
Why AI adoption in healthcare is a necessity, not a trend
Across hospitals in the UAE and beyond, diagnostic imaging is one of the most overburdened parts of the healthcare system. Radiologists are expected to interpret thousands of complex scans with speed and accuracy, all while dealing with an aging population, increasingly complex cases, and finite resources. The pressure is real and so are the consequences. Delays in diagnosis can lead to delays in treatment, and in high-stakes scenarios such as strokes, cancers, or internal bleeding, those delays can be life-altering.
For years, we've relied solely on human expertise to meet this demand. But we're reaching a point where that model needs reinforcement. Not replacement—reinforcement. That's where AI comes in.
From 'Nice to Have' to 'Need to Have'
For a long time, AI in healthcare was viewed as an emerging innovation: interesting, potentially useful, but not yet central to care. That perception has shifted. Today, AI is becoming foundational to diagnostic workflows. In radiology departments, AI models can scan images in real time, flagging anomalies that might otherwise take hours or days to surface. They're trained on thousands of cases, and they operate without fatigue, bias, or distraction. This isn't about removing the human element; it's about enhancing it.
'In the Middle East and North Africa, heart disease is responsible for 14% of all deaths—making it one of the leading health threats in the region.
At the same time, the number of people living with diabetes is expected to grow by 85% over the next two decades. That's nearly doubling the burden of a disease that already requires constant monitoring, medication, and long-term care.
These numbers are a clear signal: chronic conditions are on the rise, and the pressure on health systems in this region is only going to grow. Without smarter, more scalable approaches to care, it's going to be harder and harder to keep up.'
A growing number of hospitals in the UAE have begun integrating these tools into their systems not because it's trendy, but because it's necessary. From triaging high-risk patients faster to improving the consistency of diagnoses, the benefits are already being felt. This move toward digitalisation is part of a broader trend seen in the Middle East, with healthcare expenditures in the Gulf Cooperation Council (GCC) predicted to reach $135.5 billion by 2027, buoyed by an increasing adoption of emerging technologies like AI. In fact, Saudi Arabia allocated more than $50 billion in 2023 to improve healthcare efficiency, including investments in digital health services.
Recent developments showcased at major regional conferences have also reflected this shift. At Arab Health 2025, AI-powered diagnostic innovations took center stage—among them, MRI and CT systems that leverage deep-learning algorithms to enhance image clarity, reduce scan times, and improve patient throughput. One example included new AI-enhanced ultrasound tools designed to offer faster, more confident assessments at the point of care—critical in high-pressure clinical environments. These systems, already being adopted in select hospitals, illustrate how AI is quietly becoming part of everyday care delivery in the UAE.
AI's Role in Speed and Diagnostic Accuracy
One of the greatest strengths of AI in diagnostics is speed. A chest X-ray flagged by AI for signs of pneumonia can be moved to the top of the review queue. A brain scan showing signs of hemorrhage can trigger an immediate response. But speed alone isn't the point. The more important contribution AI makes is in reducing diagnostic error. AI, when properly trained and deployed, can act as a second set of eyes—one that's tireless and able to catch the subtleties.
Studies from multiple health systems globally are showing that diagnostic accuracy improves when AI and human expertise work together. And when diagnostic quality improves, patient care improves. In fact, research has shown that AI-assisted diagnosis of mammograms can detect 20% more cancers, underscoring the immense potential for AI to enhance diagnostic precision.
The UAE is in a Unique Position to Lead
Few countries are as well positioned as the UAE to lead the way in AI-powered diagnostics. Government strategies, such as the National Strategy for Artificial Intelligence and the UAE's broader digital health vision, have laid a clear foundation. Hospitals here are technologically advanced, and leadership teams are often more agile in implementing innovation than their counterparts in other regions. The UAE's thriving AI agenda is reflected in the expected growth of its AI market, which, at USD 3.47 billion in 2023, is predicted to grow at a compound annual growth rate (CAGR) of 43.9% through 2030.
We're already seeing pilots and case studies across both public and private health networks that are proving the value of AI. In some cases, it's about improving radiology throughput. In others, it's about extending high-quality diagnostics into under-resourced areas through remote AI interpretation.
Emirates Health Services has already integrated AI tools into radiology workflows—particularly in areas like visa screening and mammography, helping shorten turnaround times and easing the burden on physicians. These efforts not only reduce repetitive tasks but also help healthcare professionals focus on higher-value decision-making.
Even established providers like American Hospital Dubai have begun incorporating AI-enabled imaging systems in collaboration with tech partners—signaling how AI is moving from pilot to practice. With AI predicted to contribute Dh335 billion to the UAE's GDP by 2030, healthcare applications are set to be a driving force in this economic growth.
The Next Chapter: From Diagnostics to Prediction
Imaging is just the beginning. To truly understand a patient's health, we can't rely on just one type of data. In modern medicine, we work with a wide range of data types, or what we call multimodal data.
Soon, AI will support physicians in anticipating disease rather than reacting to it. Models that analyse not only scans but also clinical histories, lab results, and genomics will provide predictive insights—flagging patients at risk of chronic illnesses or relapse before symptoms appear. This kind of proactive, personalised care could fundamentally change how we approach medicine. But it won't happen automatically. It requires investment, regulation, clinician engagement, and above all, trust in accuracy of AI.
AI is no longer just an assistant in the diagnostic room—it's becoming the backbone of a more resilient, more efficient healthcare model. As healthcare expenditure in the GCC continues to rise and the AI sector grows exponentially, hospitals that integrate AI thoughtfully will be faster, safer, and better equipped to handle what comes next. Patients will benefit from earlier interventions, more accurate diagnoses, and a more consistent standard of care, regardless of where they are or who they see.
We're not talking about science fiction. This is happening now, and the UAE is on the front foot. The opportunity isn't just to adopt AI. It's to lead with it.
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