AI has gone mainstream. There are impressive advancements that indicate the rapid progress being made in AI, but what does the growing popularity of large-scale AI models mean for sustainability?

From fashion brands to manufacturing companies, they have started reporting on their environmental impact as it’s become clear that we must do everything possible to curb carbon emissions. Organizations have been working hard to incorporate advanced technologies into building applications, optimizing and reducing operational costs, or providing data. 

A study found that more than 50% of the countries in the MENA region are already renewable energy efficient, and with the handy help of AI, this can be further improved.  

By 2030, the deployment of AI in managing renewable energy sources is expected to enhance efficiency by 10% to 25%, translating to a significant uptick in clean energy production without additional resource expenditure.

In the region, investment in AI for environmental sustainability is on an upward trajectory, with projections indicating a surge in funding by over 50% in the next five years.

Moreover, national sustainability agendas across the region increasingly incorporate AI-driven solutions, aiming for a 30% reduction in carbon footprints across major industries by 2025. 

“AI enhances the efficiency of renewable energy systems by optimizing power grid operations and forecasting energy demand and supply. Organizations can leverage AI to analyze large amounts of data from solar panels and wind turbines, identifying patterns to increase energy production and reduce waste,” says Alfred Manasseh, COO and co-founder of Shaffra. 

“Also, AI-driven predictive maintenance can prolong the lifespan of renewable energy infrastructure, making sustainability efforts more cost-effective.” 

AI can track and identify issues. “It can provide potential solutions and optimization strategies to meet current and future demands while minimizing emissions and operational costs,” says Khalid Al Huraimel, CEO of Beeah Group.

Vikash Gupta, CEO of Greenr Technologies Ltd., an AI-based carbon management company, says that upon working with companies in the MENA region, he noticed that organizations aim to become more sustainable. 

“There’s an element of recognition that the oil-driven economy can only go so far. With a lot of energy production coming from MENA, we are using AI to help companies consume less energy and transition to renewables by providing them with real-time data,” he adds.

This can have economic benefits and, most importantly, an environmental impact—a win-win situation. 

GOING GREEN WITH AI

The energy and sustainability sector seeks to adopt AI and advanced technologies to scale, grow, and drive towards local and global sustainability targets.

Companies like Greenr Technologies are helping businesses take a more sustainable path using AI. The company looks at what kind of energy companies are using and how they use it and deploys AI to give them recommendations. 

“We give them real-time feedback and ongoing reporting rather than one-off reporting,” Gupta says. 

Furthermore, AI can process and analyze environmental data at an unprecedented scale, helping understand climate patterns, predict extreme weather events, and develop more sustainable practices. 

“Adopting technology, especially AI, is crucial in combating climate change. It’s not just about innovation, but survival,” says Manasseh.

Meanwhile, Al Huraimel says that predictive AI and digital twin technology, in particular, allow for the automation of systems, gathering of data, making informed decisions, and achieving sustainability targets, including transitioning to cleaner energy and reducing emissions. 

For example, these technologies have helped Beeah integrate different energy systems, optimize them, and scale them according to demand.

At the same time, collected data provides the company with insights into business operations and environmental performance. The digital twin provides performance insights, acting as a virtual replica that gathers data from the physical structure. 

Waste reduction is another area where AI shines, with some firms reporting a decrease in material waste by up to 50%, contributing significantly to sustainability goals. 

Beeah’s AI City Vision project is a prime example, whereby vehicles are fitted with 360 cameras integrated with AI that can detect issues such as overflowing bins or streets with obstacles or litter. 

“Using AI, we are driving towards sustainability targets by reducing environmental waste and minimizing emissions while also providing exceptional service to communities,” says Al Huraimel.

OVERCOMING OBSTACLES

Adopting AI for sustainability comes with challenges, albeit the pros outweigh the cons.

Integrating AI requires significant investment in technology and training, while another challenge involves ensuring data accuracy and privacy. 

“Setting up AI systems necessitates upfront costs that can be high for many organizations, potentially requiring millions in investment for state-of-the-art technologies and skilled personnel to manage them,” says Manasseh. “At the same time, ensuring the accuracy and privacy of data adds another layer of complexity.”

Despite this, companies achieve efficiency improvements, substantial cost savings, and significant reductions in their carbon footprint through AI. In fact, organizations leveraging AI for energy efficiency have seen energy costs decrease by as much as 20% to 30%, owing to smarter consumption patterns and predictive maintenance that reduces equipment failures and extends asset life. 

Reem Asaad, Vice President for Cisco Middle East, Türkiye, Africa, Romania, and the Commonwealth of Independent States (CIS,) notes that, inadvertently, unless they are smaller, domain-specific AI models, it is also important to keep in mind that the widespread adoption of AI often leads to increased energy consumption and significant greenhouse gas emissions.

An analysis shows that by 2027, AI servers globally could be using as much energy as some small countries do in a year.

“There is a pressing need for higher-performing and cost-effective inference AI solutions to mitigate the carbon footprint of AI technologies. Developing and deploying energy-efficient AI systems is crucial to sustainably meet the growing demand for AI-driven applications, such as fraud detection, translation services, and chatbots,” she says.

Due to this predicament, organizations face the challenge of building energy-efficient AI systems, with a particular focus on optimizing infrastructure, models, and software tools to reduce computational workload during inference.

At Beeah, Al Huraimel cites challenges from both technical and cultural perspectives. “From a technical standpoint, it can be hard to unify teams and processes to automate them. Or in the case of AI, it is a challenge to gather enough data to train AI models to deliver actionable insights,” he mentions. 

The obstacles are overcome through external partnerships and internal organizational alignment, exposure, and training.

For example, the Sharjah Waste to Energy plant, a collaboration between Beeah and Masdar, has helped implement an innovation that is scalable and connected to the grid, producing 30 megawatts of power and offsetting 450,000 tonnes of carbon dioxide emissions annually. At the same time, the plant is driving a 90% landfill waste diversion rate in Sharjah, which is the highest in the region. 

“Implementing technologies to gather this data and drive us towards targets like net-zero and achieving zero-waste to landfill have been crucial for tangible and positive climate action,” says Al Humairel.

A GREEN-TECH FUTURE

As these trends gain momentum, the fusion of AI and sustainability initiatives is set to redefine regional and global landscapes, creating an era of smarter, cleaner, and more efficient energy.

“MENA companies and governments can be much more successful and create a more sustainable economy for their people,” says Gupta.

AI’s applications in energy transition are diverse and promising. “Using advances in energy networking and improved energy efficiency, we can significantly reduce the world’s energy needs by 2050 – and along the way, we will be better able to control global emissions of greenhouse gasses,” says Asaad.

With this in mind, the outlook for this progression of AI and energy solutions is expected to have a quantifiable impact on business and environmental performance. “AI will eventually grow to become a basic tool to solve problems and present solutions, optimize energy consumption, and achieve net-zero targets,” says Al Huraimel. 

“The region has the potential to lead in green technology, harnessing AI not just for economic growth but also for a sustainable future,” adds Manasseh.