Is Automation Really the Answer? Regional Insights

Apr 11, 2026

Is Automation really the Answer? The Hidden Challenge Inside the Middle East’s Recycling Boom

Egis Published on 10 April 2026

*As published in Waste & Cycling – April 2026

Is Automation really the Answer? The Hidden Challenge Inside the Middle East’s Recycling Boom. Let us what Abhijeet Chaudhary and Teeba Allaw of Egis say.

Across the Gulf Cooperation Council, recycling is moving from the margins to the mainstream. Governments are setting ambitious circular economy and waste diversion targets under national programs such as Saudi Arabia’s Vision 2030, Qatar National Vision 2030, the UAE Net Zero Strategy 2050 and Oman’s Vision 2040. These frameworks are reinforced by flagship projects such as NEOM, where sustainability and resource recovery are embedded in the city’s design. Collectively, they are backed by large-scale investment in new infrastructure, from waste-to-energy plants to material recovery facilities, designed to keep resources in circulation and reduce dependence on landfills.

Within this regional transition, material recovery facilities are taking centre stage. The latest plants combine conveyors, optical sorters and robotics to process hundreds of tons of recyclables each day. Automation aligns with the wider digital agenda promoted through the UAE National AI Strategy 2031, Qatar’s National AI Strategy and Saudi Arabia’s Data and AI Strategy. Together, these efforts signal a determined move toward smarter, data-led waste systems and measurable diversion outcomes.

Yet amid this momentum lies a practical design question: how much automation is enough? Can technology alone overcome the region’s complex waste composition, or does lasting efficiency depend on combining machines with informed human oversight?

Across Europe and the United States, recycling plants have evolved quietly but decisively. Cameras and robotic arms now handle tasks that once depended entirely on manual sorting. Computer vision distinguishes between aluminium cans, coloured plastics and glass fragments while learning from every batch it processes. In regions where households already separate their waste, these tools have raised recovery rates by as much as twenty percent and reduced worker exposure to hazards on sorting lines.

The GCC starts from a different baseline. According to the Gulf Statistical Center, municipal waste in member states contains between fifty and sixty percent organic material, while paper, cardboard and plastics form less than a quarter. This mix leaves recyclable streams heavily contaminated. In the United Arab Emirates, for example, studies show impurity levels of thirty to forty percent in recyclable waste. Behavioural patterns add to the challenge: only about one-third of household’s separate recyclables at home, while more than half still dispose of all materials together. When facilities receive such mixed feedstock, even advanced robotics struggle to produce clean and valuable output.

Investment patterns further shape outcomes. Robotic sorting lines, recognition systems and specialised software require high initial capital and continual spending on maintenance, energy and skilled technicians. In Europe and the United States, consistent waste data and stable recycling policies make such investments predictable. In the GCC, data on waste generation and composition is collected by national authorities but is not always publicly available or detailed enough for private operators to base technology decisions on. This limited visibility makes it harder to compare performance or evaluate long-term returns. That is beginning to change. Policy initiatives such as Dubai’s Green Building System, Saudi Arabia’s National Environment Strategy and Qatar’s National Waste Management Framework are improving data transparency and standardising recycling metrics. As information quality improves and source separation becomes more common, operators will be able to apply automation where it delivers measurable gains in purity and recovery instead of adopting technology for its own sake.

Building the next generation of waste infrastructure in the GCC is not only about installing new machines. It is about knowing what level of automation truly fits the market, what it costs to sustain and how it supports long-term diversion goals. These are complex questions that sit between policy, economics and technology. Egis works in this space, helping governments and municipalities interpret automation and translate it into practical, scalable design decisions.

Every engagement begins with data. Egis studies what the waste stream actually contains, how separation occurs at the source and what recovery levels are realistic within current market conditions. From that foundation, the firm assesses where automation improves purity and throughput and where simpler processes ensure resilience and easier maintenance. This approach shaped Egis’s advisory work for one of the GCC municipalities developing the region’s largest integrated waste-to-energy and material recovery facility under a public-private partnership model. The project combines large-scale energy recovery with a high-capacity facility for recyclables, showing how technology can serve as an enabler rather than a headline feature.

Egis also connects the GCC with global innovation. With offices and technical teams in more than one hundred countries, the firm maintains constant dialogue with technology developers, equipment suppliers and research partners from Europe to Asia and North America. This global reach allows Egis to test new ideas and offer governments a clear view of what truly performs under regional conditions. It replaces buzzwords with evidence and helps public authorities make confident, data-driven investment choices.

Across the region, Egis applies this collective intelligence to one persistent challenge: turning available waste data into actionable design guidance. By combining local datasets, site audits and digital modelling, the firm helps cities and ministries understand how automation influences performance, cost and operations. In doing so, Egis brings clarity to one of the most complex questions in modern recycling: how much technology is enough, and where human insight still adds the greatest value.

Across the GCC, the new measure of progress in recycling is not how automated a plant is but how well its design fits local reality. Real innovation lies in balance, where technology supports the goal of better recovery instead of becoming the goal itself. Consultants are central to that transformation. They link policymakers who set direction with technology creators who build solutions. Through this collaboration, automation becomes a means of solving the waste problem rather than a costly race to install equipment.

Egis stands at the centre of this change. Its strength lies in translating complexity into clarity and turning global technology insight into practical, data-driven choices for cities and ministries. By bringing together markets, governments and innovators, Egis is helping shape a circular economy in which progress is measured not by automation but by outcomes: cleaner materials, smarter investment and stronger systems.

Is Automation really the Answer? The Hidden Challenge Inside the Middle East’s Recycling Boom

Teeba Allawi, Graduate Environmental Consultant

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Abhijeet Chaudhary, Senior Waste & Resource Management Consultant

AI Data Centers And The Thirst For Water

Apr 9, 2026

A modern server room featuring network equipment with blue illumination. Ideal for technology themes. by Panumas Nikhomkhai via pexels

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AI Data Centers And The Thirst For Water In MENA

Author: Fanack Water Editorial Team

Artificial intelligence needs vast computing power, and that power now depends on water. In the Middle East and North Africa (MENA), one of the world’s driest regions, this creates a serious new pressure on already scarce resources.

Why AI Data Centers Need Water

AI data centers generate intense heat as servers train and run large models. Operators often rely on water-based cooling, either through evaporative systems that directly consume freshwater or through chillers and towers that use large volumes indirectly. Water is also embedded in the electricity that powers these facilities, because many power plants themselves need water for cooling.

Recent research shows how quickly this adds up. Training a single large model can consume millions of liters of water when you include both onsite cooling and the power supply. One study estimates that answering 20 to 50 AI queries can use the equivalent of a 500‑milliliter bottle of water, when you count the full water footprint of the data center and grid.

A Thirsty Technology In The World’s Driest Region

MENA holds about 6.3% of the world’s population but only around 1.4% of its renewable freshwater, making it the most water‑stressed region on Earth. Of the 17 most water‑stressed countries globally, 11 are in MENA, and some forecasts warn that almost the entire population could face acute scarcity by 2050 if trends continue.

At the same time, Gulf states and other regional economies are racing to become AI and cloud hubs. New data centers are rising in Saudi Arabia, the United Arab Emirates, Qatar and beyond, often in areas where rainfall is minimal and summer temperatures soar above 40 degrees Celsius. Analysts expect regional data center water use to grow rapidly this decade as AI clusters demand denser, more water‑intensive cooling.

Desalination, Energy And The Water–Energy Nexus

Because natural freshwater is so limited, many MENA countries depend heavily on desalination. In Kuwait, about 90% of drinking water comes from desalinated sources; in Oman it is around 86%, in Saudi Arabia nearly 70%, and in the UAE more than 40% of municipal supply. The region already accounts for roughly 42% of global operational desalination capacity, with thousands of plants producing tens of millions of cubic meters per day.

Desalination is lifeline and burden at once. It is energy‑intensive and can harm marine ecosystems through brine discharges, so each extra unit of water for cooling AI infrastructure can also mean more emissions and coastal impacts if powered by fossil fuels. Experts argue that integrating solar and wind power into desalination and water treatment is essential to keep this nexus from becoming a vicious circle.

Emerging Solutions For Water‑Smart AI

There are promising technical responses. In the MENA, some large data centers now use closed‑loop systems and onsite treatment that recycle up to 96% of process water. Mega‑campuses in Saudi Arabia and the Gulf are pairing photovoltaic‑powered desalination with advanced cooling designs, using underground thermal storage and waste‑heat recovery to cut both water use and energy demand.

Globally, major cloud providers are also rethinking their strategies. Microsoft’s own projections showed that its annual water use for data centers could more than triple by 2030, before it revised designs and targets to curb the increase. Independent reviews still find sharp year‑on‑year rises in water consumption for Microsoft and Google, underlining how fast AI is outpacing earlier efficiency gains.

Policy And Transparency Gaps

Despite the scale of the challenge, water data for AI facilities in MENA remains patchy. Many companies do not disclose their withdrawals or consumption, because regulation has not yet caught up with the speed of investment. This lack of transparency makes it hard for communities and policymakers to judge trade‑offs between digital growth and local water security.

Some governments and regional bodies are starting to respond. New water‑energy strategies, desalination partnerships and water security task forces in the Gulf link future infrastructure to renewable energy, wastewater reuse and stricter efficiency standards. To keep AI compatible with a liveable future in MENA, these efforts need to go further—making water‑smart cooling, regenerative desalination and full public reporting standard features of every new data center, not optional extras.

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AWS Bahrain Disruption Exposes Cloud Fragility Today

Mar 27, 2026

Bahrain, trade center, skyscraper, Manama, Bahrain World Trade Centre, City, WTC, Bahrain, Manama by IrinaKar via pixabay

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AWS Bahrain Disruption Exposes Cloud Fragility: What this Means for Middle East’s Cloud Infrastructure

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The disruption has prompted enterprises to reassess cloud resilience strategies amid rising geopolitical risks, highlighting vulnerabilities in infrastructure reliance.

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By Pavneet Kaur – March 25, 2026

ITP.NET

Adrone-related AWS outage in Bahrain is forcing enterprises to rethink cloud resilience, multi-region strategy and infrastructure risk across the Middle East.

The recent AWS disruption, triggered by drone activity near critical infrastructure, has disrupted services and pushed enterprises to shift workloads across regions. For many organisations, this is a stark reminder that cloud computing infrastructure is still deeply physical.

In an official statement to ITP.NET, AWS ensured that the team is working with authorities, while securing their personnel and empowering affected customers with migration efforts.

“The AWS Bahrain Region has been disrupted as a result of the ongoing conflict. We are working closely with local authorities and prioritizing the safety of our personnel throughout our recovery efforts. We continue to support affected customers, helping them to migrate to alternate AWS Regions, with a large number already successfully operating their applications from other parts of the world. As this situation evolves and, as we have advised before, we request those with workloads in the affected regions continue to migrate to other locations.”

Behind every cloud platform are data centres tied to specific geographies, dependent on power, connectivity and regional stability. When a Bahrain data centre disruption occurs, the impact extends far beyond a single facility, affecting applications, platforms and users across the region.

Cloud disruption in the Middle East is a concentration problem

The bigger issue exposed by this AWS cloud disruption is not downtime, but infrastructure concentration risk. Across the Middle East cloud market, many enterprises rely heavily on a single hyperscaler or a single region, particularly AWS Bahrain, which has become a core hub for startups, fintech platforms and government workloads.

This centralisation improves efficiency and latency. It also creates a single point of failure.

When a cloud outage in Bahrain happens, multiple organisations face simultaneous disruption, highlighting the risks of over-reliance on a single cloud region.

Geopolitical risk is now a cloud computing risk

Unlike typical outages caused by software failures or power issues, this AWS outage in Bahrain was linked to regional instability.

That shifts the conversation. For CIOs and IT leaders, geopolitical risk is now directly tied to cloud infrastructure strategy. As the Middle East accelerates investments in AI, digital services and cloud adoption, physical threats to infrastructure are becoming part of the risk landscape.

“The lesson is straightforward: enterprises must diversify both geographically and across providers,” says Dmitrii Gartung, CEO, OneSun Capital – an eco-conscious industrial robotics and automation software provider.

Distributing your nodes across multiple countries is only half the strategy — if all those nodes sit within the same cloud ecosystem, a platform-level failure can take everything down simultaneously. The practical steps for CIOs are clear. First, implement true multi-cloud architecture — not just multi-region within one provider, but across independent providers. Second, consider supporting smaller, independent data centre operators rather than concentrating everything with hyperscalers. Large cloud providers are obvious high-value targets; smaller operators present a lower risk profile. Third, invest in high-availability cluster design with geographic distribution built in from the start, not bolted on as an afterthought.

Over-reliance on a single cloud region or provider is, frankly, a sign of taking shortcuts during deployment. Convenience should never come at the cost of resilience — especially in a region where infrastructure risks are real and evolving.”

Cloud strategy can no longer focus only on cost, scalability and performance. It must now account for regional security risks, infrastructure exposure and operational continuity.

Levent Ergin, Chief Strategist for Agentic AI, Regulatory Compliance & Sustainability at Informatica from Salesforce also adds to this:

Resilience is a shared responsibility, and in practice, failover, recovery, and validation sit firmly with the customer.

The immediate step for CIOs is to revisit how resilience is defined and operationalised within their organisations. This starts with making SLAs more explicit about shared responsibility and ensuring they go beyond infrastructure uptime to prioritise data integrity, portability, and recoverability.

Equally important is moving from static SLAs to actively tested ones. Defining recovery objectives on paper is not enough; organisations need to regularly test failover and recovery scenarios under real-world conditions to ensure they actually work when needed.

Cloud resilience depends on architecture, not just providers

Hyperscalers like AWS are built with redundancy, but enterprise cloud resilience depends on how systems are designed. Many organisations still operate on a single-region cloud deployment model, assuming uptime rather than engineering for failure. Best practices like multi-region cloud deployment, disaster recovery planning and multi-cloud strategy are often discussed, but not always implemented due to cost or complexity.

The Bahrain disruption highlights a critical gap.

When systems are not designed for failover, cloud migration becomes reactive instead of seamless, increasing downtime and operational risk.

From cloud-first to resilience-first strategy

The AWS Bahrain disruption signals a broader shift in enterprise thinking. The next phase of digital transformation in the region will move from cloud-first to resilience-first.

This includes:

Adopting multi-region cloud architecture to avoid regional outages
Exploring multi-cloud strategies to reduce vendor concentration risk
Strengthening disaster recovery and business continuity planning
Mapping dependencies across cloud, SaaS and third-party services

Echoing these observations is Santiago Pontiroli, Lead TRU Researcher at Acronis:

Multi-availability and multi-region architectures improve resilience, but only if they are deliberately designed. The main benefit is that data can survive localized failures. Cloud providers replicate across zones and regions, so loss of data is rarely the issue. The challenge is that availability of data does not automatically translate into availability of operations. If dependencies such as identity systems, control planes, or application layers are not designed to fail over, the business can still be disrupted even when the data is intact.

There is also a trade-off between resilience and complexity. Multi-region setups require planning around replication, consistency, failover logic, and cost. In many environments, replication is not fully implemented because of cost or operational overhead, which limits the actual resilience achieved.

Another factor is recovery time. Moving workloads between regions is technically feasible, but it is not always immediate. If replication is not already in place, migration can introduce downtime and operational friction. In practice, the benefit is clear: higher resilience. But the drawback is equally clear: without proper architecture, multi-region becomes an assumption of safety rather than a guarantee.

For governments and regulated industries in the Middle East, this is already driving conversations around sovereign cloud and data localisation.

For enterprises, it is quickly becoming a priority.

The bigger takeaway for Middle East enterprises

The AWS outage in Bahrain will likely be resolved without long-term impact.

But its significance lies elsewhere. It exposes how fragile cloud infrastructure can become when physical, regional and geopolitical risks intersect. The cloud remains powerful, scalable and essential.

Ergin puts it directly, “What this situation underscores is the need for a fundamental shift in mindset. Resilience can no longer be viewed purely through the lens of protecting against infrastructure-level failures, whether that’s power, networking, or even regional or geopolitical disruption. Instead, the focus needs to move towards ensuring that data itself can be reliably replicated and recovered, using metadata, lineage, and robust integration pipelines to maintain a strong recovery posture.”

Pavneet Kaur

Pavneet is the Editor of ITP.NET, where she leads content strategy and writes across its five brands. A technology writer by choice and passion, she breaks down complex trends in AI, cybersecurity, cloud,… More by Pavneet Kaur

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AI and Jobs in the Emerging and Developing Countries

Mar 26, 2026

Artificial intelligence is poised to be a major economic catalyst in the MENA region’s emerging and developing economies, with the potential to add $320 billion to the region’s economy by 2030. However, this digital transformation presents a double-edged threat. ERF

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AI and Jobs in the Emerging and Developing Countries

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What if artificial intelligence could become the most powerful driver of inclusive growth and job creation across emerging markets? Our latest report by Jeffrey D. Sachs, University Professor and Director of the Center for Sustainable Development, Columbia University outlines how artificial intelligence is redefining economic growth and job creation across emerging markets and developing economies. […]

PUBLISHED BY FII Institute – March 24, 2026

Download Publication

What if artificial intelligence could become the most powerful driver of inclusive growth and job creation across emerging markets?

Our latest report by Jeffrey D. Sachs, University Professor and Director of the Center for Sustainable Development, Columbia University outlines how artificial intelligence is redefining economic growth and job creation across emerging markets and developing economies (EMDEs), replacing outdated labor-intensive manufacturing models with a dynamic, AI-powered framework driven by productivity, skills, and service-sector expansion. The analysis reveals how AI can unlock trillions in value by boosting export competitiveness in agriculture, mining, and manufacturing while simultaneously fueling large-scale employment in healthcare, education, construction, tourism, and the rapidly growing creative economy. With a strong focus on human capital, smart urbanization, and innovative financing models such as education bonds and diaspora contributions, the report presents a bold, future-ready blueprint for inclusive and sustainable development, positioning AI not as a disruptor, but as a catalyst for long-term prosperity and global economic transformation.

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Prototype Driverless Taxi Unveiled in Astana Event

Mar 26, 2026

Astana cityscape featuring the iconic Bayterek Tower and modern architecture under cloudy skies. by Valeria Drozdova via pexels

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Prototype Driverless Taxi Unveiled in Astana

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@gov.kz

As part of the Nauryz celebrations in Astana, a demonstration run of a driverless vehicle developed at the Daulet Serikbayev East Kazakhstan Technical University (EKTU) was held. In the future, this prototype could become part of the city’s driverless taxi system.

The presentation took the form of a public demonstration for residents and visitors to Kazakhstan’s capital. According to the Astana City Administration, the vehicle’s software and test route were developed by specialists from the Luban Workshop, which opened at EKTU in Ust-Kamenogorsk in late 2023 with support from China’s Tianjin Vocational Institute.

The project is being implemented as part of an initiative to develop engineering competencies and introduce new technologies, ranging from alternative fuels to AI systems in the transport sector.

At the same time, an agreement was signed to establish the Kazakhstan Engineering Center for the Application and Development of Intelligent Automotive Technologies.

The demonstration run was organised by the Ministry of Artificial Intelligence and Digital Development in collaboration with the capital’s city administration and the IT company Astana Innovations.

The test took place at one of the city’s festive venues. Visitors were able to observe the autonomous vehicle in real time and assess its potential for use in an urban environment.

According to the organisers, the prototype demonstrated the potential for integrating AI technologies into Smart City systems, including navigation, data processing, and interaction with infrastructure.

Authorities view driverless transport as one of the key areas in the development of urban mobility. In the future, such solutions may be integrated into Astana’s infrastructure, including the launch of autonomous taxis.

It was previously reported that Kazakhstan plans to launch pilot projects for driverless taxis in the capital as early as 2026.

At the same time, work is under way to prepare road infrastructure. Digital “passports” for highways are being developed, which are expected to enable the future use of driverless trucks.

Dmitry Pokidaev

Is Automation Really the Answer? Regional Insights

Is Automation really the Answer? The Hidden Challenge Inside the Middle East’s Recycling Boom

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AI Data Centers And The Thirst For Water

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