International Collaboration: Mainstreaming Artificial Intelligence and Cyberphysical Systems for Carbon Neutrality

Cyberphysical systems together with Artificial Intelligence play vital roles in reducing, eliminating, and removing greenhouse gas emissions across sectors. Electrification with renewables introduces complexity in systems in the deployment, integration, and efficient orchestration of electrified economic systems. AI-driven cyberphysical systems are uniquely suited to tackle this complexity, potentially accelerating the transition towards a low-carbon economy. The objective of this policy brief is to advocate for the mainstreaming of AI-driven cyberphysical systems for climate change risk mitigation and adaptation. To effectively and more rapidly realize the Intelligent Decarbonation potential, the concept of AI-driven cyberphysical systems must be elevated to a global level of collaboration and coordination, fostering research and development, capacity building, as well as knowledge and technology transfer. Drawing on a multidisciplinary, international study about intelligent decarbonization use cases, this brief also highlights factors impeding the transition to carbon neutrality and risks associated with technology determinism. The importance of governance is emphasized to avoid unwanted path dependency and avert a technology-solutionist approach dominating climate policy that delivers limited results. Given only 12% of the Sustainable Development Goals have been realized, a condensed version of this policy brief was submitted to the India T20, a G20 engagement group, urging global collaboration to prioritize AI-driven CPSs.


I. INTRODUCTION
T HE primary motivation for this policy brief is the urgent need to address the global challenge of achieving carbon neutrality.This urgency is underscored by the fact that only 12% of the Sustainable Development Goals (SDGs), including crucial climate action objectives, have been realized at the halfway point of the U.N. 2030 Agenda for Sustainable Development.The rapid advancement of Artificial Intelligence (AI) and Cyberphysical Systems (CPS) has opened innovative avenues for addressing this challenge.This brief aims to explore the potential of AI and CPS in driving effective decarbonization strategies across key sectors.It specifically seeks to understand how these technologies can reduce greenhouse gas (GHG) emissions, optimize energy use, and promote sustainable practices in vital areas like electricity and heat generation, transportation, buildings and cities, industry, and agriculture.
This paper has two objectives: First, it provides fresh insights into the integration of AI and CPS across various sectors, delving into their roles and impacts on decarbonization efforts.This involves highlighting diverse use cases and assessing both the potential benefits and challenges associated with AI and CPS.Secondly, the brief serves as an urgent call to action, advocating for enhanced global collaboration and governance.It underscores the urgency of harnessing AI-driven CPS for climate crisis mitigation and emphasizes the critical role of global coordination, particularly under the leadership of the Group of Twenty (G20).The G20, responsible for over 80% of global carbon emissions, is positioned as a pivotal platform for driving the development and adoption of these technologies, while simultaneously addressing and managing their risks.This paper begins by highlighting the potential and challenges of AI and CPS in advancing carbon neutrality, stressing their role in the context of the U.N. SDGs.Section III, "Cyberphysical Systems at the Center of Intelligent Decarbonization," delves into how these systems are integral to decarbonization, with a focus on their applications across various sectors.To achieve widespread adaptation of AI CPS, electrification of all economic systems with renewable energy is crucial.Section IV, "Artificial Intelligence-enhanced Cyberphysical Systems", concretely outlines the use of AI in CPS for decarbonization strategies and emphasizes their role in energy management and optimizing economic systems.It also includes case studies highlighting practical applications of AI-enhanced CPS across various sectors demonstrating their impact on climate change adaptation and decision-making.It will become evident that only AI can manage complex cyber-physical systems.The reader will then understand the dual challenge of climate change and the rapid advancement of AI in Section V, "Climate Change and Artificial Intelligence: A Twin Critical Junctures."The section discusses the role of technology in climate mitigation, the risks of overreliance on technological solutions, and the need for careful regulation and balance in AI development to harness its benefits for societal and environmental good, while also considering its carbon footprint in the global digital transformation.Section VI, "Cybersecurity," highlights the importance of cybersecurity in the context of AI-driven CPS.The necessity of international cooperation in addressing climate change and AI governance is emphasized in Section VII, "Global Collaboration."Finally, Section VII, "Recommendations to the Group of Twenty," outlines actionable steps for global leaders, particularly focusing on the G20's role in promoting AI and CPS for environmental sustainability.The paper concludes with a discussion on the urgency of global collaboration to prevent a climate crisis and manage the responsible proliferation of AI technologies.

II. THE OPPORTUNITY OF INTELLIGENT DECARBONATION
Artificial Intelligence has the potential to help achieve the United Nations (UN) Sustainable Development Goals (SDGs) [1].Within the United Nations, the International Telecommunication Union (ITU) listed, in its 2022 report [2], 281 projects carried out by 40 different U.N. entities that have initiated or already implemented AI projects addressing some of humanity's most urgent issues.This includes projects focused on climate action (SDG 13), which is of concern in this policy brief.Beyond the U.N. context, a number of promising studies have been conducted, emphasizing a broad array of strategies and application areas across key sectors that utilize AI or Machine Learning (ML) to attain carbon-neutral transformation goals [3, 4, also cf. 5].Specifically, the Cambridge Centre for Advanced Research and Education in Singapore (CARES) analysed various projects from the industry, municipalities, and research institutions, demonstrating that AI, in conjunction with CPS, can substantially contribute to the reduction, elimination, or removal of GHG emissions.Study results suggest that AI-enabled CPS offer a substantially higher potential for emissions reduction and lower costs of reducing CO2 compared to conventional decarbonization approaches [6].
This brief details that such abatement potential mainly stems from the capability and high efficiency of AI-enabled CPSs, which can integrate, operate, and manage increasingly complex and fully electrified economic systems.Those study results confirm the strategic agendas of the U.S. Department of Energy's Clean Energy Smart Manufacturing Innovation Institute (CESMII) and the European Strategic Energy Technology Plan (SET Plan) who locate digitalization and AI at the core of their decarbonization strategies [6].Based on these promising developments, the objective of this policy brief is to advocate for the mainstreaming of AI-driven cyber-physical systems, or what will be referred to here as Intelligent Decarbonization (IDC), as a vital technology for climate change risk mitigation and adaptation efforts, enabling the efficient electrification of all sectors.To grasp the full potential of IDC, the brief outlines the key components of IDC, primarily focusing on the concept of AI-enhanced CPSs and their applications across the sectors.
Building on the insights from the CARES study, the synergistic application of AI with CPSs emerges as a transformative solution in the quest for carbon neutrality.These integrated systems exemplify the fusion of advanced computation with physical processes, enabling a dynamic, responsive approach to energy management and resource optimization.In practical terms, AI-driven CPS can forecast energy needs, adaptively manage renewable energy sources, and optimize industrial and urban systems for optimal efficiency.This technology transcends traditional boundaries, offering real-time, intelligent decisionmaking and automation capabilities that are crucial for reducing operational inefficiencies and, consequently, cutting down on GHG emissions.The proficiency of AI in analysing complex datasets, coupled with CPS's capacity to interact with the physical world, paves the way for a transformative approach in managing and reducing carbon footprints across various sectors.This innovative integration not only promises to enhance the effectiveness of existing green technologies but also lays the groundwork for discovering novel pathways to achieve sustainable, eco-friendly practices, heralding a new era in the fight against climate change.
Despite the decarbonization potential associated with IDC, emphasizing climate technology as major remedy for climate change would be problematic [5], [7], [8].Climate policy can already be characterized by an overreliance on technology as the primary solution to climate change, but this emphasis has shown limited success, as evidenced by repeated warnings from the U.N. and IPCC [9].Now, IDC faces its own limitations, such as lack of data, absence of CPSs and AI solutions, and unintended reverse effects of optimizations.Furthermore, IDC is still in its early stages, making any exploration of its long-term impacts merely speculative.AI research also scarcely focuses on climate change [1], [4].However, the issue of technology solutionism is not just about engineering bottlenecks; technology itself can be part of the problem [8].As certain technologies from previous industrial revolutions contribute to today's climate crisis, AI might become part of a future crisis.This concern is not solely about AI's immense energy consumption, which will increasingly be replaced by renewable energy.Rather, it is more about the proliferation of rapidly advancing AI and the unprecedented risks that might come with it.These risks are not inherent to the technology, but rather how it is designed, used, and regulated.Like climate action, AI presents a critical juncture, giving policymakers the opportunity to steer AI towards benefiting people and the planet, as discussed further below.

III. CYBERPHYSICAL SYSTEMS AT THE CENTER OF INTELLIGENT DECARBONIZATION
To scale AI in conjunction with other digital technologies critical for climate change mitigation and to set the technology on a path that serves people and the planet, it is important to identify the major components of intelligent decarbonization (IDC).At the centre of IDC are cyber-physical systems (CPSs), which connect the physical with the virtual world through integrating computations, physical objects and processes.They monitor and control physical processes through advanced sensors and actuators, with feedback loops where the physical processes affect computations and vice versa.IDC is engineered to improve efficiency, performance, safety, and reliability through real-time data capture, exchange and analysis, as well as through self-regulation and decision automation.CPSs are enabled by a combination of advanced digital technologies that facilitate such integration, information exchange, and control between digital and physical components.Those enabling technologies include mobile communication networks (5G/6G, Wi-Fi, lowpower wide-area networks); cloud computing; edge computing; blockchain/smart contracts; Internet of Things (advanced sensors and actuators); smart metering; semantic web/knowledge graph; digital twin; Big Data; as well as machine learning [6], [10].
The concept of Cyberphysical Systems (CPS) originated in the mid-2000s in engineering and computer science to describe systems that combine sensors, decision-making software, and device outputs, thereby enabling real-world interaction based on processed data.Over the past decade, however, CPSs have emerged as a vital technological component in the industry sector, forming the basis of the "Industry 4.0" vision to transform traditional manufacturing into intelligent, adaptive, and efficient systems [3].Functionally defined by a high level of digitization, connectivity, and automation, the initial application focus has been on individual organizations and their supply chains, with the aim of creating "smart factories" [11].The rise of CPS is accompanied and further enabled by the convergence of Information Technology (IT) and Operational Technology (OT), referring to the integration of traditionally distinct technologies and systems used to manage corporate information flows and control industrial operations, respectively.Today, the initial integration and application scope of CPSs is expanding towards increasing connectivity and data exchange vertically and horizontally, not only within but also between the industry and other sectors.The aspiration behind establishing a "digitally networked industry" [12] is not just to enhance operational efficiencies and competitiveness, but also to systematically reduce carbon emissions and transform the industry towards a circular economy [13].
The dual objectives of economic growth and environmental sustainability have often been seen as conflicting when transitioning from a linear to a circular economy.However, this seems less of a case with CPSs, particularly in light of the sharply declined levelized cost of renewable electricity [14].From a technological and economic perspective, CPSs align with the requirements of net-zero transformation and decarbonization efforts.The high capability of efficiently reducing and optimizing inputs and costs, combined with that of integrating and coordinating large systems, make CPSs well-suited for the green transformation.Such capability is not limited to the industry sector but can also be employed within the other emission-intensive sectors, including electricity and heat production, transportation, buildings and cities, and agriculture (already within the former three sectors, CPSs already find increasing application).All sectors must undergo transformation to meet net-zero targets.The substitution of fossil fuels is achieved through the electrification of all economic systems with renewable energy (such as solar, wind, or hydro power); and electrification precisely requires the integration and efficient orchestration of the cyber and physical dimension.Thus, the implementation of CPSs does not only serve internal efficiency improvements of individual organizations but is an enablement for the transformation towards a low carbon economy.

IV. ARTIFICIAL INTELLIGENCE-ENHANCED CYBERPHYSICAL SYSTEMS
The convergence of AI and CPS marks a pivotal advance in decarbonization strategies.At the heart of this integration lies the potent combination of AI's advanced computational intelligence and CPS's ability to interact directly with physical processes.AI's role in this synergy is to provide deep learning capabilities, predictive analytics, and real-time decision-making, crucial for interpreting vast arrays of environmental and operational data.Simultaneously, CPS bring these insights into the physical world, orchestrating precise control over industrial systems, energy grids, and urban infrastructures.This interplay allows for a level of efficiency, adaptability, and responsiveness previously unattainable in traditional systems.In practical terms, AI-enhanced CPS can dynamically optimize energy consumption, streamline manufacturing processes, manage smart grids, and enhance urban sustainability.These capabilities are integral to transforming existing infrastructures into smarter, more sustainable systems that are critical for achieving significant reductions in GHG emissions.
As derived from the CARES study [3], [6], the pathway to GHG reduction through AI and CPS integration starts with collecting comprehensive environmental and operational data via sensors and IoT devices across sectors such as energy, transportation, and manufacturing.This data, encompassing everything from energy usage patterns to production line efficiencies, forms the backbone of AI-driven analysis.In the first step, AI Authorized licensed use limited to the terms of the applicable license agreement with IEEE.Restrictions apply.
algorithms process this data to identify inefficiencies and emission hotspots.For instance, in energy sectors, AI predicts demand trends and optimizes the integration of renewable energy sources, reducing reliance on fossil fuels.In transportation, AI algorithms analyse traffic and logistic patterns to suggest routes and methods that minimize fuel consumption and emissions.In manufacturing, AI monitors and adjusts production processes in real-time for peak efficiency, cutting down energy use and associated emissions.Following analysis, CPS, which merge physical systems with computational insights, implement these AI-driven optimizations.This might involve adjusting control systems in real-time to align with AI's energy-efficient strategies or modifying operational parameters in a manufacturing setup to minimize waste and energy use.The final step involves continuous monitoring and feedback loops where AI adjusts its predictions and recommendations based on real-time data, ensuring sustained efficiency and adaptation to changing conditions.This holistic approach, where AI provides the intelligence and CPS the operational layer, represents a dynamic and responsive strategy for reducing GHG emissions across multiple sectors.
Building upon the foundational understanding of how AI and CPS collaboratively facilitate GHG reduction, we observe the transformative impact of these technologies in the context of the growing renewable power generation, electrification, and digitalization.These developments have led to the coupling of organizations and sectors into integrated, cross-and transsectoral systems with feedback loops, significantly facilitating decarbonization across various sectors and economies.In such a landscape, CPSs combined with AI capabilities become crucial for efficiently deploying and managing these complex electrified economic systems.Serving as an overarching architectural and governance structure, CPSs ensure the essential integration, computing, and communication functions across subsystems, while AI, functioning as a sub-system, brings to the table its strengths in predictive analytics, adaptive control, and decision optimization and automation capabilities.The application of major AI/ML technologies, including computer vision, time series analysis, reinforcement learning and control, uncertainty quantification, unsupervised learning, natural language processing, transfer learning, interoperable models, and causal inferences, is increasingly evident in AI-driven decarbonization and climate change risk mitigation efforts [4].The following Table I provides an overview of selected case studies exemplifying how AI-enhanced CPS are being applied across various sectors, highlighting the specific technologies in use and their contributions to advancing decarbonization.It encapsulates the diverse and far-reaching implications of AI and CPS integration in practical, sector-specific scenarios, demonstrating the significant role these technologies play in driving sustainable transformations in our journey towards a carbon-neutral future.
AI and CPS are assuming an increasingly crucial role in broader climate change adaptation strategies, extending beyond sector-specific decarbonization efforts.These technologies are instrumental in refining decision-making processes around climate events.AI's advanced capabilities enable a deeper understanding of climate science (e.g., applications of deep learning  to Earth Observation and other remote data) and more accurate predictions of extreme weather occurrences, thus informing more effective response strategies.Furthermore, AI's analytical prowess aids in navigating the complex interplay of markets, policies, and human behaviours that are integral to comprehensive climate change mitigation and adaptation efforts.This includes supporting initiatives in geoengineering and bolstering disaster recovery operations, where timely and data-driven decisions can significantly reduce environmental and economic impacts [4].

V. CLIMATE CHANGE AND ARTIFICIAL INTELLIGENCE: A TWIN CRITICAL JUNCTURES
Situating intelligent decarbonization at the nexus of AI development and climate change mitigation, this section extends the previous discussions by critically evaluating the persistent challenges in climate change mitigation.It emphasizes that although AI holds substantial potential, it is not a standalone solution for the climate action gap.The analysis will address the dual challenges of AI governance, including the safety concerns, as highlighted above, and its own carbon footprint.
Since the first report from the Intergovernmental Panel on Climate Change (IPCC) in 1990, technology has been assigned a dominant role in tackling climate change [7].New technology -such as carbon capture and storage; plant-based and geological carbon sinks; mitigating overshoot scenarios with geoengineering; or models to estimate the impact of investments and technology on GHG emissions -plays a crucial role in climate change mitigation and has led to avoided and in some cases reduced or removed emissions.Nevertheless, technology-focused climate policies have demonstrated little success as evidenced by the ongoing warnings and increasing frustration with the inability to tackle the climate crisis more rapidly and effectively.Technology solutionism has falsely led to an oversimplification of a complex issue while omitting or accepting that existing technology, together with capitalist expansion and institutional legacies, have created a path dependency from which humanity cannot simply depart primarily based on the introduction of new technologies.Clearly, climate action faces a planetary crisis.At this point in time, it manifests as a critical juncture [8], which yet opens up the space for more far-reaching political action and global coordination and cooperation.Such efforts are urgently needed to prevent large sets of bio-physical systems from reaching climate tipping points.Arguably, such space for political agency was not available in the past.Now, surpassing 1.5 °C of global warming may lead to the activation of multiple tipping points, beyond which humanity loses control, and the consequences of severe global warming become inevitable.
In the context of current climate action, this policy brief advocates for using technology in climate change mitigation, while cautioning against overreliance on technology and the uncontrolled proliferation of AI.Like climate change, the widespread AI-driven digitalization has reached a critical juncture that makes possible and necessitates political intervention to steer AI development towards development towards societal and environmental benefits while sufficiently mitigating risks.For AI critics, the development of large generative AI models that can produce human-like text, images, videos, or audio might be considered as AI's "tipping point."Beyond this point, it could become increasingly challenging to influence or control the trajectory of rapidly advancing AI.At this critical juncture, policymakers face a dilemma [8], [25].On one hand, regulating a new technology at an early stage of its proliferation is relatively easier, while its long-term consequences remain a matter of Authorized licensed use limited to the terms of the applicable license agreement with IEEE.Restrictions apply.
speculation.On the other hand, waiting for a technology to mature leads to clearer consequences, but attempts to regulate a mature technology and mitigate these consequences often fail.To prevent unwanted path dependency, policymakers must strike a balance: regulate AI at an early stage while avoiding over-regulation, which could stifle innovation, competitiveness, and the realization of AI's tremendous efficiency potential for the green transformation and addressing other major challenges.
Importantly, AI and other digital technologies carry their own carbon footprint, which is likely to increase due to the ongoing global digital transformation.The estimated contribution of the ICT sector to global GHG emissions lies between 1.8 and 2.8 percent or are even as high as 2.1 and 3.9 percent [26].The carbon footprint of machine learning has grown tremendously in recent years.Despite ongoing efforts to increasing efficiency, the energy required specially to train large language and foundation models has raised concerns from a climate policy perspective [27].

VI. CYBERSECURITY
Increasing the connectivity of physical infrastructure through sensors, along with AI optimizing the use of infrastructure within and across sectors, will significantly enlarge the surface of cybersecurity risks and threats.Cybersecurity has been a growing concern, and the integration of AI is set to profoundly change the landscape of these risks.The adversarial use of AI could expand existing cybersecurity attack patterns, creating more effective and targeted threats, as well as entirely new types of cyberphysical threats.In addition to deliberate attacksmainly those causing disruption, theft, or espionage -there will also be unintended incidents due to engineering errors and bottlenecks, which could lead to unpredictable consequences and become targets for intentional exploitation.
Cybersecurity risks associated with AI-driven CPS are particularly concerning, as these risks are primarily related to the disruption of large-scale or critical infrastructure, essential for the functioning of an economy and society.There are instances where entire cities suffer cyberattacks, with data and systems of, for example utility services, are held hostage until a ransom is paid, thus paralyzing supply of essential services and public life.For this reason, it is essential that cyber-physical security must be a primary design criterion when developing and implementing those systems.
From a regulatory standpoint, the European Union stands as the most advanced major economic bloc in implementing a comprehensive framework of EU-wide cybersecurity regulations that are binding for the member Accordingly, the Cybersecurity Act together with the Network and Information Systems (NIS) Directive and the Critical Entities Resilience Directive (CER) mandate that key companies, considered essential or important for national and economic security, proactively address cybersecurity risks.Unlike the General Data Protection Regulation (GDPR), which focuses on protecting the data of individual citizens, these cybersecurity regulations aim to safeguard critical infrastructure sectors, including energy, transport, banking, finance, health, water, digital infrastructure, and space.Furthermore, the EU has introduced the 5G Toolbox, a strategic initiative to secure 5G networks, which are deemed integral to Europe's digital transformation.Currently, EU lawmakers are negotiating the Cyber Resilience Act (CRA) to enhance the safety of hardware and software containing digital components.Alongside this, Cybersecurity Certification Schemes are being developed to bolster defences against cybersecurity risks and improve mitigation strategies.With the AI Act, EU lawmakers have also agreed on the provisions for the globally first law that will regulate AI across different risk categories, which includes foundation and generative models.
In comparison, although the United States has yet to establish comprehensive federal cybersecurity and privacy laws, only China, as the major economic bloc, has a regulatory landscape in cybersecurity protection comparable to the EU's extensive framework.However, implementing such a broad regulatory approach is a balancing act between ensuring security and safety on one hand, and fostering innovation and competitiveness on the other.

VII. GLOBAL COLLABORATION
At this dual juncture, driven by AI and climate change, the global community faces not only a climate action gap, but also an AI governance gap [7], indicating a lack of global collaboration and coordination to ensure that AI primarily serves society's benefits, among which climate success is crucial for humanity's survival.To address the need for global collaboration, the authors believe that the role of the G20 as preferred intergovernmental forum is relevant from three perspectives: its efforts on (1) climate change, (2) knowledge and technology transfer, and (3) digitalization and AI.Firstly, the G20 recognizes the massive concern for climate change and actively pursues various initiatives, policies, and collaborative efforts aimed at addressing the challenges and driving progress towards a more sustainable future.Its member countries collectively account for approximately 80 percent of GHG emissions.The G20 encompasses both fossil energy exporters and importers, and with their commitment to a timeline for achieving net-zero emissions, both groups concur that a rapid adoption of innovative solutions is essential for successfully transitioning to a new global energy matrix.The G20 encourages collaboration on research, development, and deployment of clean technologies; promotes investments in clean energy technologies and infrastructure as well as in the deployment of renewable energy technologies [cf. 28].
Second, the G20 Development Working Group supports capacity building and the transfer of knowledge and technology to the developing world, aiming to combat climate change through various mechanisms and collaborative efforts [29].This includes mobilizing financial resources, collaborating with multilateral development banks, establishing or joining clean technology partnerships that include provisions for technology transfer and capacity building; bilateral and regional cooperation with developing countries; and the work through international frameworks, such as the United Nations Framework Convention on Climate Change (UNFCCC), who facilitate the transfer of technology and knowledge.Based on the ITU's Facts and Figures report from 2022, knowledge and technology transfer remain crucial for addressing the global digital divide.The Internet has become more affordable and widespread in all regions of the world, but one-third of the global population still remains unconnected and many countries still lack affordable access to information and communications technology [30].Many of the countries most affected by this lack of digitalization are also the ones hardest hit by climate change [9].
Finally, the G20 supports a responsible and inclusive digital transformation and human-centred artificial intelligence, as evidenced by the G20 Roadmap for Digitalization and the G20 AI Principles, respectively.As early as 2019, the G20 Leaders in Osaka acknowledged that AI has the potential to be a driving force in helping achieve the UN Sustainable Development Goals [31].Specifically, the G20 Principles emphasise that the G20 countries should collaborate on the "realisation of a sustainable and innovative global society, by making full use of digital technologies [ …] and harnessing the benefits of technological transformation" [32: 1].However, the G20 Leaders did not further elaborate or derive concrete actions addressing the intersection of the digital transformation and green transformation and, more specifically, the role AI and other digital technologies could play in more effectively driving climate change mitigation and adaptation strategies and measures.While emphasizing the role of the G20, it's important to note that the intention isn't to favour a top-down, centralized approach, which is impractical.Instead, the emphasis is on complementing decentralized, network-driven, and polycentric governance structures [33].This includes AI-centric mechanisms such as the G7 Hiroshima Process, Global Partnership on Artificial Intelligence (GPAI), UNESCO, ITU's AI for Good, and the United Nations' High-Level Advisory Body on Artificial Intelligence established in October 2023, along with regional, country-level initiatives, and those steered by corporations and civil society.

VIII. RECOMMENDATIONS TO THE GROUP OF TWENTY
Given the convening power of the G20 members, their commitment to leveraging AI and CPS technologies for climate change risk mitigation and net-zero transformation is crucial.As summarized in Table II, the following five recommendations outline actionable steps the G20 can take to promote the responsible and effective use of AI and CPS in addressing climate change.
Existing global path dependencies necessitate global collaboration and coordination to effectively tackle the climate crisis and avoid irreversible climate breakdown.The same applies to the proliferation of rapidly advancing AI systems, such as the recent emergence of generative AI and large language models.Concentration of technology resources and intense global competition over AI leadership undermines the responsible use of such technology and for the purpose of reaching net-zero transformation goals.The G20 is the most suitable global institution for urgently needed governance, given its broad representation of economic activity, its influence on international policy, and diplomatic linkages, including those between competing economic blocs and rival political systems.Amidst the escalating geopolitical tensions during the G20 meeting under India's 2023 presidency, which underscored the risk of further fragmentation in global governance, the G20 retains its significance as a vital intergovernmental forum, notably for its commendable addition of the African Union as a new member.

IX. SUMMARY AND OUTLOOK
In concluding, this policy brief has highlighted the transformative potential of integrating AI and Cyberphysical Systems in the quest for carbon neutrality.The success of these technologies in driving effective decarbonization strategies across the sectors is not solely a matter of technological innovation but equally a question of governance.Ensuring fierce competition and geopolitical differences do not further lead to the fragmentation of key technologies is crucial.Emphasis on openness and collaborative innovation, which have been drivers of technological advancement after the deregulation and liberalization of the telecommunications and other key sectors in the 1980s and 1990s, is essential.At the same time, it is imperative to manage the associated risks effectively.Recent trends towards digital sovereignty, while intended to bolster security and self-reliance, risk veering towards protectionism, potentially stifling innovation and global cooperation.
The critical importance of knowledge and technology transfer, especially to the Global South, cannot be overstated.Bridging the digital divide to ensure equitable access to advanced technologies is essential for a comprehensive global approach to climate change mitigation.The Global South, often disproportionately affected by climate change, requires empowerment with not just technology but also the necessary skills and expertise to use these tools effectively for sustainable development.This necessitates the development of training programs, collaborative research initiatives, and policy support to enable these regions to fully harness AI and CPS in climate action.Beyond the G20, other international mechanisms such as the European Union's Global Gateway, the G7 and U.S.-led Partnership for Global Infrastructure and Investment (PGI), Japan's Partnership for Quality Infrastructure, and China's Belt and Road Initiative serve as potent platforms to scale up AI and CPS globally.In addition to those development mechanisms, engaging the global AI community is crucial.This includes leveraging platforms like ITU's AI4Good, the Global Partnership on AI (GPAI), and the U.N. Secretary General's High-level Advisory Body on Artificial Intelligence, to foster collaboration and knowledge sharing, further complementing these development mechanisms in the pursuit of AI-enhanced CPS for global, sectoral decarbonization.
The rapid and widespread adoption of foundation models and generative AI underscores the rapid advancement of AI technologies.Concurrently, there is a notable dearth of research in the field of intelligent decarbonization.Currently, the implementation of AI-enhanced CPS is predominantly spearheaded by the industry sector, augmented by pioneering projects in the transportation and energy sectors.Encouragingly, the realized efficiency potential through AI-enhanced CPS aligns well with ongoing efforts in electrification and decarbonization, offering a beacon of optimism for future developments.

TABLE II RECOMMENDATIONS
TO THE G20Authorized licensed use limited to the terms of the applicable license agreement with IEEE.Restrictions apply.