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How are leaders in the Middle East using AI to solve for supply chain issues

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Businessman in suit holding holographic digital icons representing quality management systems including gears, checkmark, security, analytics, and team collaboration symbols

Attributed by Harsh Kumar, Chief Strategy Officer, Shipsy

The Middle East’s logistics sector is undergoing a fundamental change as industry leaders embrace AI to tackle region-specific challenges and build the foundation for autonomous supply chain operations. “In the wake of the fourth industrial revolution, governments and businesses across the Middle East are beginning to realise the shift globally towards AI and advanced technologies. We estimate that the Middle East is expected to accrue 2% of the total global benefits of AI in 2030. This is equivalent to US$320 billion,” highlights a PwC Middle East report.

When it comes to making supply chains autonomous, logistics leaders in the Middle East agree that there are some inherent challenges in the region that hinder growth and that they are working towards addressing the same.

Addressing the Middle East’s Obstacles to Autonomous Supply Chains

Inaccurate addresses remain one of the most critical pain points for Middle Eastern logistics operations, directly impacting productivity, costs, and customer experience. The region’s diverse linguistic landscape and inconsistent address systems have made last-mile delivery particularly challenging.

In the Middle East, inefficient address structure often results in packages and letters being addressed only with a recipient’s name, city, and country, lacking a specific delivery address. Courier services are typically provided with just a name and mobile number, requiring them to investigate and determine the intended delivery location. According to a report by Logistics Middle East, incorrect addresses can potentially impact more than $7.42 billion in eCommerce revenue in the Middle East.

“AI’s success and differentiation from any other technology before it, will depend on its ability to solve region-specific challenges. Unlike banking and financial services sectors, logistics and supply chain operations often deal with fragmented processes and disconnected systems. AI is uniquely positioned to bridge these gaps by harmonizing data, streamlining workflows and enhancing efficiency across the entire value chain all of which have a direct impact on operational productivity.” said Iyad Kamal, ex COO of Aramex.

Incorrect addresses also create another challenge of driver productivity and retention. With retail customer expectations rising and delivery times shortening, logistics providers will need to focus on making it easier for drivers to complete their work, get the right information at the right time to ensure they deliver a better customer experience.

The challenge compounds due to a flawed hypothesis in route optimization which does not take into consideration real-world variables when allocating deliveries creating delays and impacting driver productivity.  Another critical problem that needs to be addressed is financial settlements. Validating data for settlements remains a heavily manual and time-intensive process. It will not be incorrect to say that only about 10% of invoices are accurately validated, as the human effort required is significant. This results in a higher risk of inaccuracies in settlement. AI agents can help here by analyzing delivery proofs against trip data and automatically calculate delay fees using GPS timestamps and contractual rates.

How leaders are moving from Guesswork to Data-Driven Precision

Resource allocation has traditionally relied on intuition, resulting in suboptimal vehicle utilization and excessive mileage. Digital Twin technology is changing this paradigm by enabling logistics providers to run scenario analyses and predict the impact of different allocation strategies before implementation.

Real-time incident management has also evolved beyond manual dashboard monitoring. Autonomous monitoring agents now continuously check operations against KPIs, detecting anomalies like delays or harsh braking incidents. When issues arise, these agents assess impact, proactively communicate updated ETAs to customers, and suggest rescheduling options, thereby drastically reducing resolution times.

Aujan Coca-Cola Beverages Company is leveraging Agentic Incident Management, AI-powered dynamic route optimisation and load balancing and Agentic Control Tower to enhance customer experience by ensuring ETA adherence and real-time visibility.

Fair compensation and equitable workload distribution emerged as critical for combating driver attrition, with leaders emphasizing that rewards must be immediate rather than deferred to maintain motivation. Customer-centric execution requires moving beyond basic data matching. AI-enabled semantic matching creates comprehensive customer profiles that preserve delivery preferences across different drivers and addresses, ensuring consistent service quality.

“Verifying every transaction and validating every invoice, continue to be a massive overhead for supply chain leaders even in 2025. Companies that can leverage AI to automate highly human-intensive processes will unlock velocity as an advantage, making it harder for their competition to catch up.” said Soham Chokshi, Co-Founder and CEO of Shipsy, while emphasizing AI’s role in logistics.

The Road Ahead

Logistics leaders in the Middle East envision autonomous, intelligent, and customer-centric supply chains powered by agentic AI that independently solves complex problems. However, the success of these systems hinges on a human-in-the-loop approach. Balancing algorithmic optimization with human expertise, such as local knowledge and driver preferences, is essential to address the region’s unique challenges, like inefficient address systems. By integrating continuous monitoring and predictive intervention, AI can shift operations from reactive to proactive, but human oversight ensures adaptability and accuracy. This synergy between AI capabilities and human insight drives resilient, efficient, and customer-focused logistics networks.

As the region’s logistics sector continues its digital transformation, these AI-driven foundations are positioning Middle Eastern supply chains at the forefront of global innovation in autonomous operations.

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Tech Features

HOW WOMEN SCIENTISTS CAN ACCELERATE NATIONAL INNOVATION GOALS

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Dr Heba El-Shimy, Assistant Professor (Data and AI), Mathematical and Computer Sciences, Heriot-Watt University Dubai

Healthy societies, institutions, or teams operate best when comprising a healthy balance between males and females. A landmark study by Boston Consulting Group (BCG) with the Technical University of Munich uncovered that companies with above-average gender diversity generated around 45% of their revenues from innovative products, compared to only 26% as innovative revenues for companies with below-average gender diversity. These findings are echoed in the scientific field. A 2025 study by Nature analyzing 3.7 million US patents revealed that inventing teams with higher participation of women are associated with increased novelty in patents. Research by the Massachusetts Institute of Technology confirms that teams with more women exhibit significantly higher collective intelligence and are more effective at solving difficult problems. These studies tell one clear story: that participation of women in innovative and scientific fields is not only desirable — it is a strategic national asset.

UAE Women In STEM

The UAE holds one of the world’s most striking gender profiles in STEM education. According to UNESCO data, 61% of graduates in STEM fields are Emirati women, surpassing the Arab world average of 57% and nearly doubling the global average of 35%. At government universities, 56% of graduates are women, and they represent over 80% of graduates in natural sciences, mathematics, and statistics.

These numbers have translated into accomplishments that have captured global attention. The Emirates Mars Mission — the Hope Probe — was developed by a team of scientists that was 80% women, selected based on merit. Noora Al Matrooshi became the first Arab woman to complete NASA astronaut training in 2024. The Chair of the UAE Space Agency and the mission’s Deputy Project Manager is a woman: H.E. Sarah Al Amiri. At Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), female enrolment reached 28% within five years and continues to grow. Women’s talents are being recognised — this is not a mere future ambition, but a present reality.

Scientific Research As An Engine For National Strategy

The ‘We the UAE 2031’ vision sets ambitious goals: doubling GDP to AED 3 trillion, generating AED 800 billion in non-oil exports, and positioning the country as a global hub for innovation, artificial intelligence, and entrepreneurship. The UAE’s rise to the 30th place in WIPO Global Innovation Index 2025 signals a steady pace towards achieving the UAE 2031 vision. Sustaining this ascent requires continued investment into human capital to produce research output, intellectual property, and commercial innovation at a pace matching the ambition. This is precisely where women scientists become indispensable.

Women scientists are already major contributors to the seven priority sectors identified in the UAE National Innovation Strategy: renewable energy, transport, education, health, technology, water, and space. UAE women scientists are research-active in climate science, sustainable materials, clean energy systems, AI-driven diagnostics in healthcare, and environmental monitoring — all crucial sciences that the national development commitments depend on.

Knowledge economies are built on the ability to generate, apply, and commercialize research locally — reducing the dependence on imported technologies and creating self-sustaining innovation ecosystems. When a researcher at UAEU develops patented computational methods for drug design, as Dr. Alya Arabi recently did with four patents spanning AI-driven pharmaceutical development and medical devices, that is intellectual property created on UAE soil, addressing healthcare challenges that would otherwise require imported solutions. When women scientists at Masdar City and Khalifa University advance research in solar energy systems, carbon captured materials, or sustainable desalination, they are producing foundational science that the UAE’s Net-Zero 2050 Strategy depends upon.

Masdar’s WiSER (Women in Sustainability, Environment and Renewable Energy) programme has graduated professional young women from over 30 nationalities, closing the gap in the global sustainability workforce. In healthcare, women scientists are active in the areas where AI, genomics, and precision medicine converge. The Emirati Genome Programme, M42’s Omics Center of Excellence, and the Abu Dhabi Stem Cells Center all represent domains where locally produced research can reduce the country’s reliance on imported diagnostics and therapeutics.

From these examples, it is clear that women scientists’ and researchers’ contributions are a central pillar of the national R&D ecosystem.

A Regional And Global Perspective

The UAE’s experience is instructive for the wider region. Across the Arab world, up to 57% of STEM graduates are women, yet the MENA region maintains one of the lowest female workforce participation rates globally at 19%. Saudi Arabia’s Vision 2030 has made notable progress, with women’s workforce participation reaching 36.2% and women now comprising 40.9% of the Kingdom’s researchers. The challenge across the GCC and MENA is consistent: converting educational attainment into sustained professional participation and research output. Globally, only one in three researchers is a woman, and parity in engineering, mathematics, and computer science is not projected until 2052. UNESCO’s 2026 International Day of Women and Girls in Science theme — “From Vision to Impact” — captures this urgency well.

The Way Forward: From Vision To Impact

As an academic working at the intersection of artificial intelligence and healthcare research in Dubai, I witness this potential daily — in students who arrive with rigour and ambition, in researchers producing work that stands alongside the best globally, and in a national ecosystem that increasingly treats women’s scientific participation as a strategic priority rather than a social courtesy. But policies alone do not produce innovation. What produces innovation is funding, access to facilities, clear pathways from research to commercialisation, and the recognition that a woman scientist publishing a patent in the UAE is building national capability in exactly the same way as the infrastructure projects that make headlines.

Sustained commitment is key — from governments, institutions, and the private sector — to ensure that every woman scientist in this region has the funding, the platforms, and the pathways to convert her research into national impact. When women scientists thrive, nations innovate faster. The UAE understands this. Now it must ensure the rest of the ecosystem does too.

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Tech Features

WOMEN IN AI AND DATA SCIENCE: WHO IS BUILDING THE ALGORITHMS THAT SHAPE OUR FUTURE?

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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.

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Tech Features

INSIDE THE TECHNOLOGY THAT MAKES HUAWEI FREECLIP THE BEST OPEN-EAR EARBUDS!

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White HUAWEI FreeClip open‑ear earbuds inside an open charging case on a table, with a smartphone, Christmas tree, lights, and wrapped gift boxes in the background.

It has been two years since the debut of the original HUAWEI FreeClip, Huawei’s first-ever open earbuds that took the market by storm. Its massive popularity proved that the world was ready for a new kind of listening experience. The new HUAWEI FreeClip 2 tackles the hard challenges of open-ear acoustics physics head-on, combining a powerful dual-diaphragm driver with computational audio. It delivers depth and clarity, which was once thought impossible with an open-ear design.

Solving the acoustic limitations of open-ear audio alone would have been sufficient to make the HUAWEI FreeClip 2 our pick for best open-ear audio. But it is way more than that.

Comfortable C-Bridge design

The HUAWEI FreeClip 2 earbuds weigh only 5.1 g per bud, a 9% reduction from the previous generation. This lightweight architecture ensures an effortless experience, perfect for long calls, workouts, and commutes, allowing you to wear them all day without fatigue. The comfort bean is 11% smaller than the previous model, yet the design provides a secure fit that prevents the earbuds from falling out, even during intense activity.

Constructed from a new skin-friendly liquid silicone and a shape-memory alloy, the C-bridge is 25% softer and significantly more flexible than its predecessor. Finished with a fine, textured surface, it ensures a comfortable, irritation-free wearing even after extended use.

Adaptive open-ear listening

The acoustic system has been significantly upgraded, featuring a dual-diaphragm driver and a multi-mic call noise cancellation system. This setup not only delivers powerful sound but also maximises space efficiency. That’s why, despite their small size, these earbuds can deliver substantial acoustic performance.

The Open-fit design of the earbuds demands high computing power to maintain sound quality and call clarity. The HUAWEI FreeClip 2 offers ten times the processing power of the previous generation, serving as Huawei’s first earbuds to feature an NPU AI processor for a truly adaptive experience. The new dual-diaphragm driver includes a single dynamic driver with two diaphragms, effectively doubling the sound output within a compact space to provide a significant boost in volume and bass response.

Furthermore, the earbuds dynamically detect surrounding noise and adjust volume and voice levels in real-time. If the environment is too noisy, the system uses adaptive voice enhancement to specifically boost human frequencies, ensuring you never miss a word of a podcast or audiobook. When you return to a quiet environment, the earbuds automatically settle back to a comfortable volume level.

Crystal clear calls

To ensure call quality in chaotic environments, the HUAWEI FreeClip 2 utilises a three-mic system combined with multi-channel DNN (Deep Neural Network) noise cancellation algorithms. This system intelligently identifies and filters out ambient noise. Thanks to the NPU AI processor, the earbuds automatically enhance voice clarity, ensuring your conversations remain crisp regardless of your surroundings.

Battery life and charging

With the charging case, the HUAWEI FreeClip 2 offers a total battery life of 38 hours, allowing users to enjoy music throughout a full week of commuting on a single charge. On their own, the earbuds last for 9 hours—enough for a full workday of uninterrupted calls. For those in a rush, just 10 minutes of fast charging in the case provides up to 3 hours of playback. For added convenience, they support wireless charging and are compatible with watch chargers.

Rated IP57, the earbuds are resistant to sweat and water. They can easily withstand intense workouts or even a downpour.

Connectivity

The earbuds support dual connections and seamless auto-switching across iOS, Android, and Windows. When connected to EMUI devices, you can even switch audio between more than two devices. Additionally, when connected to a PC, the earbuds allow you to answer an incoming call without disconnecting from or interrupting your conference setup.

It is, quite simply, a pair of earphones reliable enough for the gym, the office, and the commute.

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