?

Evidence from other healthcare settings suggests that AI can deliver measurable operational gains. A 2023 cluster-randomized trial at four stroke centers that used AI software to analyze CT angiograms for large-vessel occlusions reduced the time from hospital arrival to thrombectomy initiation by 11.2 minutes. A more recent prospective study of generative AI-assisted radiograph reporting found a 15.5% improvement in documentation efficiency across nearly 24,000 interpretations, with peer review finding no significant difference in clinical accuracy or report quality.

These gains matter because they translate directly into better patient outcomes and reduced clinician burden. However, Akselrod-Ballin distinguishes between earlier waves of AI in healthcare, which focused on image interpretation, and the current wave of generative AI, which targets the administrative waste that consumes clinician time.

How to Build AI Governance While the Technology Is Still Emerging

One of Sheba's unique advantages is having a 50-plus-person AI Center embedded directly within the hospital. This structure allows teams to work closely with clinicians, IT, and security to develop and validate AI systems in real time. However, it also means Sheba is operating in areas where established regulatory guidelines remain limited.

• Regulatory Development: Sheba is building guardrails, monitoring systems, policies, and governance frameworks as it deploys new AI workflows, essentially co-creating regulation with regulators rather than waiting for formal guidelines to emerge.
• Internal Validation: The AI Center works directly with clinicians to test and refine AI systems before broader rollout, ensuring that technology meets clinical needs and maintains safety standards.
• Cross-Institutional Learning: Sheba's ARC innovation arm supports more than 130 startups and operates across 31 health systems and more than 300 hospitals, creating channels for sharing implementation experience and best practices.

Akselrod-Ballin noted that this collaborative approach is an advantage of having an AI Center inside the hospital. "There is some regulation, of course, but we are in a way building the regulation, the guardrails, the monitoring, the policy, the governance. We're building it together as we go," she said.

Sheba's partnership with OpenAI and its broader AI strategy reflect a maturation in how healthcare systems are thinking about artificial intelligence. Rather than chasing the latest AI model or deploying isolated tools, the hospital is building integrated infrastructure designed to solve recurring problems across the organization while maintaining clinical oversight and safety. As healthcare systems worldwide grapple with clinician shortages and rising administrative burden, Sheba's approach offers a practical blueprint for what "AI-powered" healthcare might actually look like in practice.