Amanda Gravitis, CEO of Smart Salem.
In healthcare, AI is not just a concept on the horizon or in some distant future; it is transforming the industry in powerful and practical ways.
In fact, I am witnessing this firsthand in my work in the United Arab Emirates (UAE), where I lead my company in integrating AI-driven solutions for medical testing and screening.
Embedding AI In Healthcare
AI is already universalizing access and enhancing diagnostic speed, accuracy and insights. In the next few years, I see it becoming a fully integrated element of health systems.
Particularly within our centers, I have seen how AI enables earlier intervention for common conditions such as diabetes or hypercholesterolemia. Ultimately, that means better outcomes for patients, and a greater focus on prevention.
Personalized Care With AI
Thanks to AI, the general public’s access to personalized medicine is dramatically improving. One example is using personalized digital twins, an AI-powered replica of your biological profile. These allow us to gain precise insights into health risks, predict outcomes, accelerate and improve clinical decision-making.
Advanced computing and AI models are also helping clinicians make more tailored recommendations. One recent example of an AI-driven impact comes from a patient who underwent gut microbiome testing with us. The AI flagged patterns of microbial imbalance linked to high protein intake and elevated beta-glucuronidase production.
Based on these insights, our expert clinical dietitian recommended a targeted nutrition plan that focused on lowering beta-glucuronidase activity and restoring gut balance. This included reducing excess protein intake, increasing fiber from whole plant sources and balancing animal with plant-based proteins.
Within a few weeks of implementing these dietary recommendations, the patient reported noticeable improvements in overall well-being. She had higher energy levels, sharper concentration and reduced bloating and digestive discomfort.
This is an outcome that might otherwise have taken months to achieve through conventional trial-and-error approaches.
Deeper Insights Through Advanced Analysis
With AI, we can analyze the billions of nucleotides in your DNA or the trillions of microbes in your gut microbiome. This level of insight allows us to uncover the root causes of common issues and deliver far more personalized solutions.
Even with AI, processing these insights can still take weeks to complete. But without AI and powerful computing infrastructure like graphics processing units (GPUs), this level of analysis would be next to impossible.
The outcome? Common ailments like gut health issues, hair loss and acne can now be tackled more effectively than ever before.
Key Challenges And Opportunities
Representative Data
Despite its huge potential, AI adoption in healthcare comes with several challenges, the most critical being data.
For AI to be truly effective, the data used to train it must be representative of the population it serves. In a diverse population such as the UAE, this is essential, not optional. Without inclusive datasets, AI tools risk delivering biased outcomes that don’t reflect the real-world needs of patients. Systems trained on narrow or incomplete data fail to generalize across broader populations, reinforcing existing healthcare disparities.
To counter this, we must intentionally build sociodemographic diversity into AI training data from the outset, which includes race, age, gender, geography and other health-relevant variables. When built on rich, inclusive datasets, AI can most accurately provide personalized care and generate insights that are meaningful.
Knowledge And Training
It’s also incredibly important that our healthcare teams have the knowledge and confidence to work effectively with AI. Clinicians must be able to critically assess AI systems, to ensure outputs are safe, accurate and trustworthy. AI should support clinical judgment, not override or replace it.
Beyond training, regulation and infrastructure must evolve too. Patient data privacy is nonnegotiable; your data belongs to you, and transparency and security must be built into every step. People have the right to understand and decide how, why and by whom their data is being used.
Collaboration
We also need collaboration between the public and private sectors, and within organizations. Leaders will need to champion AI, rethink internal strategies and provide teams with the tools and training needed to adopt new systems successfully.
Testing And Adapting
One of the biggest misconceptions I’ve encountered is that AI is a one-size-fits-all solution. But its effectiveness depends entirely on context, input quality and appropriate use. One of the biggest lessons we’ve learned at my company is the importance of continuous validation. What works in one cohort or condition may not translate directly to another.
Maintaining The Human Touch
Even with advances in AI and the benefits it brings, the human element of patient care remains essential and core to healthcare.
At our clinics, AI complements our services, accelerating processes and driving efficiencies that we couldn’t replicate manually. Alongside our customer happiness officers, nurses, doctors, lab technicians and everyone else who contributes to the patient journey, this is what helps deliver an outstanding all-round experience.
The key is to think of AI as a time-saving tool that handles background processes, allowing clinicians and the rest of the team to focus on what matters most: the customers.
Looking Ahead
As AI continues to evolve, we must evolve with it thoughtfully, ethically and with a clear focus on improving patient outcomes.
When paired with a human-first mindset, I believe AI has the potential to completely transform how we prevent, diagnose and treat illnesses, unlocking a new era of accessible, proactive and personalized healthcare.
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