By Federico Pienovi, CEO for APAC & MENA at Globant

When technologies go exponential, even experts are caught off guard. Generative AI is one of those inflection points and nowhere is this tension more profound than in healthcare and aging, particularly in the Gulf region where demographic realities are driving unprecedented transformation. In Saudi Arabia, the population over 60 is expected to increase fivefold by mid-century, making longevity no longer just a Western debate but a Middle Eastern economic and social reality where AI moves from optional to existential.

While most organizations struggle to operationalize AI beyond demos, Saudi Arabia and the UAE are building system-level infrastructure that represents the real story. Saudi Arabia is embedding AI throughout its healthcare system through Vision 2030, with the Saudi Genome Program using multi-omics data—genomics, proteomics, metabolomics—and AI to shift from reactive to predictive care, moving beyond isolated diagnostics toward continuous early detection models.

Riyadh recently showcased the world’s first fully robotic heart transplant, CAR-T cell therapy advancements, VR-based medical education, and mobile stroke units with advanced diagnostics, while digital twin technology and precision medicine are becoming standard rather than experimental. These initiatives reflect a national longevity strategy that positions geroscience research and personalized digital twins as core infrastructure, with private-sector innovators like Rewind building AI-powered diagnostics to prevent disease before it emerges.

The UAE has gone even further, treating longevity as a national industry with Abu Dhabi’s Pura Longevity Clinic offering AI-integrated assessments and personalized prevention programs that combine nutrition, sleep, fitness, and mental health services, positioning longevity medicine as mainstream rather than elite. Dubai aims to become the global capital of “well-care”, biohacking, stem-cell therapies, and AI-driven anti-aging, as part of a broader strategy to engineer the “100-year life” through advanced preventive and regenerative medicine.

The UAE now hosts 680 longevity companies and 670 investors across 100 innovation hubs spanning PharmTech, telemedicine, advanced cosmetics, mental health, and wellness, making longevity a full economic sector. The Institute for Healthier Living Abu Dhabi is building a Healthy Longevity Medicine ecosystem with longevity-focused clinical care, innovation hubs, and population health research, while government-level commitment is evident through Abu Dhabi’s Department of Health convening global forums to accelerate personalized healthcare and longevity science.

Beyond the Hype: The Human Element

But here’s the uncomfortable truth: more AI doesn’t automatically mean better health. Like millions of others tracking sleep, monitoring recovery, and measuring stress variability, we risk becoming surrounded by dashboards of health metrics where everything is quantified and notified, yet the more data we collect, the more a critical question emerges—are we actually healthier, or simply more informed about our anxiety?

The healthcare system risks repeating the same mistake enterprises made with digital transformation, adding layers of technology without redesigning the underlying architecture, creating more apps, more portals, more fragmented experiences, with noise disguised as progress.

Harvard Medical School researchers have highlighted how AI can already match or exceed clinicians in specific diagnostic tasks, particularly in imaging and pattern recognition, while MIT’s Jameel Clinic has demonstrated how machine learning models can accelerate drug discovery cycles from years to months, and McKinsey estimates that generative AI could unlock up to $100 billion annually in value across pharma and medical products alone.

Yet the promise of AI in aging is not about adding intelligence everywhere,it’s about reducing friction and elevating judgment through agentic AI systems capable of orchestrating actions autonomously across complex environments, moving healthcare from reactive to anticipatory with adaptive health pathways tailored to biology, behavior, and environment instead of generic wellness advice.

We must be careful because biology is not software, data can be biased, predictions can be misinterpreted, and AI systems trained predominantly on specific datasets may fail in other populations, making governance, explainability, and medical accountability foundational requirements rather than afterthoughts.

The Bigger Picture

From a technology executive’s perspective, the next decade will redefine healthcare economics as systems shift from hospital-centered to prevention-centered models, payment structures evolve toward outcome-based frameworks, and AI doesn’t replace physicians but enables those who leverage it to outperform those who don’t.

The Middle East understands this transformation, with the UAE’s push into genomics and Saudi Arabia’s investments in biotech and digital health reflecting recognition that longevity will shape national competitiveness, where healthy lifespan, not just GDP, will define prosperity.

In these nations where governments are investing heavily in smart hospitals, genomics programs, and national AI strategies, the opportunity is enormous as they position themselves as global hubs for the future of healthspan and aging, demonstrating that AI is moving from experimentation to infrastructure with longevity becoming a national economic and healthcare priority.

Dr Maheen Hasib, Global Programme Director for BSc Data Sciences, School of Mathematical and Computer Sciences, Heriot-Watt University Dubai

Artificial intelligence (AI) and data science are no longer distant or experimental ideas. They quietly sit behind many of the decisions that shape our everyday lives: how patients are diagnosed, how job applications are filtered, how loans are approved etc. These systems increasingly influence who gets opportunities and who does not. That reality makes one question impossible to ignore: who is building the algorithms that shape our future?

As a Programme Director for the Data Sciences programme at Heriot-Watt University, this question is not just academic for me, it is deeply personal. Every year, I meet capable, curious, and motivated young women who are genuinely interested in data science. Yet many hesitate. Not because they lack ability, but because they are unsure whether they truly belong in the field. Too often, they do not see people (like themselves) reflected in AI research, technical teams, or leadership roles. And that absence matters.

When bias in AI feels uncomfortably familiar

AI systems are often described as objective or neutral, yet they are trained in data shaped by human history, something that is far from neutral. When training data reflects existing gender imbalances, AI systems can replicate and even magnify those patterns. This has led to technologies that perform less accurately for women, fail to capture women’s health needs, or disadvantage women in recruitment and evaluation processes.

For many women, these outcomes feel uncomfortably familiar. They echo everyday experiences of being overlooked, misunderstood, or underrepresented. In most cases, this is not the result of deliberate exclusion. It is the consequence of design choices made without diverse perspectives at the table.

Why representation goes beyond numbers

Representation in AI and data science is often discussed in terms of statistics or diversity targets. But at its core, representation is about perspective. When women are involved in developing AI systems, they help shape how problems are defined, what data are considered relevant, and which risks are taken seriously.

From an academic perspective, diverse teams produce more robust research and better-tested models. From a human perspective, they help ensure that AI systems work for the full range of people they are meant to serve. Inclusion improves both technical quality and social impact, it strengthens the science and the society it serves.

Women and the future of ethical AI

Many women working in AI are already at the forefront of discussions around fairness, transparency, explainability, and responsible data use. These are not peripheral concerns; they are central to building trustworthy AI. Ethical AI requires asking difficult questions: Who might be harmed when a system fails? Whose data is missing? Who is affected by design decisions that seem minor on the surface?

By advocating for human-centered approaches, women in AI are helping shift the field beyond purely performance-driven metrics toward systems that balance innovation with responsibility.

Education, encouragement, and visibility matter

At Heriot-Watt University Dubai, we make a deliberate effort to encourage women to pursue data science, not just as a degree, but as a long-term career. This means creating supportive learning environments, highlighting female role models, and openly discussing the wide range of paths that data science can lead to. Students need to see that success in AI does not follow a single template.

Equally important are spaces where women can connect, share experiences, and feel supported. As an ambassador for Women in Data Science, I have seen how such events play a vital role. They create visibility, build confidence, and remind women that they are not alone. We need more of these initiatives, not as one-off celebrations, but as sustained platforms for mentorship, networking, and growth.

Encouraging women in AI is not about lowering standards or meeting quotas. It is about recognizing that inclusive participation leads to better research, more ethical technologies, and systems that genuinely reflect the societies they shape.

Conclusion

As AI and data science continue to influence our world, we must ask not only what these systems do, but who designs them. Supporting women to study data science, pursue AI careers, and step into leadership roles is essential to building technologies that are fair, responsible, and trustworthy. Through education, visibility, and initiatives, we can help ensure that the future of AI is shaped by many voices.

The future of AI should be one where women do not simply use technology but actively shape it.

By Ahmad Hamad Bin Fahad, CEO of DUBAL Holding

The UAE’s growth journey is led by an unwavering focus on driving digital transformation, enhancing renewable energy capacity and promoting regulatory excellence. This is best reflected in the ‘Net Zero 2050’ strategy, which aims to create 200,000 jobs across the solar, battery and hydrogen sub-sectors, combining economic and sustainability goals. Digitalisation of the industrial sector will play an important role in realising this vision by paving the way for long-term industrial competitiveness and resilience.

Smart manufacturing, AI adoption and Industry 4.0

Across the UAE, factories are being installed with smart manufacturing systems that integrate IoT sensors, predictive analytics and real-time data environments. These optimise energy usage, reduce downtime and minimise material waste, turning sustainability into a measurable, operational outcome rather than an abstract concept.

Furthermore, digitally connected factories can track emissions at every stage of production, benchmark efficiency and automate corrective actions. This is crucial to achieving the goals of ‘Operation 300bn’ and positioning the UAE as a global hub for future industries.

According to the Ministry of Industry and Advanced Technology (MoIAT), Industry 4.0 tools can increase the nation’s industrial productivity by up to 30 per cent while reducing operational costs by nearly 20 per cent through wider structural transformations. Moreover, AI adoption is set to contribute AED 335 billion to the UAE economy by 2031, as reported by the UAE Council for AI and Blockchain.

Artificial Intelligence is also redefining how industrial assets function, from power plants and smelters to logistics centres and material processing facilities. AI-enabled algorithms can even forecast equipment failures, balance energy loads and simulate entire production cycles to identify carbon-saving interventions. AI also helps enhance transparency and enforce operational discipline, promoting both sustainability and profitability.

Role of advanced automation in redefining industrial operations

Advanced automation, from robotics to autonomous transport systems, is driving sustainability by eliminating key bottlenecks that cause higher emissions. Furthermore, automated systems ensure enhanced precision, enabling industries to streamline energy usage, optimise supply chains and accelerate circular-economy practices such as recycling, material recovery and waste-to-value processes.

However, automation does not replace human capability; it merely enhances it, enabling operators to move on to high-value digital roles. It efficiently tackles repetitive, energy-intensive tasks, creating a more resilient, low-carbon industrial ecosystem. A key enabler of this transition is the rise of strategic, government-aligned investments in digital-first industrial ventures. These investments are the backbone of the nation’s industrial future as they help build advanced manufacturing platforms, AI-driven optimisation technologies, smart mobility solutions and digital energy-management systems.

By investing in companies that integrate digital tools into core industrial operations, the UAE is accelerating technology adoption at scale. These investments further position digital transformation as a strategic imperative for fulfilling the UAE’s sustainability goals while boosting economic competitiveness.

Way Forward: Shaping a resilient industrial economy

The UAE’s wise leadership remains committed to fostering an ecosystem that rewards digital innovation and AI adoption. Moreover, by directing long-term strategic capital towards transformative technologies, the nation is building an industrial sector that is both future-ready and climate-aligned.
Amid this shift, digitalisation stands out as the most critical tool for building a sustainable, net-zero industrial economy. Aligning with this, companies must embrace forward-looking strategies that can positively shape the future of the industry.