According to the Market Statsville Group (MSG), the Global AI for Decarbonization Market size is expected to grow at a CAGR of 47.2% during the forecast period (2024 to 2033).
The AI for the decarbonization market is equally seen as a promising growth exposure that would play an important role in decarbonizing the world economy. Hence, AI solutions rely on computer systems, machine learning, and predictive analytics as well as optimization algorithms to facilitate energy efficiency, minimize emissions, and promote the use of green power. The important areas of application are the effective control of the delivery of electricity, water, and gas, the efficiency of agricultural production, emissions reduction, storage and effective management of greenhouse gases, and intelligent transportation systems.
The drivers influencing the market growth include increasing regulatory requirements, corporate socially responsible actions, and substantial research and development expenditures on energy-efficient solutions. Moreover, AI grows stronger and wiser, and IoT extends its support to smart implementation and scalability of change for decarbonization. In recent years, the demand for the adoption of sustainable processes has come to the forefront of businesses' and governments' implementation strategies, and more specifically, the use of AI for decarbonization is predicted for significant growth in the forecast period due to the increasing importance and need to achieve the net-zero emissions target around the world.
Decarbonization is the process of minimizing or eliminating CO2 emissions from all sources, such as production, transportation, and industry. This would ensure a shift away from fossil fuels to clean renewable energy sources like geothermal, hydro, solar, and wind, which have far less carbon dioxide output. Artificial intelligence stands out to be of great potential significance in the decarbonization of the economy to help reduce greenhouse gasses and transition to an almost low-carbon future. Artificial intelligence is fitted into many different carbon removal challenges. Applications of Artificial Intelligence allow up to 10% fewer greenhouse gases or 2.6 - 5.3 gigatons CO2.
Huge spending by both government and private players in renewable energy and green technologies are among the underlying encouraging factors to the application of AI solutions to address decarbonization goals. For instance, in March 2024, funding worth £1.73 million was given by the UK government to innovative AI projects that aim at lessening carbon emissions across key sectors; secondly, based on the IEA, global clean energy investments increased from an estimated USD 1.0 trillion in 2017, to USD 1.3 trillion in 2021, with compound growth of 5.0% per annum over the same period. There is increased budget allocation by governments towards the financing of clean energy solutions such as solar, wind, bioenergy, and AI technologies. These investments are focused on meeting climate objectives and encouraging sustainable development.
Likewise, private sector organizations, which realize not only the ecological and financial advantages of utilizing green capital, apportion more resources towards sustainable innovation. Companies and venture capital firms investing in start-ups and projects include social causes such as energy efficiency, emissions, and resource optimization using Artificial Intelligence. This inflow of capital not only helps drive innovation in software development around AI but also enables the two to find ways to cut their costs in deploying and implementing AI solutions. Therefore, the synergy provided by public and private financing entails faster rates of adoption and deployment of AI technologies, which are central to aiding global decarbonization measures that propel market growth.
High costs of implementation are one of the major challenges toward the deployment of AI technologies in decarbonization efforts. The high investment required in sophisticated hardware, software, and human capital can act as a significant barrier to the adoption of AI solutions, which is unaffordable for most small companies and developing nations that have limited financial resources. This financial barrier limits the penetration of AI solutions since these entities makes it hard to justify direct expenses regardless of long-term benefits.
Moreover, costs associated with integration of the system into the existing systems and the maintenance of such technologies further add to budgets. Therefore, high implementation costs inhibit access to technologies of AI-driven decarbonization and may slow down global sustainability initiatives while expanding the divide between developed and developing regions.
The study categorizes the AI for Decarbonization market based on deployment model, enterprise size, and end-use industry type area at the regional and global levels.
Based on the end-use industry the market is divided into Energy and Utilities, Transportation, Manufacturing and Industry, Buildings and Construction, and Others. The energy and utilities segment has the largest share in the AI for decarbonization market because during the decarbonization process energy consumption and distribution, energy production, and energy demand are major keys that are efficiently controlled by the energy and utility segment.
The application of AI technologies is widespread in this sphere to increase the productivity of renewable energy sources, including wind and solar, as well as in optimizing grid operation through monitoring and predictive support. Specifically, beneath the pressure in efforts to decrease emissions and steer the energy and utilities industry to cleaner solutions, there is immense regulatory pressure that is already boosting investment in AI-related innovations. The size and effectiveness of these applications in enhancing decarbonization efforts that are widely used across the energy and utilities industry ensure that this market segment stands out as the leader in the adoption of AI solutions.
Based on the regions, the global market of AI for Decarbonization has been segmented across North America, Europe, the Middle East & Africa, South America, and Asia-Pacific. In 2023, Europe had the largest market share around the world. This is due to the stringent environmental laws, challenging emission goals, and increased political commitment to sustainable policies and projects.
Moving to the European Union’s Green Deal, which focuses on achieving a level of net-zero carbon emissions by 2050, provides significant incentives for investing in green technologies, AI solutions included. For instance, the UK government has announced a £1 million investment into twelve green AI initiatives, all pointing toward the decarbonization and enhancement of generation from renewable sources in a big push toward the ambitious goal of reaching net zero by 2050. In addition, The European Commission will invest around €65 million in AI. Of this, € 50 million will go toward projects creating fresh methods for integrating data and enhancing the functionality of big AI models. These will strengthen European research leadership in this field and make AI more applicable to new sectors.
Moreover, the EU has a highly developed technological environment and proper engagement from both public and private entities that contributes to utilizing AI for decarbonization. These factors put Europe in the right place at the right time in the efforts to implement AI and contribute to the reduction of carbon emissions that lead to sustainable development.
Some of the big players that are operating in the global market of AI for decarbonization include Brainbox AI, Carbon Research, Neto, CO2 AI, Equans, and Expect AI. These firms are engaged in creating, and implementing, specific mechanisms based on artificial intelligence to fight carbon emissions and support a sustainable economy in numerous sectors. These companies, which are all committed to the development of technologies and strategic collaborations, are instrumental in the global efforts to implement AI in the process of decarbonization.
Major players in the global AI for Decarbonization market are:
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