AI can help boost our clean energy ambitions
The impact of artificial intelligence (AI) was inescapable at this year's World Economic Forum Annual Meeting. Whether dialogues were focused on the global economic outlook, the future of the labour force, or the energy transition, the spectre of AI was ever present. And it's not hard to see why. With breakthrough technologies and innovations making their way from research labs to factories, supply and value chains, we are on the brink of a new era of social, economic and human possibility. Harnessing and integrating these technological breakthroughs into the global energy system will be crucial to unlocking this immense potential. This consensus from the Swiss mountains in Davos was also echoed at the International Day of Clean Energy. At a dedicated session hosted at the UAE pavilion at the annual meeting on January 22, global leaders who had gathered underscored the need for greater ambition and faster adoption of technologies to meet the UAE Consensus goals of tripling renewable energy capacity and doubling energy efficiency by 2030. With 2024 marking the first time that the 1.5 °C warming threshold has been breached for the year on average, long-term solutions are as desperately needed, as our time to deploy them is short. Right now, the research suggests that, if scaled at the right pace, digital technologies can reduce emissions by 20 per cent by 2050 in the three highest-emitting sectors: energy, materials and mobility. That represents a significant portion of the emissions reductions needed to keep a 1.5 °C future in our sights. There is, however, a dichotomy at the centre of the AI-energy revolution. The more AI technologies and tools that are developed, the higher the demand for the energy that supports them will grow. Thus, energy demand is only set to increase the more we depend on AI tools and networks. A World Economic Forum report from the start of 2024 pointed out that AI's energy use is currently estimated to be around 2-3 per cent of total global emissions. But that is likely to change rapidly as more companies, governments and organisations use AI to drive efficiency and productivity. And, when we realise that AI, and in particular generative AI systems might use up to 33 times more energy to complete a task than task-specific software would, it also comes with a renewed sense to make our energy supplies clean and renewable. For now, the early signs of AI's affect on the energy sector are encouraging. We are already seeing a wave of technological disruption reshaping the energy system – from transforming renewable energy generation and fundamentally altering how energy is consumed across end-use sectors. On the supply side, innovations such as advanced solar photovoltaic systems, offshore wind turbines, and next-generation grid-scale battery storage are enabling cleaner, more efficient energy production while improving grid reliability. When transmitted to end-use sectors like transport, buildings, and industry, technologies such as green hydrogen, smart grids, and electrification are driving significant reductions in carbon emissions. What's more, digital tools such as AI and blockchain are optimising energy efficiency and facilitating the integration of decentralised renewable energy systems. This tech-driven energy revolution is simultaneously transforming how we produce and consume energy, and creating a new development pathway that prioritises clean, affordable and accessible energy. The integration of AI with renewables is also helping enhance community resilience in vulnerable regions. For example, machine learning algorithms are being used to optimise microgrids, ensuring uninterrupted power supplies during extreme weather events. AI-powered predictive maintenance tools are reducing downtime in solar and wind facilities, while advanced forecasting models improve energy storage and grid balancing to accommodate variability in renewable energy sources. Such digital solutions are critical in scaling renewable energy systems globally and ensuring they are resilient to disruptions. The UAE, as a global leader in renewable energy, is already demonstrating how AI can be harnessed to achieve energy resilience and security. For instance, the Mohammed bin Rashid Al Maktoum Solar Park uses AI to optimise solar panel cleaning schedules and enhance energy output. The UAE has also integrated AI into its energy planning systems, enabling real-time monitoring of grid performance and predictive analytics to mitigate potential outages. Through initiatives such as Masdar City and partnerships with global technology leaders, the UAE is using AI to drive efficiencies, reduce emissions, and future-proof its energy systems. The convergence of AI and the energy transition presents an unprecedented opportunity to tackle the twin challenges of decarbonisation and growing energy demand. However, realising this potential requires co-ordinated global action. Policymakers must prioritise investments in clean energy technologies, while industry stakeholders adopt AI solutions responsibly to ensure they align with sustainability goals. The UAE is showing what is possible when innovation meets ambition, but it cannot do this alone. If we want to keep 1.5°C within reach and create a future powered by clean, reliable energy, the time to act is now. AI, when integrated thoughtfully and equitably into energy systems, can help us achieve a transformative and sustainable future. But only if we commit to scaling the technologies and policies that make it possible.
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