18 February 2026 11:09 pm
If the AI bubble bursts, will MENA startups survive?

If the AI bubble bursts, will MENA startups survive?

Feb 5, 2026

A man sits amidst collapsed buildings and debris following an earthquake in Marrakesh, Morocco by YOUSSEF elbelghiti via pexels

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If the AI bubble bursts, will MENA startups survive?

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By May El Habachi

For some founders in the region, the fear of a potential overhype and overvaluation is concerning.

If the AI bubble bursts, will MENA startups survive?

[Source photo: Pankaj Kirdatt/Fast Company Middle East]

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Is there an AI bubble?  From the head of Google’s parent company to officials from the Bank of England, many fear that the AI’s growth is being driven by massive investment and hype, similar to the dot-com boom.  As it stands today, the unit economics of the AI industry don’t add up. The revenue or value an AI company or a large language model like ChatGPT earns from servicing a single user or query is less than the amount it earns from that interaction. OpenAI, for example, is not profitable, even though it generates billions of dollars in annual revenue. Spending on operating costs, compute, research, and development far outpace revenue.Yet, investors are still pouring billions into this technology. About $202 billion was invested globally in AI in 2025, according to Crunchbase. This includes AI infrastructure, foundation labs, and applications. AI was also the leading sector for startup funding globally from 2023 to 2025.In the MENA region, AI startups raised over $2 billion in the first half of 2025, a 134 percent year-on-year increase, according to HUB71.

IMPACT ON FUTURE INVESTMENT

For some founders in the region, the fear of a potential overhype and overvaluation is concerning. “Even if you’re looking to build applications that are commercially viable, if there is big noise around you, this will impact everyone’s decision-making,” says Ahmed Mahmoud, CEO of DXwand, a startup that leverages AI to automate customer service and employee assistance. “It could impact any future investment.”

It’s not only startups that have invested heavily in AI, but also enterprises and corporations. Many have allocated significant resources to Graphics Processing Units (GPUs), servers, and subscription services, but some, if not all, are still waiting to see returns on their investment. “This will make all decision makers think if they’ve done the right thing,” says Mahmoud.

To ensure AI delivers real value, he offers SMEs AI-powered sales agents that help acquire and convert customers at a fraction of the cost of hiring human sales staff.

OPPORTUNITIES FOR STARTUPS

Mohamed Hussain, Principal at Anara Capital, while he recognizes the hype, overvaluation, and risks associated with the underlying technology, sees real demand for it. One that founders can leverage if they know how to use it right.

“There’s definitely huge capital inflows into AI companies, inflated valuations, and a lot of AI washing,” he says. “A lot of AI is being used for marketing purposes rather than for actual operating purposes. So yes, I do think there’s definitely some hype. And I do think there has to be a market correction at some point, which will result in many AI startups disappearing over the next few years, but I also think there is huge, tangible demand for AI.”

He adds: “At the foundational level, like data centers and compute platforms, we’re seeing millions and millions of users. There’s real demand, serious money, and serious traction.”

The key, according to Hussain, is for startups to use AI to solve real problems rather than as a tool to attract funding, especially to streamline operations and increase efficiency. He gives an example of a fintech startup assessing credit scores. By using AI, the startup can reduce processing time, increase efficiency, and perhaps even cut costs by becoming leaner.

“AI is now becoming an expectation, at least in the tech startups world,” he says. “So, we always have to look one step further. How are they using AI? Is their AI different, or are they simply integrating it with ChatGPT at the back end? So, we really assess what AI means to them. And we also assess what impact AI is having on the operations of companies.”

In addition to increased efficiency, AI can also improve a startup’s economic margins, making its unit economics more sustainable and putting it on the road to profitability sooner rather than later. All this gives founders the opportunity to improve their products and services, and reach new markets quickly.

“There are definitely expectations on startups,” says Hussain. “They’ll need to make sure that their business and solution are defensible and scale that much quicker and take advantage of the capital inflows for now because that’s not going to be forever. But at the same time, there’s also a lot of opportunities for them across the board.”

RISK OF UNDERINVESTING

To keep innovating and creating value, however, founders need money.

Akshat Prakash, CTO at CAMB.AI, a startup that live streams in multiple languages, says there is a risk in underinvesting rather than overinvesting in AI. “It’s not debatable that AI is going to be consequential,” he adds. “We’re not debating here whether AI is going to be the fundamental backbone of any vertical. People already believe that. The question is, is it going to be in 10, 15, or 20 years?”

He says that the mindset of investing in AI needs to change. Unlike other technologies, AI must be deployed and invested in before it generates returns. “We do live streaming for the world’s biggest leagues in multiple languages,” he says. “This technology will never be complete. It can only get better and better. So, it must be bought first and then scaled. So, enterprises and companies are just not used to buying something that doesn’t work yet.”

Prakash likens it to companies like Google and Facebook when they first started. In their early days, they weren’t profitable. They focused on creating value first, in getting people to use their platforms before becoming some of the world’s biggest companies. “These companies made a profit later,” he explains. “New technologies like AI must be deployed before they can be fully monetized; those profit cycles are even longer.”

If startups can’t see that, they are missing the bigger picture, he adds.

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Global population living with extreme heat expected to double by 2050

Global population living with extreme heat expected to double by 2050

Feb 2, 2026

A vast aerial view of a densely populated urban residential area with diverse building types. By Ludvig Hedenborg via pexels

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Global population living with extreme heat expected to double by 2050

by University of Oxford

edited by Gaby Clark, reviewed by Robert Egan

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Global population living with extreme heat to double by 2050

Global mean HDDs for three global warming scenarios. Credit: Nature Sustainability (2026). DOI:10.1038/s41893-025-01754-y

A new University of Oxford study finds that almost half of the global population (3.79 billion) will be living with extreme heat by 2050 if the world reaches 2.0°C of global warming above pre-industrial levels—a scenario that climate scientists see as increasingly likely.

Most of the impacts will be felt early on as the world passes the 1.5°C target set by the Paris Agreement, the authors warn. In 2010, 23% of the world’s population lived with extreme heat, and this is set to grow to 41% over the next decades.

Regions and populations most at risk

Published in Nature Sustainability, the findings have grave implications for humanity. The Central African Republic, Nigeria, South Sudan, Laos, and Brazil are predicted to see the most significant increases in dangerously hot temperatures, while the largest affected populations will be in India, Nigeria, Indonesia, Bangladesh, Pakistan, and the Philippines.

Countries with colder climates will see a much larger relative change in uncomfortably hot days, more than doubling in some cases.

Compared with the 2006–2016 period, when the global mean temperature increase reached 1°C over pre-industrial levels, the study finds that warming to 2°C would lead to a doubling in Austria and Canada, 150% in the UK, Sweden, Finland, 200% in Norway, and a 230% increase in Ireland.

Infrastructure and adaptation challenges

Given that the built environment and infrastructure in these countries are predominantly designed for cold conditions, even a moderate increase in temperature is likely to have disproportionately severe impacts compared with regions that have greater resources, adaptive capacity, and embodied capital to manage heat.

Lead author, Dr. Jesus Lizana, Associate Professor in Engineering Science, said, “Our study shows most of the changes in cooling and heating demand occur before reaching the 1.5ºC threshold, which will require significant adaptation measures to be implemented early on. For example, many homes may need air conditioning to be installed in the next five years, but temperatures will continue to rise long after that if we hit 2.0 of global warming.

“To achieve the global goal of net-zero carbon emissions by 2050, we must decarbonize the building sector while developing more effective and resilient adaptation strategies.”

Dr. Radhika Khosla, Associate Professor at the Smith School of Enterprise and the Environment and leader of the Oxford Martin Future of Cooling Programme, added, “Our findings should be a wake-up call. Overshooting 1.5°C of warming will have an unprecedented impact on everything from education and health to migration and farming. Net zero sustainable development remains the only established path to reversing this trend for ever hotter days. It is imperative politicians regain the initiative towards it.”

Energy demand and new climate data

The projected increase in extreme heat will also lead to a significant rise in energy demand for cooling systems and corresponding emissions, while demand for heating in countries like Canada and Switzerland will decrease.

The study also includes an open-source dataset of global heating and cooling demand, comprising 30 global maps at ≈60km resolution that capture climate intensity in “cooling degree days” and “heating degree days” worldwide. This dataset provides a strong foundation for incorporating accessible climate data into sustainability planning and development policy.

Publication details

Lizana, J. et al, Global gridded dataset of heating and cooling degree days under climate change scenarios. Nature Sustainability (2026). DOI: 10.1038/s41893-025-01754-y www.nature.com/articles/s41893-025-01754-y

Journal information: Nature Sustainability

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Hospitality skills can help all businesses adapt to the AI revolution

Hospitality skills can help all businesses adapt to the AI revolution

Jan 30, 2026

Futuristic delivery robot navigating an empty outdoor plaza, symbolizing modern innovation and mobility. By Kindel Media via pexels

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Why hospitality skills can help all businesses adapt to the AI revolution

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Drazen Zigic/Shutterstock

Alisha Ali, Sheffield Hallam University; Lisa Wyld, Buckinghamshire New University, and Maria Gebbels, University of Greenwich

The future of work is being rewritten by artificial intelligence (AI) – but technology competence alone will not be enough to empower the workforce of the future. While AI has massive potential to improve efficiency, accuracy and productivity in the workplace, it’s less clear how it will evolve to foster the person-centred concerns that all businesses face.

The human-centred skills found in the hospitality sector (empathy, creativity, adaptability, kindness, resilience and cultural intelligence) have been shown to be strategic assets in AI deployment in the workplace – things like chatbots or virtual assistants. They also remain the hardest skills to replicate in and by AI.

These qualities are not just soft skills – they should be at the heart of all customer service businesses. They enable employees to turn routine interactions into memorable experiences through emotional connection and the anticipation of customers’ needs. For now at least, AI is ill-equipped to manage this.

These hospitality skills matter for all businesses – not just those in the sector. In a world of evolving AI, they can help organisations ensure that the human touch is not lost. And investing in these skills can also drive profitability.

The UK hospitality sector leads the Social Productivity Index, a metric that measures the broader social value of industries beyond just how much revenue they make. Hospitality is the third-largest employer in the UK and the top employer of under-25s, part-time workers and minority groups. It also contributes £93 billion to the UK economy annually, accounting for 3% of GDP.

As such, investing in hospitality skills is critical to driving economic growth and building more resilient, people-centred workplaces. These skills are essential for things like creating a welcoming environment or navigating complex and changing business demands. There is a need for all businesses to prioritise these skills alongside their use of AI.

ai chatbot conversation on a phone screen
Efficient… but impersonal.
Tero Vesalainen/Shutterstock

By 2030, industries such as banking, healthcare and retail are expected to rely heavily on agentic AI (those systems that can solve complex problems in real time) to interact with customers. These industries lean heavily on efficiency, compliance and product knowledge – which are important – but they leave little room for genuine emotional engagement.

Many businesses are using chatbots and virtual concierges to resolve customers’ problems. Hospitality skills can help to determine which customer concerns can be dealt with by AI and which need to have the human touch. Similarly, AI can manage staff and rotas, but it cannot judge uncertainty or consider the impact of decisions on staff.

Hospitality comes into its own in terms of personalisation and cultural sensitivity. These skills are not just add-ons; rather they are the glue that holds great customer experiences together. Multilingual greetings, tailoring menus to cultural norms, spotting unspoken needs and other small touches all build loyalty.

Good hospitality professionals do not just serve, they anticipate, adapt and make people feel seen. Emotional intelligence and emotional labour are embedded into hospitality roles, with staff trained to manage emotions and respond with empathy.

The ‘what’ and the ‘why’ of business

In an era where technology handles the “what”, hospitality skills can deliver the “why” – that is, the meaning behind the interaction. And when transferred to sectors that also rely heavily on these strengths, such as healthcare, hospitality skills can provide great opportunities for career change or progression.

We suggest three ways organisations can embrace hospitality skills alongside AI to future-proof their talent pool.

First, staff training should be designed to combine both AI knowledge and the deep connectivity of hospitality skills. This training should encompass how businesses expect staff to engage with AI, as well as how hospitality skills can be fused to support and enhance their customers’ experience.

While AI can process data and do transactions, it cannot truly care, comfort or create trust. These are crucial measures in ensuring that the human element does not fade into the background.

Second, by investing in hospitality skills, businesses can concentrate more effectively on the customer journey and improve the efficiency of their service. For example, while AI can provide prompts on what to say, it cannot offer genuine comfort to a dissatisfied customer. Hospitality skills are essential to deliver those messages effectively and with care.

These skills help businesses to understand customer management, flow and touchpoints (points of interaction). This in turn strengthens the connection between AI and the customer experience as they interact to deliver a warm welcome.

Third, in developing AI for business use, hospitality skills will become core to the training process in order to improve the customer experience. This kind of hospitality training can transform business services from being standardised and short-termist to those that focus on building a lasting relationship with the customer.

For example, using banking apps, customers receive automatic suggestions on loans, mortgage updates or new accounts. But it is the staff’s hospitality skills that ensure these recommendations are presented with warmth and a genuine understanding of customers’ needs. This delivers experiences using AI but also conveys personalised customer service.

Businesses that engage with hospitality skills will not only navigate the AI revolution, but lead it. By combining AI-driven efficiency with the kind of skills that encourage genuine human connection, they can deliver streamlined services while making customers feel valued. In other words, technology can enhance, not replace, the human touch.The Conversation

Alisha Ali, Associate Professor, Department of Service Sector Management, Sheffield Hallam University; Lisa Wyld, Professor of Hospitality Innovation and Leadership, Buckinghamshire New University, and Maria Gebbels, Associate professor in hospitality, University of Greenwich

This article is republished from The Conversation under a Creative Commons license. Read the original article.

 

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The Conversation

Global framework to safeguard world’s most vulnerable regions

Global framework to safeguard world’s most vulnerable regions

Jan 28, 2026

A man carries water across a parched landscape in Sagaing, revealing drought impact. By Pyae Phyo Aung via pexels

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New study proposes global framework to safeguard world’s most vulnerable regions amid climate crisis

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Peer-Reviewed Publication

Ecosystem Health and Sustainability

EurokAlert!

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Major socio-environmental processes in ecologically sensitive regions
image: Major socio-environmental processes in ecologically sensitive regions.  Ecologically sensitive regionsare those which are highly vulnerable to the impacts of climate change and humanactivities, most significantly industrialization and urbanization, while theirecosystem services are low or reducedview more 

Credit: Yonglong Lu, Xiamen University

The paper “Prioritizing Sustainable Development of Ecologically Sensitive Regions” was published recently in Ecosystem Health and Sustainability – A Science Partner Journal. The innovative research calls for merging AI with indigenous knowledge and targeting “tipping point” ecosystems to achieve the Sustainable Development Goals.

A groundbreaking new study urges a global priority shift toward sustainable development in four types of ecologically sensitive regions, warning they are at imminent risk of catastrophic “tipping points” due to climate change and human pressure. The research, lauded by expert reviewers as “timely,” “innovative,” and “forward-looking,” proposes a novel integration of artificial intelligence (AI) with Indigenous knowledge and a unified scientific framework to prevent systemic collapse and guide equitable resilience.

Global Significance: Averting Cascading Crises

The study identifies four critical region types – plateau/alpine systems, resource-depleted regions, super-fast-growing cities, and island/coastal states – as disproportionately vulnerable. Despite their diverse geographies, they share a common trait: high sensitivity to shocks that can trigger irreversible damage with global consequences.

“These are not just local problems,” the study emphasizes. “The Tibetan Plateau’s melting glaciers threaten water security for billions across Asia. The collapse of a resource-depleted city can destabilize entire regions. Coastal overtopping can create climate refugees. Protecting these regions is a linchpin for global stability and achieving the UN Sustainable Development Goals (SDGs), particularly those related to water (SDG 6), cities (SDG 11), climate action (SDG 13), life under water (SDG 14), and life on land (SDG 15).”

Theoretical and Methodological Innovation: A Unified Lens and a Novel Fusion

The study’s core innovation is its unified social-ecological systems (SES) analytical framework, which allows policymakers to analyze disparate regions – from the Arctic permafrost to megacities like Shenzhen – through the same lens of exposure, sensitivity, and adaptive capacity. This approach reveals how ecological fragility and social vulnerability intertwine to create systemic risk.

Its most pioneering proposal is the integration of AI-enhanced monitoring (using satellite data and IoT sensors) with Indigenous and local knowledge. While AI can detect large-scale environmental changes, local communities hold deep, place-based understanding of ecological rhythms and resilience strategies. The study argues that fusing these knowledge systems is essential for accurate early warning and culturally appropriate solutions.

“AI can spot a forest canopy change from orbit, but local knowledge can explain why it’s happening and what it means for the community,” the paper notes. “This synergy is the future of sustainability science.”

Implications for Global SDG Implementation: A Blueprint for Ethical Action

To translate science into action, the study makes concrete recommendations with profound implications for global SDG implementation:

1. Establish a Global Sensitivity Observatory Network: A proposed international network would standardize monitoring of these critical zones using the integrated AI/local knowledge model, providing real-time data for global assessments and local action.

2. Governance for Equity and Justice: The research strongly warns against a purely technological fix. It calls for adaptive governance that empowers local communities, resolves policy conflicts, and ensures long-term political and financial commitment. Success hinges on placing equity and environmental justice at the center of all interventions.

3. An Ethical Framework for Technology: The study directly addresses ethical pitfalls, advocating for clear policies on data sovereignty, the use of understandable “explainable AI,” and participatory design. It insists that communities must own their data and have the right to contest AI-driven decisions affecting their lives and lands.

4. Targeted, Resilient Development: By providing a clear typology of sensitive regions, the framework allows the international community to prioritize funding, technology transfer, and policy support to where it is most urgently needed, making SDG implementation more strategic and effective.

The anonymous reviewers unanimously praised the study’s ambition and relevance. They highlighted its “valuable synthesis” of interdisciplinary science and its “commendable” call for knowledge integration. It provides not just a warning, but an actionable roadmap. It argues that safeguarding the world’s most fragile socio-ecological systems is the ultimate test of our commitment to a sustainable and just global future.

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What Is Circular Economy Building a Sustainable Future

What Is Circular Economy Building a Sustainable Future

Jan 26, 2026

 

Classic typewriter displaying ‘Circular Economy’ in outdoor setting, conveying sustainability.  By by Markus Winkler via pexels

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What Is Circular Economy (CE) － Building a Sustainable Future

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By Mayuko Taniguchi Portraits of Mayuko Taniguchi, Consulting Business Development Department.

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What Is Circular Economy

Circular Economy is an economic activity that reduces resource input and consumption, makes effective use of existing resources and products, and creates new value through services, in addition to 3Rs of “Reduce”, “Reuse”, and “Recycle”. Circular Economy aims to create a sustainable society.

Why we need to shift to Circular Economy

Society today is aiming to achieve sustainable economic activity by maximizing the value of resources and products, minimizing resource consumption, preventing waste generation, and regenerating nature and natural resources.
In a society of mass production, mass consumption and mass waste, resource depletion, environmental pollution, and climate change due to greenhouse gas (GHG) emissions are already global issues.
In a linear economy that manufacturing and recycling industries are separated, the cost of recycling exceeds the value of recycled materials, resulting in situations that products or materials have been discarded even if they have resource potential.
It is important to transition to a Circular Economy that uses resources sustainably.

Linear Economy and 3Rs

Circular Economy is proposed as a new socioeconomic system to replace the Linear Economy of mass production, mass consumption, and mass waste.
Linear economy is a unidirectional socioeconomic system of “Resource extraction or Mining→ Product Manufacturing → Consumption → Disposal”. As the population grows and living standards improve, production, consumption, and waste have steadily increased, resulting in issues such as waste generation exceeding processing capacity. To address these issues, 3Rs (Reduce, Reuse, and Recycle) have been promoted.
While 3Rs have proven effective in addressing waste-related issues, other issues recently have also emerged, such as resource depletion and environmental pollution associated with mass production and mass consumption, as well as climate change due to greenhouse gas (GHG) emissions.
In addition to environmental issues or resource depletion, various forms of resource procurement risks are increasing, such as the trend toward economic blocks (restrictions on the import and export of resources across regions and countries) that is progressing in regions and countries around the world. In response to these issues, it is important to address not only the traditional 3Rs that focus on “mass waste,” but also “mass production and mass consumption.”

Change Business Model by Circular Economy

The way manufacturers operate, which has traditionally focused on the production and sale of products, is beginning to change.
In addition to 3Rs, the concept of refurbishing and remanufacturing has recently gained attention, in which manufacturers collect and refurbish used or defective products and reship them in near-new conditions. It is believed that if manufacturers can maximize service opportunities as added value by maintaining customer contact throughout the product lifecycle to ensure the functionality and durability of products (or parts), and understanding customer needs, this could lead to highly profitable businesses.
Furthermore, given this background, there are examples of businesses achieving Circular Economy by shifting from a one-time product sale model to a service provision model such as subscription or sharing (home appliance rental or car sharing).

Circular Economy is Industrial Perspective rather than Environmental Policy

The European Union (EU) announced “The Circular Economy Action Plan” as its policy guideline in 2015 and subsequently positioned Circular Economy as a key policy in “The European Green Deal” formulated by the European Commission (EC) in 2017. This was followed by “The Circular Economy Action Plan” in 2020, and more recently “The Ecodesign for Sustainable Products Regulation” which incorporates regulations covering the entire lifecycle of products, including design, durability, repairability, and recycled content.
Furthermore, for specific products, “The Packaging and Packaging Waste Regulation” which stipulates the recycling, minimization, and reuse of packaging, and “End-of-Life Vehicles (ELV) Regulation” which regulates the entire lifecycle of automobiles, have been published.
While these policies aim to reduce environmental impact, they also position themselves as industrial policies that enhance the EU’s industrial competitiveness by making compliance with regulations regarding raw material sourcing and product design mandatory requirements for market entry, changing manufacturing practices and market rules. China also published its “The 14th Five-Year Circular Economy Development Plan” in 2021, and similar trends can be seen in countries and regions outside the EU.
In Japan, the Ministry of the Environment published “The 4th Fundamental Plan for Establishing a Sound Material-Cycle Society” in 2018, which mentioned economic aspects in addition to the traditional environmental aspects. In recent years, the Ministry of the Environment also published “The 5th Fundamental Plan for Establishing a Sound Material-Cycle Society” in 2024, and the Ministry of Economy, Trade and Industry also formulated “Growth-Oriented Resource Autonomous Economic Strategy” in 2023, both of which are notable for incorporating many elements of industrial strategy.

The Key to achieving Circular Economy is Information Collaboration

Achieving Circular Economy requires policy regulation and guidance. Realizing business requires not only technological development by specific companies but also collaboration among a wide range of stakeholders.
Collaboration across the entire value chain is required, involving both “Manufacturing Industry”, which develops and manufactures materials and products, and “Recycling Industry”, which handles processes such as sorting and recycling of collected materials and waste.
Minimizing information gaps between the Manufacturing and Recycling Industries is crucial for efficient collaboration across the entire value chain, and the distribution of various information related to manufacturing and recycling is essential.
Specifically, competitive concerns should be taken into consideration, if manufacturers share information on the composition, properties, history of use, and chemical constituents of the materials in their products with recycling industries, it will help recyclers improve the efficiency of recycling and preserve material and product value.
Recycling Industries can increase trust in recycled materials and promote their use by collaborating information on the traceability of the recycling process and the composition and characteristics of recycled materials with Manufacturing Industries.
It is need that common rule as common language that allows stakeholders participating in the information distribution platform to operate.

* Organization names and job titles may differ from the current version.

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