Dr. Zaid Al-fagih, the co-founder and CEO of Rhazes AI, stands at the forefront of a critical battle in modern medicine: the fight against diagnostic error, a silent killer responsible for an estimated 10% of all patient deaths. He argues that while doctors are overwhelmed by skyrocketing administrative burdens and an ever-expanding universe of medical knowledge, healthcare systems in the West are stifling the very AI solutions that could save lives. In this conversation, Dr. Al-fagih unpacks the frustrating paradox of life-saving technology being blocked by red tape, explains how agentic AI can serve as a vital “second doctor” in the room, and illuminates why the Gulf nations are poised to become the world’s proving ground for the future of AI in healthcare.
You highlight that diagnostic errors contribute to 10% of patient deaths and argue that policies like “Jess’s Rule” are insufficient. What specific resources are most critical for overwhelmed doctors, and can you describe the practical, day-to-day challenges that such guidelines fail to address for them?
The reality on the ground for clinicians is one of immense pressure that a simple guideline just can’t fix. Think about it: for every single hour a doctor spends face-to-face with a patient, they are saddled with two hours of paperwork. At the same time, the sheer volume of medical knowledge is exploding, doubling every 73 days. So, you have a professional who is drowning in administrative work while also being expected to retain an impossible amount of new information. A policy like “Jess’s Rule,” which urges them to “think again,” is well-intentioned but misses the mark. It’s like telling a marathon runner at mile 25 to just try harder, without offering them water or support. What they desperately need are tools that give them back time and cognitive space—resources that automate the relentless documentation and act as a smart, reliable partner to help them navigate that flood of information.
You cite impressive metrics like a 60% cut in documentation time and error rates dropping to 3.1% with agentic AI. Could you walk us through how this technology functions during a patient visit and provide a real-world example of how it queries a doctor’s decision-making process?
Imagine a seamless, almost invisible assistant in the consultation room. The agentic AI is actively listening, transcribing the entire patient-doctor conversation with precision. This alone is transformative. Once the patient leaves, the doctor isn’t faced with a mountain of forms and notes to write. The AI has already generated a concise summary, drafted referral letters, and prepared the necessary documentation, which is how we see that incredible 60% reduction in a doctor’s administrative time. But its most vital role is acting as a second set of eyes. For example, if a doctor diagnoses a routine condition, the AI—having processed the conversation and the patient’s full history—might gently interject in the notes: “Given the patient’s recent travel and mention of a minor rash, have we considered the possibility of X?” It doesn’t overrule the clinician; it nudges them to consider alternatives. That single query can be the difference between a missed diagnosis and a correct one, which is how we see error rates plummet from 8.3% to a much safer 3.1%.
You mention “red tape” in the EU and UK, which classifies AI tools in the highest-risk bracket. From your perspective, what are the most significant regulatory hurdles for tech companies, and can you share an example of how these delays directly impact patient safety or outcomes?
The most significant hurdle is a profound lack of regulatory nuance. In the UK and EU, officials are placing a tool that generates clinical notes using a well-known, established large language model in the same high-risk category as a surgical robot or a life-support machine. This is a fundamental misunderstanding of the technology. For a company like ours, it means being forced into a long, incredibly expensive, and often convoluted medical device certification process for what is essentially an advanced administrative assistant. The direct impact on patients is that these life-saving tools are being kept out of clinics. Every day that an AI tool proven to reduce documentation and error is stuck in regulatory limbo is another day that doctors are overworked, burnt out, and more likely to make a mistake. The delay itself becomes a risk to patient safety.
You said scaling your company, Rhazes, in Qatar was “quicker” and “better supported.” Could you detail the specific regulatory or administrative differences you encountered compared to Western nations? What practical steps did supportive bodies in the Gulf take to facilitate this process for your company?
The difference was night and day. In the West, we often felt like we were battling an outdated system that was inherently skeptical of innovation. In Qatar, the approach was collaborative from the start. Instead of facing a wall of bureaucratic “no’s,” we found a clear, sensible regulatory pathway designed to foster innovation while ensuring patient security. The supportive bodies there didn’t just hand us a rulebook; they engaged with us, understood what our technology did, and helped us navigate the process efficiently. This made scaling not only quicker but also significantly more cost-effective. They are building an ecosystem where technology is seen as a solution, not a threat, and that proactive mindset is a game-changer for any health-tech company.
With the UAE ranking first in AI adoption and Microsoft investing over $15 billion, how will this blend of public enthusiasm and massive infrastructure investment accelerate medical AI? What tangible changes might a patient in the UAE see in their healthcare experience in the coming years?
This combination creates a perfect storm for radical acceleration. You have a population where nearly 60% of working-age adults are already using AI, so there’s an inherent trust and acceptance of the technology. You have a government that is not just paying lip service to AI but has appointed an AI minister for every department, including health, signaling a deep, systemic commitment. Then you add the fuel: Microsoft’s $15 billion investment and access to cutting-edge Nvidia chips. This provides the raw computational power needed to run sophisticated AI models across the entire healthcare system. For a patient, the change will be tangible. It could mean their doctor is fully present and making eye contact during a consultation instead of typing. It will mean faster, more accurate diagnoses, predictive models that flag health risks before they become critical, and an overall feeling of confidence that their care is supported by the most advanced technology available.
What is your forecast for the global adoption of agentic AI in healthcare over the next five years, especially considering the pioneering role you believe the Gulf nations will play?
Over the next five years, I foresee a two-track world emerging. The Gulf nations—the UAE, Saudi Arabia, and Qatar—will leapfrog ahead, becoming the global epicenter for medical AI implementation. They will generate the undeniable, large-scale case studies and clinical data proving that agentic AI drastically reduces diagnostic errors and improves patient outcomes. This wealth of evidence will put immense pressure on Western healthcare systems. Regulators in Europe and the US will no longer be able to justify their slow, risk-averse stance when a new global benchmark for safety and efficiency has been set. The Gulf will not just be an early adopter; it will become the demonstrator, showing the rest of the world how to safely and effectively integrate AI into clinical practice. The question for other nations won’t be if they should adopt these tools, but how quickly they can catch up.
