Tech Features
Unlock the Power of AI: A Guide for Enterprises
By Alaa Antar – Regional Sales Manager, Liferay
AI is revolutionizing enterprises by enhancing efficiency, personalizing customer experiences, and unlocking new business opportunities. With Machine Learning (ML) and Generative AI (GenAI) driving automation and data-driven insights, organizations can streamline operations, optimize decision-making, and foster innovation—while ensuring ethical AI practices that promote fairness, transparency, and security in a digital world.

While our introduction to Artificial Intelligence started as a sci-fi fantasy some decades back, today, it is rapidly intertwining with all things digital to infuse accuracy and generate quick results. AI underpins many aspects of our daily lives, often working behind the scenes to personalize our experiences, optimize processes, and even entertain us. From unlocking smartphones with facial recognition to receiving accurate product recommendations online, AI has become an integral part of our interactions with technology. According to PwC, the Middle East, is poised to become a global AI hub, and anticipated to accrue US$320 billion in AI related benefits by 2030.
In today’s fast-paced digital landscape, delivering exceptional customer experiences is paramount. AI, low-code development, and automation are transforming the way businesses interact with their customers. By harnessing the power of these technologies, organizations can streamline operations, personalize interactions, and drive innovation.
Understanding AI, ML, and GenAI
At its core, artificial intelligence refers to the ability of machines to mimic human cognitive functions without explicit programming. These encompass a wide range of capabilities, such as learning and problem-solving, visual perception, speech recognition, and language translation with commonly known examples of Siri, ChatGPT and more.
Artificial Learning (AI) usually refers to the field of machine learning. But AI can do more than just learn from data; it can also reason, make decisions, solve problems, and be creative.
As a subset of Artificial intelligence, Machine Learning (ML) powers many AI applications encountered daily. ML uses an algorithm, often referred to as a model, to analyze and extract patterns from data. . Over time, the models become adept at making predictions, classifications, and recommendations, automating tasks, and improving decision-making – all based on the learned pattern
Using ML and GenAI to Create Business Value
Early adopters of AI, ML, and GenAI gain a competitive edge. For example, both ML and GenAI offer great opportunities to unlock the hidden potential within the data in enterprises. ML uncovers valuable insights to inform strategies, while GenAI transforms content creation processes and personalize customer interactions.
Cumulatively, through a systematic leverage of AI, organizations improve decision-making, automate and streamline operations, and enhance customer experiences.
Practical examples of GenAI in the Enterprise:
- In customer service, GenAI can handle real-time language translation to support agents responding to customer queries from multiple regions. AI-powered chatbots can answer routine questions, engage in dynamic conversations, offer empathetic responses. By offloading common inquiries, human agents can focus on complex, high-value tasks, leading to improved efficiency and enhanced customer satisfaction.
- In marketing, GenAI can support generating personalized marketing copy, headlines and social media posts based on target audience preferences. GenAI can even be trained on a company’s brand voice and product data, automatically crafting unique descriptions for online stores.
- In product design, GenAI can assist by generating design variations or optimizing product descriptions for different markets and target groups. If trained on existing product data and user reviews, GenAI can suggest design iterations to address customer pain points or cater to specific market preferences, allowing for data-driven product development and accelerating time-to-market.
- In media production, GenAI can assist in scriptwriting, music composition, and movie trailers.
Responsible AI: A Crucial Consideration
Although AI offers immense potential, it also demands careful consideration of ethical implications. Models learn from data, and if that is biased, the resulting outputs can lead to discriminatory outcomes. Additionally, the lack of transparency in some AI algorithms can make it difficult to understand how they reach their conclusions. That’s why ensuring responsible AI development and use is paramount. Here’s why:
- Fairness and bias – Biased training data can lead to biased outputs. Businesses should scrutinize data and employ debiasing techniques to provide fairness, accountability and transparency in AI.
- Transparency and trust – Algorithms that are a “black box” can erode trust. Businesses should strive for transparency in AI decision-making processes and provide explanations for outputs, allowing users to assess their validity. Users deserve explanations for GenAI outputs and an understanding of how the AI arrived at its results.
- Human oversight. AI and ML should augment, not replace human judgement. A “human-in-the-loop” approach ensures ethical considerations are factored in and safeguards against unintended consequences.
- Privacy and security. AI systems that handle sensitive data necessitate robust privacy and security measures. Enterprises should comply with data protection regulations and implement appropriate safeguards to protect user privacy.
Embracing AI is not just about adopting new technologies—but about rethinking business strategies. Integrating AI, ML, and GenAI into daily operations can reveal hidden efficiencies, enable personalization, spark innovation, and secure a competitive edge in a digital world.
In addition, Open source DXP platforms such as Liferay encourage organizations to adopt a BYOAI (Bring your own AI) approach. This facilitates a formidable combination of Gen AI with DXP platforms, driving advanced results and widening new possibilities of use cases through combined features. As an example, Liferay’s robust out-of-the-box content management features simplifies social media posting through a tailored approach to communicate with audiences using the company’s preferred AI engines. Organizations can then accurately schedule and publish content on different platforms such as FB, Twitter and LinkedIn. This empowers a marketeer with seamless integration to streamline different workflows, save time and ensure consistent messaging across different channels making it an essential tool to enhance social media strategy across content and images.
By breaking down the complexities of AI, enterprises can embark on this journey with confidence. Implemented ethically and responsibly, AI can fuel sustainable growth, enhance decision-making, please customers, and shape a future where human expertise and AI capabilities work in harmony.
Tech Features
HOW WOMEN SCIENTISTS CAN ACCELERATE NATIONAL INNOVATION GOALS
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.
Tech Features
WOMEN IN AI AND DATA SCIENCE: WHO IS BUILDING THE ALGORITHMS THAT SHAPE OUR FUTURE?
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.
Tech Features
INSIDE THE TECHNOLOGY THAT MAKES HUAWEI FREECLIP THE BEST OPEN-EAR EARBUDS!
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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