Tech Features
Sustainable Tech: How Globant Shapes a Greener Tomorrow
By Federico Pienovi, CEO of New Markets at Globant

In today’s business landscape, the intersection of technology and sustainability is no longer optional—it’s imperative. Globant is pioneering this path, using digital innovation to create measurable environmental impact. Through AI, blockchain, and culture-driven initiatives, the company is redefining how modern enterprises approach sustainability.
Driving Impact Through AI-Powered Efficiency
At the heart of Globant’s sustainability mission lies artificial intelligence. Through its Sustainable Business Studio, Globant embeds AI into core operations, optimizing energy usage and significantly reducing carbon emissions.
For example, AI combined with IoT and data analytics has helped improve energy efficiency by up to 40%, contributing to potential carbon reductions equivalent to the lifetime emissions of 50 million cars.
This isn’t a distant vision—it’s already happening. In real-world scenarios like smart factories and commercial buildings, AI predicts energy usage and automatically adjusts systems to reduce waste. Digital twins, machine learning models, and real-time analytics work together to balance performance with environmental responsibility.
Blockchain: The Foundation of Trust and Transparency
While AI commands the spotlight, blockchain technology plays an equally critical role in Globant’s green strategy. From traceable supply chains to tamper-proof carbon credit systems, blockchain delivers the transparency needed to make sustainability accountable.
In addition, Globant is exploring peer-to-peer renewable energy trading, where blockchain ensures fairness and verification. The company’s blockchain-powered platforms allow consumers and corporations alike to track the full lifecycle of products—from sourcing and production to recycling.
NFTs with Purpose: Tokenizing Nature Through Sustainable Tech
Globant’s use of NFTs and digital tokens isn’t about speculation—it’s about measurable impact. One bold example is the tokenization of Amazon rainforest segments. These tokens don’t just represent digital ownership—they act as tangible support mechanisms for conservation efforts.
This approach transforms NFTs into tools of ecological engagement, allowing individuals and companies to contribute to preservation with verifiable, lasting results.
Culture in Action: Sustainability from Within
Of course, true sustainability doesn’t end with tech. It requires culture—and at Globant, sustainability is woven into the company’s DNA. Their Be Kind initiative empowers every employee (or “Glober”) to make environmentally responsible choices at a personal level.
Whether through Green IT Training, which teaches digital sobriety, or internal campaigns and volunteer programs, Globant nurtures a sense of collective ownership in its environmental mission.
Sustainability at Globant isn’t a mandate. It’s a movement.
Global Standards, Local Execution
Globant’s operations remain carbon neutral, aligned with frameworks like the Science Based Targets initiative (SBTi) and the Task Force on Climate-Related Financial Disclosures (TCFD). These aren’t just checkboxes—they reflect a commitment to measurable results and transparent reporting.
Moreover, by embedding sustainability into client-facing solutions, Globant helps other organizations adopt responsible practices too—amplifying its impact across industries.
Looking Ahead: Tech as a Catalyst for Change
As the world approaches critical milestones like Vision 2030, the urgency for actionable climate strategies has never been higher. Globant is leading by example—proving that sustainability and growth are not only compatible, but mutually reinforcing.
“Sustainability isn’t just an agenda—it’s a revolution in the tech landscape,” writes Pienovi.
In essence, sustainable tech is no longer a niche—it’s a blueprint. Companies that fail to evolve will be left behind. But those that embrace innovation, like Globant, are showing that technology can protect the planet while driving performance.
Worth a read—just published Leveraging Big Data Technologies for Enhanced Architecture
Tech Features
THE UAE’S NEXT AI CHALLENGE ISN’T INFRASTRUCTURE, IT’S ENABLEMENT.
By: Bindesh Vijayan, Chief Technology Officer at Myndlab
There is a line that gets repeated at every tech conference in Dubai, in every government briefing, and across most pitch decks: the UAE is building the future. Artificial intelligence is projected to contribute $96 billion to the UAE’s GDP by 2031, according to PwC and corroborated by the UAE’s own National AI Strategy. The country has invested AED 543 billion in AI since 2024 alone, as confirmed by Omar Sultan Al Olama, the UAE’s Minister of State for Artificial Intelligence. And according to Microsoft’s AI Diffusion Report for Q1 2026, the UAE has become the first country in the world to cross the 70 percent threshold for AI tool adoption among its working-age population.
These are not vanity metrics. They reflect a deliberate national strategy that has positioned the UAE as one of the world’s most ambitious AI markets and laid the foundations for long-term technological leadership. Yet despite that progress, a disconnect is emerging between the country’s AI ambitions and the day-to-day reality of the people building products within the ecosystem.
The Gap Between AI Infrastructure and AI Adoption
Much of the discussion around AI in the UAE has focused on infrastructure, whether that is sovereign AI models, data center investments, national strategies, or the capital required to support them. These are all essential components of a successful AI ecosystem. However, infrastructure alone does not create products. Founders, developers, and businesses still need the tooling layer that sits between AI capability and real-world execution.
This is precisely the challenge a new generation of AI-native development platforms is trying to solve: embedding software engineering best practices directly into the building process so that users can focus on the product rather than mastering prompt engineering.
One of the clearest examples of this challenge is language. Arabic is spoken by more than 400 million people across 22 countries. Yet developers across the region still rely heavily on tools that were primarily designed for English-speaking users. Researchers at Nature Middle East have previously highlighted how the relative lack of robust Arabic language models continues to create limitations around linguistic nuance, dialects, and cultural context.
At the same time, the developer tools, AI coding assistants, and product-building platforms that define the modern software stack were largely built around Western markets and workflows. They assume a particular type of user, a particular language, and a particular development environment. For many builders in the GCC, those assumptions become a source of friction that compounds throughout the product development lifecycle.
A founder in Dubai building a fintech product for Emirati consumers has to work through documentation written in English, prompts that perform better in English, and interfaces that treat right-to-left text as an afterthought.
The challenge is not that these tools fail outright. Rather, they introduce small points of friction throughout the development process that compound over time, affecting productivity, iteration cycles, and ultimately product delivery. Over time, that friction compounds across teams, product cycles, and entire businesses, becoming the difference between shipping and not shipping.
We’ve Seen This Before
This pattern plays out clearly in payments, an industry where many founders across the region have spent much of their careers. The UAE has built a sophisticated financial infrastructure, but for years, the tooling that sat on top of that infrastructure, the APIs, developer documentation, and integration frameworks, was largely oriented toward Western payment methods, Western card schemes, and Western compliance frameworks. Local founders had to build workarounds. Some of those workarounds were innovative, but workarounds are not a strategy. More often than not, they are a sign that the underlying stack was never designed for the people using it.
The same lesson applies to AI. Infrastructure creates possibilities, but it does not automatically create innovation. Innovation happens when builders can move quickly, efficiently, and confidently on top of that infrastructure. If the tools developers use every day are not designed for the realities of this market, then the UAE’s AI ambitions risk being partially realized by people working around their environment rather than with it.
What Comes Next
There is a real opportunity here to address the gap between the infrastructure the UAE has built and the tools its founders, developers, and businesses actually need.
The UAE has already demonstrated that it can build AI infrastructure at scale. It has invested heavily in research, talent, adoption, and national AI initiatives, creating one of the most ambitious AI ecosystems anywhere in the world.
The next phase of that strategy is not simply building larger models or attracting more capital. It is ensuring that the people responsible for creating products, launching companies, and deploying AI solutions have the tools they need to succeed. It also means reducing dependence on a small number of external AI providers. As AI becomes embedded in critical business and government workflows, questions around privacy, data governance, and long-term resilience become increasingly important. Building capable regional AI ecosystems is not simply about innovation; it is about ensuring that organisations can deploy AI with greater control, confidence, and sovereignty.
The countries that win the next decade of technology are not necessarily the ones that spend the most money. They are the ones where the people doing the building have the right tools for the job.
Infrastructure creates possibility. Tooling turns possibility into innovation. The next phase of the UAE’s AI story will be defined by how effectively it enables the people doing the building.
Tech Features
ENGINEERING INTELLIGENCE IN EDUCATION: PREPARING YOUNG WOMEN FOR FUTURE TECH LEADERSHIP

Dr Esraa Khatab, Assistant Professor at the School of Mathematical and Computer Sciences, Heriot-Watt University Dubai
As we celebrate International Women in Engineering Day (INWED), attention is increasingly focused on how to prepare young women not only to participate in engineering but to lead its future. In a world shaped by artificial intelligence, sustainability challenges, and rapid digital transformation, education must go beyond technical instruction. It must cultivate what we can call engineering intelligence, a combination of technical expertise, problem-solving ability, creativity, and leadership confidence.
For young women, this preparation is most effective when education is intentionally designed to inspire, support, and position them as future innovators and decision-makers.
Inspiring Young Women Through Meaningful Learning
Engaging young women in engineering begins with making learning relevant and purposeful. When engineering is connected to real-world challenges, such as improving healthcare systems, designing sustainable cities, or developing climate solutions, it resonates strongly with students who are motivated by impact.
Project-based learning plays a key role here. When young women work on designing smart applications, building prototypes, or solving community challenges, they begin to see themselves as capable engineers contributing to society. Thes experiences move engineering from an abstract concept to a meaningful pathway where their ideas matter.
Initiatives such as the UAE’s “One Million Arab Coders” and international programs like “Girls Who Code” have successfully introduced thousands of young women to coding, AI, and digital innovation. These initiatives are powerful not just because of the skills they teach, but because they create an early sense of belonging in technology-driven environments.
Mentorship: Unlocking Potential and Building Confidence
For young women, mentorship is a transformative element of engineering education. It provides not only guidance but also reassurance, helping students navigate academic and career pathways with clarity and confidence.
Connecting young women with mentors, whether through universities, industry partnerships, or outreach programs, offers them valuable insights into emerging fields such as artificial intelligence, robotics, and renewable energy. These relationships make career paths more tangible and achievable.
In classroom settings, mentorship can be embedded into learning through project collaborations and industry engagement. When young women receive feedback from
professionals, present their ideas, and engage in real-world problem-solving, they begin to develop both confidence and professional identity.
Mentorship also nurtures leadership. By observing and interacting with experienced professionals, young women gain exposure to decision-making, teamwork, and innovation processes, essential components of future tech leadership.
Expanding Opportunities Through STEM Outreach
STEM outreach initiatives are vital in reaching young women early and sustaining their interest in engineering pathways. Programs that focus on hands-on, creative engagement, such as robotics competitions, coding bootcamps, and innovation labs, are particularly effective in building confidence and curiosity.
These initiatives create safe and encouraging environments where young women can experiment, take risks, and learn collaboratively. Importantly, they shift the narrative from simply learning technology to actively creating it.
Digital platforms have further expanded opportunities for young women in engineering. Virtual labs such as “MIT OpenCourseWare” and interactive simulations (e.g., PhET) allow learners to experiment and build practical skills remotely, with research showing strong gains in engagement and motivation. Online hackathons, including initiatives like the “UAE InnovAIte AI” Hackathon, provide young women with collaborative spaces to design real-world solutions using emerging technologies. At the same time, AI-powered tools such as “Khan Academy’s Khanmigo” offer personalized guidance, helping learners build confidence through continuous, self-paced support.
Together, these platforms create flexible and inclusive pathways that enable young women to actively engage, experiment, and grow within today’s rapidly evolving technological landscape. By introducing young women to emerging technologies early, outreach programs help them build familiarity and confidence in fields that will define the future of work.
Encouraging Young Women to Lead in Emerging Fields
Emerging engineering domains, such as artificial intelligence, smart systems, biotechnology, and sustainable energy, offer significant opportunities for innovation and leadership. Encouraging young women to explore these areas requires intentional effort within education systems.
This can be achieved through:
- Early integration of advanced topics: Introducing AI, data science, and sustainability concepts at foundational levels.
- Interdisciplinary approaches: Encouraging young women to apply engineering skills in healthcare, environmental science, and social innovation.
- Experiential learning: Providing opportunities for internships, research projects, and innovation challenges in emerging fields.
These experiences allow young women to build not only technical expertise but also the confidence to navigate complex, real-world challenges. They begin to see themselves as contributors to cutting-edge developments, rather than observers.
Building Confidence and Leadership Identity
For young women to thrive in engineering, education must also focus on building confidence and leadership skills. This includes creating environments where their voices are heard, their ideas are valued, and their contributions are recognized.
Encouraging young women to lead team projects, present their work, and participate in competitions helps them develop essential soft skills such as communication, collaboration, and critical thinking.
Representation also plays an important role. Highlighting the achievements of women engineers and innovators, both globally and within local communities, reinforces the message that leadership in engineering is both attainable and expected.
Importantly, leadership development should be embedded into the learning journey. Innovation challenges, entrepreneurship programs, and community-based projects provide platforms for young women to take initiative and drive impact.
Looking Ahead: Empowering Young Women to Shape the Future
The future of engineering will be defined by those who can think creatively, solve complex problems, and lead with vision. Preparing young women for this future is not just about education, it is about empowerment.
By combining meaningful learning experiences, strong mentorship, expanded outreach, and opportunities in emerging technologies, we can create an ecosystem where young women thrive as engineers and leaders.
As we celebrate INWED, the focus is clear: to ensure that young women are equipped not only with skills, but with the confidence and ambition to lead. When this happens, they do more than contribute to technological advancement, they shape it.
Tech Features
FIVE WAYS UAE WORKFORCE PLANNING IS CHANGING IN 2026
The UAE is entering a more complex phase of workforce growth. Hiring momentum remains strong, with the country recording a Net Employment Outlook of 60% for Q2 2026, placing it among the strongest employment markets globally. Yet the main challenge for companies is whether their employment structures, immigration planning, compliance systems, and HR leadership can support growth at scale.
Aethra Advisory, a UAE-based global hiring strategy and mobility architecture firm, outlines five shifts companies should prepare for as compliance, immigration, and HR become more connected.
HR is becoming workforce architecture
HR can no longer be treated as an administrative function focused only on recruitment, onboarding, contracts, and employee relations. In 2026, HR leaders are expected to help design the workforce model itself. That includes where a company hires, which employment structures it uses, how talent moves across borders, and where compliance risk may appear. A hiring decision is now linked to visa eligibility, payroll structure, sponsorship, worker classification, relocation timelines, and long-term operating needs.
Many companies still hire first and address structure later. The consequences often emerge months afterwards, when employment models become costly, difficult to manage, or unable to support growth.
AI is entering recruitment and workforce planning
Companies are using AI to screen CVs, match candidates to roles, automate outreach, schedule interviews, assess skills, and generate workforce insights. Used well, it can make hiring faster and more consistent, especially in high-volume recruitment environments.
A 2025 field experiment involving around 37,000 applicants found that 54% of candidates assessed through an AI-assisted recruitment pipeline passed the final human interview, compared with 34% of candidates assessed through a traditional pipeline. However, AI does not replace human judgement. Companies still need clear hiring criteria, documented decision-making, oversight and an understanding of how recommendations are generated and reviewed.
Companies are moving into global talent systems
Many companies make the UAE a base for regional and international expansion due to its business-friendly policies and strategic location. Local companies are hiring across borders, global firms are entering the UAE, and leadership teams are being built across multiple jurisdictions. In fact, the cross-border workforce and migration solutions market is projected to reach $11.37 billion by 2033, growing at an annual rate of 11.8%.
For employers, hiring can no longer be treated as a local HR process. Companies must make deliberate decisions about how they enter new markets and engage talent. Some may use an Employer of Record to hire quickly, while others may establish a local entity to gain greater control. In some cases, relocating and sponsoring employees will be the right approach or engaging contractors or building a longer-term market entry structure may be more suitable. Each route carries different implications for cost, compliance, operational control, and future scalability.
Employment models are becoming more hybrid
As companies scale, informal arrangements become harder to manage. A single UAE business may now have locally sponsored employees, remote workers, consultants, contractors, relocating workers, etc. This gives companies more flexibility, but also creates operational risk when obligations are not understood from the start. Worker classification, payroll treatment, benefits, visa eligibility, contract terms, management control, and termination rules can vary depending on how a person is engaged. Employers need clear structures defining employment status, work location, applicable law, and how each relationship is governed.
Regulation is influencing hiring decisions
In the UAE, hiring depends on more than finding the right candidate. Companies need the right regulatory setup before they can move quickly. Licensing gaps, unclear sponsorship routes, incomplete documentation, or a mismatch between the role and the employment structure can still delay a strong hire.
This makes compliance and immigration planning an early hiring priority. Companies should understand the requirements before entering a market, confirming a hire, or committing to a relocation timeline.
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