The UN 2030 Agenda for Sustainable Development (SDGs) emphasizes addressing poverty, inequality, environmental sustainability, and economic growth. Artificial Intelligence (AI) has emerged as a pivotal technology capable of accelerating progress towards th ese goals. This perspective explores the potential of AI to address environmental, social, and ethical challenges related to the SDGs. The verdicts indicate that AI can significantly enhance healthcare, education, environmental protection, economic growth, and gender equality. Specific applications include renewable energy optimization, waste management, disease detection, personalized education, and the promotion of gender equality. The perspective also highlights the ethical concerns associated with AI de velopment and deployment, such as algorithmic bias, data privacy breaches, and potential job displacement. To mitigate these risks and fully harness AI’s potential, the judgment recommends the implementation of intelligent automation governance systems, pr ofessional engagement, educational initiatives, and stringent regulatory frameworks. Achieving the SDGs through AI necessitates a comprehensive, ethical approach that fosters interdisciplinary research, public -private partnerships, AI literacy among the general populace, environmentally sustainable AI policies, and adherence to ethical standards. AI advancements that align with a people -centered, ethical framework for sustainability can significantly accelerate the achievement of the SDGs, paving the way fo r a more inclusive and equitable future. Keywords: United Nations, Sustainable Development Goals, Agenda 2030, Artificial Intelligence. Key Points: • AI significantly advances SDGs in healthcare, education, environmental sustainability, economic growth, and gender equality. • Addressing ethical concerns such as algorithmic bias, data privacy, and job displacement is crucial for responsible AI deployment. • AI technologies must adopt sustainable practices to mitigate their high energy consumption and C O2 emissions. Sustainable practices should include minimizing electronic waste and promoting circular economy approaches. • Effective AI implementation requires global interdisciplinary collaboration and sharing of best practices. 2 • Policymakers should develop governance frameworks, promote AI literacy, and ensure equitable access to maximize AI benefits. Figure: AI for UNSDGs. 1. Contextual Framework and Literature Insights 1.1. Background Achieving a society characterized by fairness, economic prosperity, and environmental sustainability by 2030 requires concerted efforts from all stakeholders aligned with the United Nations’ Sustainable Development Goals (SDGs). In 2015, all UN member nations adopted the seventeen SDGs, committing to address in terrelated challenges such as hunger, poverty, climate change, gender inequality, and inadequate educational opportunities [1, 2] . The success of this ambitious agenda cruxes on the development and implementation of innovative and efficient solutions. Among these, AI has emerged as a key technology, given its widespread application across various domains. AI’s potential extends beyond the SDGs, encompassing critical areas such as healthcare, education, pollution management, economic development, and pattern identification. For instance, AI can enhance healthcare delivery through predictive analytics and personalized medicine, optimize educational pathways via adaptive learning technologies, and improve environmental monitoring and management by analyzing vast amounts of ecological data. In addition , AI can drive economic development by fostering automation and enhancing decision - making processes through sophisticated data analys is [3]. However, the integration of AI into these systems must also address significant social, enviro nmental, and ethical concerns. Issues such as algorithmic bias, data privacy breaches, and the potential for job displacement must be carefully managed to ensure that AI deployment is both fair and responsible. Despite its promise, the deployment of AI is not without drawbacks, necessitating careful consideration of its broader implications. Ethical considerations are paramount, as AI systems can inadvertently perpetuate existing inequalities or introduce new biases. Hence , there is a need for robust govern ance frameworks to oversee the ethical use of AI, ensuring that the 3 technology is deployed in a manner that aligns with societal values and promotes the public good. This perspective investigates how advanced AI technology can contribute to achieving the UN’s SDGs . It synthesizes the latest economic, technological, ethical, and social research on AI capabilities and applications. The analysis focuses on leveraging cutting -edge AI technologies as a holistic approach to simultaneously address and advance mult iple SDGs. In addition , the perspective examines how AI can be harnessed to optimize renewable energy use, enhance waste management systems, improve disease detection and treatment, tailor educational experiences to individual needs, and promote gender equ ality. The perspective proposes an AI -driven framework and strategy designed to maximize impacts across various fields, thereby fostering cohesive progress towards sustainable development. This framework emphasizes the importance of interdisciplinary colla boration, involving experts from AI, sustainability, ethics, and policy -making to create comprehensive solutions. Furthermore , it highlights the need for public -private partnerships to scale AI innovations and ensure broad access to these technologies. Public AI literacy initiatives are also crucial to enable informed participation in discussions about AI ’s role in society and its potential impacts. The integration of AI into efforts to achieve the SDGs holds significant promise but require s a balanced approach that considers both opportunities and challenges. By aligning AI advancements with a people -centered, ethical sustainability framework, we can accelerate progress towards the SDGs and pave the way for a more inclusive and equitable fu ture. 1.2. Research Context Advancements in AI technology are pivotal for achieving the UN SDGs. With the facilitation of AI, all 17 SDGs can be further supported with innovative and effective solutions , for example in the field of quality education (SDG 04) [4]. Discussions highlight how AI can help developing nations achieve SDGs 01 and 09, aiming to reduce poverty and enhance innovation and infrastructure. In devel oping countries such as China and India, AI can play an indispensable role in accelerating the process of national SDGs by monitoring, analyzing , and offering suggestions on policy tools, accelerating digital transformation and data -driven decision -making [5, 6] . AI-powered drones in disaster environments can help identify human signals and improve rescuing efficiency , contribut ing to SDG 03 on health and wellbeing [7]. The contribution of telecommunications and informatio n technology, including AI, to implementing SDGs 11 and 12 (Sustainable Cities and Communities and Responsible Consumption and Production) was also examined [8, 9] . Rapid progress in AI necessitates updating and revising several SDG targets to keep pace with technological developments. The intentional integration of AI systems can have a negative impact on SDGs. For instance, training advanced AI models requires significant processing power and energy, which can increase carbon emissions and strain energy resources, exacerbating climate change (SDG 13) [10]. Similarly, without careful design and regulation, AI-driven automation might disrupt labor markets, causing job losses and exacerbating poverty and economic instability (SDG 01) [11]. In terms of SDG 16 that focuses on building a just, peaceful, and institutionally strong world , AI-driven lethal autonomous weapon systems 4 (LAWS) are posing physical, ethical, and legal challenges to the provision of a peaceful world [12]. This paper acknowledges both the positive and negative aspects of AI, which continue to generate interest and debate. A substantial body of research suggests that AI can contribute to achieving the SDGs. However, it is crucial to design, deploy, and monitor AI systems in alignment with sustainability principles and human values, emphasizing societal and ethical responsibility. Interdisciplinary collaboration, stakeholder involvement, and careful evaluation are essential for making informed judgments about AI ’s ability to improve global conditions. 2. AI-Driven Solutions for Sustainable Development 2.1. The Impact of AI on Health and Wellbeing AI technology holds substantial potential to positively influence health outcomes and the achievement of SDGs. In healthcare (SDG 03) , AI’s capabilities extend to disease diagnosis, treatment planning, prescription management, drug discovery, and epidemiology. Machine learning algorithms can analyze patient data and information from electronic health records, aiding in early disease detection, personalized treatment formulation, and the identification of potential adverse medication side effects. This can lead to improved health outcomes, reduced healthcare costs, and more rational resource distribution [13]. AI in public health can assist in simulating the spread of infections within populations, optimizing resource allocation during pandemics or other outbreaks, and identifying high -risk groups for targeted treatments. Developing AI -enabled telemedicine and remote monitoring systems can promote equity in healthcare access, ensuring that underserve d and remote communities receive high -quality medical services [14]. Virtual patient consultations, AI - enabled diagnostics, and remote patient monitoring can facilitate healthcare access in distant locations, a critical aspect of achieving universal health coverage. AI and telehealth technologies enhance healthcare efficiency. The increasing adoption of AI in healthcare settings significantly improves patient outcomes. AI -enabled remote monitoring, virtual consultations, and data analysis streamline operations, enhance care access, and improve patient outcomes through informed decision -making [15]. In addition , AI can ensure efficient medical supply chain management, facilitating the timely delivery of essential medications and medical eq uipment during shortages. 2.2. AI for Inclusive Education and Gender Balance AI can play a significant role in advancing SDG 04 (Quality Education) and SDG 05 (Gender Equality) by enhancing accessibility to educational resources for all individuals, regardless of gender [16, 17] . The implementation of AI -driven adaptive learning platforms and intelligent tutoring systems can provide personalized educational experiences, tailoring resources and instruction to meet the unique learning needs of each student . In regions where traditional educational institutions are scarce, AI can help overcome infrastructure challenges and facilitate access to qualified education. AI’s language translation capabilities can broaden access to learning materials for students from diverse linguistic and ethnic backgrounds. In promoting gender equality, AI can be 5 utilized to identify and address gender disparities within educational materials, curricula, and career guidance resources. By analyzing textbooks, teaching methods, and professional development resources, AI can detect and eliminate gender stereotypes or imbalances, fostering more inclusive and equitable educational practices. AI-driven skills training and employment matching programs are vital for supporting women ’s professional development. These initiatives can personalize learning experiences, provide tailored support, and highlight gender biases in educational content and delivery methods [18]. By ensuring that women acquire the necessary knowledge and skills for specific careers, AI can help them capitalize on labor market opportunities, thereby promoting gender equality and empowering women. 2.3. AI in Economic Growth and Decent Work AI has the po tential to drive innovation and economic advancement significantly. It can contribute to the achievement of SDGs related to decent work and economic growth (SDG 08) as well as industry, innovation, and infrastructure development (SDG 09) by enhancing labor productivity and improving working conditions [19, 20] . These goals emphasize the importance of inclusive economic growth through productive employment, technological progress, and sustainable industrial practices. AI’s capacity to accelerate technological development can foster innovation across various sectors more rapidly than traditional methods, leading to enhanced efficiency and sustainable economic growth. Technologies such as machine intelligence and artificial intelligence can automate processes, implement predictive analytics, and optimize decision -making, thus improving manufacturing efficiency, develo ping agile supply chains, and streamlining product development cycles. This not only enhances operational efficiency but also encourages creative innovations within industries, promoting sustainable economic expansion. The integration of AI can improve lab or conditions by creating new job opportunities and enhancing workplace environments through the automation of hazardous, monotonous, or repetitive tasks. For instance, AI -enabled automated code scanning can enhance productivity in manufacturing, thereby a ligning with the economic growth objectives of SDG 08. AI -driven automation can also mitigate manual labor risks, further supporting the decent work principles outlined in SDG 08. 2.4. AI for Ecological Conservation Among the three SDGs focused on climate action and biodiversity protection, encompassing terrestrial and marine life (SDGs 13, 14, and 15), AI emerges as a highly effective tool for addressing environmental challenges. Numerous studies have demonstrated the potential of AI to aid in environmenta l conservation [21, 22] . AI-based models and forecasts are instrumental in developing strategies for climate change mitigation, producing advanced models and simulations. By analyzing extensive climate data, machine learning algorithms can uncover patterns and correlations that inform policy decisions, adaptation strategies, and the formulation of comprehensive climate action plans. 6 AI-driven data analysis and recommendations can foster environmentally friendly practices, potentially mitigating the adverse impacts of climate change. Integrating AI into the design, construction, and management of renewable energy plants can optimize the use of renewable resources . For instance, AI enhances the eco -friendliness of solar and wind farms by analyzing weather data, energy loads, and system performance, thereby maximizing the efficiency and productivity of renewable energy sources. AI technologies streamline resource ef ficiency, waste management, and the implementation of circular economy principles. The increasing effectiveness of AI in promoting environmental sustainability is reflected in the growing interest of researchers in solar photovoltaic (PV) monitoring system s [23]. These systems mitigate environmental impacts and conserve natural resources. The adoption of solar energy systems to replace non -renewable en ergy sources is illustrated by the rising installation of solar panels on residential roofs, which supports environmental sustainability and advances the SDGs. Solar -powered households reduce their carbon footprint and combat climate change, thereby contri buting to multiple SDGs. For example, they support Affordable and Clean Energy (SDG 07) by reducing reliance on non -renewable resources and enhancing energy security. Additionally, these actions align with SDG 13 on Climate Action, as solar energy generati on and solar panels reduce greenhouse gas emissions and combat climate change. Additionally , urban residential solar panels decrease building emissions and promote sustainable and resilient communities, contributing to SDG 11. 3. Outcomes and Critical Reflections 3.1. Sustainab le AI Practices While AI holds considerable potential to contribute positively to environmental sustainability and advance our sustainability goals across various domains, it also poses challenges such as high energy consumption a nd increased CO 2 emissions that must be carefully managed [8]. The environmental implications of AI technologies can be significant and warrant thorough examination. For instance, the development of large -scale AI models and the operation of AI systems can lead to substantial greenhouse gas emissions, increased energy demand, and environmental degradation. Effectively managing the ecological impacts of AI is crucial to prevent setbacks in achieving SDGs 13 (Life Below Water), 12 (Responsible Consumption and Production), and 15 (Life on Land) [21]. To address energy efficiency and sustainability challenges, AI practitioners should prioritize the adoption of energy -efficient models powered by renewable energy sou rces. Minimizing the environmental footprint of AI throughout its lifecycle requires attention to the sourcing of raw materials, reduction of electronic waste, and promotion of circular economy practices. The literature underscores the necessity for a comp rehensive and responsible approach to AI development that integrates ethical considerations, socioeconomic equity, and environmental sustainability. Collaboration among AI researchers, policymakers, private sector actors, and civil society organizations is essential for leveraging the positive aspects of AI while proactively mitigating 7 its potential risks and unforeseen consequences. Ongoing monitoring, assessment, and adaptive management are critical for ensuring that AI technologies align with the broader framework of sustainable development goals, maintaining a focus on long -term objectives. 3.2. Societal and Ethical Challenges AI has the potential to be a powerful ally in the pursuit of sustainable development; however, its implementation must be approac hed with caution to mitigate ethical and social consequences. The incorporation of incomplete, biased, or unbalanced data into machine learning models can exacerbate inequalities rather than alleviate them, as such datasets may overlook critical societal factors that demand equity, thereby worsening existing disparities [24]. The goals of the SDGs aimed at reducing inequality and fostering inclusivity face increased challenges under these circumstances. The training and opera tion of large -scale AI systems on personal datasets raise significant privacy concerns, necessitating robust data governance and the adoption of privacy -enhancing measures. In addition, the risk of job displacement across various sectors due to AI adoption may exacerbate economic inequalities, hindering progress toward inclusive and sustainable economic growth as outlined in the SDGs [25]. The concentration of AI capabilities within a limited number of organizations can lead to power imbalances and potenti al misuse of these technologies, fostering conflicts and impeding advancements toward goals aimed at achieving equity and promoting a peaceful and inclusive society. To mitigate these risks, it is essential to establish sustainable governance frameworks, e nsure broad stakeholder participation, and implement reskilling and upskilling initiatives for the workforce. These measures will help ensure that the benefits of AI are equitably distributed, thereby promoting social fairness and reducing the potential ne gative impacts associated with AI deployment. 4. Actionable Insights for Policymakers To achieve long -term sustainable development while addressing the inherent risks associated with AI technologies, a range of measures aligned with the principles of humanizing AI is essential. First, it is necessary to establish a framework and guidelines for AI governance that emphasize ethical and equitable development. This framework should address critical issues such as accountability, transparency, and fairness, as these concerns are integral to the functioning of AI systems. Second, organizing and implementing training and skills enhancement programs is vital for equipping workers with AI and data literacy. This knowledge will enable employees to e ffectively leverage AI for the realization of sustainable projects. Third, fostering collaboration between the public and private sectors is important, particularly through multi -stakeholder dialogues that incorporate diverse perspectives, resources, and e xpertise to support the SDGs. Finally, the development and promotion of inclusive AI technologies tailored to marginalized and underrepresented groups are essential. These technologies should ensure an equitable distribution of the benefits derived from AI advancements within society. 8 5. Closing Remarks and Future Prospects The increasing deployment of AI technologies is vital for accelerating progress toward the UN SDGs. AI has the potential to address complex environmental challenges and contribute to economic and social development, while also serving as a tool to improve accessibility and health outcomes. However, it is imperative to address ethical and social considerations to ensure the responsible development of AI systems. To effectively combat socie tal inequalities and foster a sustainable future, issues such as algorithmic bias, data privacy, and the environmental impacts of AI must be taken into account. The successful harnessing of AI ’s capabilities will depend on collaborative efforts and the involvement of diverse stakeholders. The exchange of ideas and knowledge among countries, organizations, and communities can facilitate the dissemination of proven best practices. Furthermore , prioritizing interdisciplinary research in conservation can drive AI advancements while addressing sustainability and ethical concerns, which necessitate ongoing investment. This approach should include capacity - building initiatives that enhance AI and digita l literacy across all sectors, enabling stakeholders to engage in AI -driven solutions for the 17 SDGs. Above and beyond , comprehensive governance frameworks and regulations grounded in principles of transparency, accountability, and fairness are essential for the effective management of AI systems. The strategic and conscientious integration of AI is key to achieving the SDGs, aiming to create an environmentally sustainable, socially equitable, and economically viable world for all. It is crucial that AI is applied in ways that minimize harm and unintended consequences while adhering to ethical guidelines and social objectives. A future in which technology and societal values align is essential for realizing these goals. Declaration of Competing Interest: The authors declare no competing financial interests or personal relationships that could have appeared to influence the work reported in paper. Authors Contribution: Mirza Abdul Aleem Baig designed the concept of article; Jingchen Huang and Jingzehua Xu made substantial contribution to acquisition and analysis of data. Funding: No funding received for this research. Data Availability: Data sharing is not applicable to this article.