What's the link between Artificial Intelligence and Renewable Energy?
Artificial Intelligence (AI) and the transition to renewable energy sources are emerging sectors already shifting the landscape for investors, employers, and the public on a global scale. While the pace of these changes will be moderated by geopolitical factors, a clear link is emerging between the technologies. AI requires massive amounts of energy to power the data centres that 'think' for their large language models, the levels of which are expected to quadruple by 2030. This energy can be generated with minimal environmental impacts and at a lower cost from renewable sources. Conversely, renewable energy sources often struggle to meet and manage the fluctuating demands of consumers, and AI offers improvements that mark a path to a faster transition.
Australia's market is already well-positioned to rise as a market leader in joining these fields, with policy creating a harbour for investment in technology and renewable energies. In conjunction with an abundant number of ideal locations for renewable energy generation and data centres, Australia is ripe for ventures in this novel cross-sector domain. As interdependence across industries emerges as a major driver of mergers and acquisitions (M&A) activity into 2025, the importance of recognising opportunities to capture market share, drive value and obtain technological advantage is greater than ever.
The Fast-Moving Markets for AI and Renewables in Australia
Movement in the AI industry within Australia is rapid, with both public and private sector actions moving the needle through policy and investment. The Minister for Industry and Science recently unveiled the ‘Australia-first AI Plan’, designed to boost capability by expanding skills and infrastructure, expand investment in technology and grow the economy by stimulating this emerging sector. A report by JLL predicted that 175 new data centres will be required in Australia by 2030, with an estimated investment of $26 billion to meet this need. Capitalising on this fertile foundation, many companies are looking to further invest into AI, with 58% of Australian CEO's indicating that Generative AI is a top investment priority for their businesses regardless of the economic environment.
The energy transition is expected to continue as the main catalyst for global M&A activity in the energy sector through 2025, following investments amounting to USD $117 billion in 2024. This private investment is bolstered by policies and capital deployment from the Australian Government, which includes a target of achieving 82% renewable energy generation by 2030 and an expanded Capacity Investment Scheme (CIS). Concreting these policies, an estimated $9 billion in financial investments commitments was dedicated to Australia's clean economy in 2024. As the private sector continues to drive capital into this space with new large scale renewable energy projects including the Phoenix Pumped Hydro Project recently announced, significant growth is expected into the future.
How can AI help the Renewable Energy transition?
The breadth of potential AI applications to renewable energy systems is immense. In broad strokes, these uses can be categorised as improving efficiency, managing large and complex systems, and accelerating the innovation cycle.
Improving efficiency
Smart grid integrations and energy recycling are two methods that are expected to take the forefront in improving energy efficiency through AI. Data centres are being designed that consume energy efficiently through smart grid solutions that optimise energy demand, while feeding battery-stored excess renewable power back to the grid during peak hours. Additionally, the significant heat generated by AI-driven data centres may be redirected to surrounding infrastructure through heat recovery systems that benefit residential and commercial buildings and reduce the burden on the grid.
AI also promises to improve efficiency in the renewables sector by overcoming the challenge of intermittency. Wind and solar power are both subject to intermittent interruptions due to lack of wind and sunlight, impacting their ability to reliably and efficiently supply the grid. AI is meeting this challenge by implementing predictive maintenance and grid management systems, optimising the charge and discharge cycles of batteries and predicting energy demand patterns. In doing so, AI is transforming the way these fluctuations are handled to ensure a more stable and reliable energy supply.
Managing large and complex systems
Consumer management systems for energy providers are large and complex systems that often require significant resources to maintain and oversee. AI systems can help reduce this burden, allowing providers to limit expenditure while providing an optimal experience. Some companies are already adopting AI to assist in the management of the significant systems required in the energy transition. Kraken is one such organisation that aims to use AI to allow energy providers to manage millions of customer accounts as electricity sources move from coal-fired power stations to battery systems distributed widely around the grid. AI can also assist by providing consumers with real-time information about their energy consumption, empowering them to optimize their own energy usage including through distributed generation (such as solar panels) and storage systems (including home batteries). Consumers reap the benefits of reduced energy bills while contributing to grid stability through these AI enhancements.
The scale of infrastructure needed to support commercial renewable energy systems is often significant. Managing the maintenance of systems this size is an intense endeavour, but AI can assist in reducing the burden and limiting environmental impacts. Using algorithms that analyse data from these renewable energy systems to identify patterns and predict potential issues before they occur, AI facilitates proactive maintenance and optimisation of operations whilst reducing costs. Additionally, this serves to limit the downtime and improve the overall efficiency of the systems, maximising the benefits provided by these large and complex renewable energy systems. AI is also more precise and therefore minimises environmental impacts - for example, a prototype pile driving machine adopted at Engie's Goorambat East solar farm has proven 20% quieter than human-driven piles.
Accelerating the innovation cycle
Beyond the immediate benefits from adopting AI to deliver optimal renewable energy systems, long-term benefits are expected from the expedited technological advances that AI can deliver. The energy transition relies in part on the discovery of new materials including alternative battery chemistries that allow manufacturers to expand their storage capacity and duration. Applying AI to this process can assist in exploring and testing promising new chemistries, leading to lower costs and better results in delivery of critical components.
Leveraging AI capabilities to accelerate the learning curves in new energy areas also promises to further optimise costs and performance. Learning curve impacts of industrial development can be significant with many products quickly becoming inefficient and obsolete. In the clean energy sector, this can be seen through a 25% reduction in battery costs on a dollar-per-kilowatt-hour basis between 2019 and 2024. By using AI methods to analyse operational performance data across various conditions, developers can incorporate that information into the next project design cycle, reducing the demand for additional expensive deployments.
Growth Opportunities
The emerging value pool presented by the interdependence of the AI and renewables sector is a fruitful field for investment. AI's ability to enhance efficiency, manage complex systems, and accelerate innovation is revolutionizing the renewable energy sector. This synergy is particularly evident in Australia, where favourable policies and abundant resources create a fertile ground for investment and growth. As companies look to acquire, ally and partner in novel ways and across industries throughout 2025, many may look to explore or create new opportunities in this space. Australian policies relating to renewable energies and AI make it a particularly appealing jurisdiction to test and grow this evolving domain. The future of energy in Australia is not just renewable; it is intelligent, interconnected, and incredibly promising.
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