With accelerating climate change and rising global energy consumption, the application of artificial intelligence (AI) and machine learning (ML) has emerged as a crucial tool for enhancing energy efficiency and mitigating the impacts of climate change. However, their implementation has a dual character: on one hand, AI facilitates sustainable solutions, including energy optimization, renewable energy integration and carbon reduction; on the other hand, the training and operation of large language models (LLMs) entail significant energy consumption, potentially undermining carbon neutrality efforts. Key findings include an analysis of 237 scientific publications from 2010 to 2024, which highlights significant advancements and obstacles to AI adoption across sectors, such as construction, transportation, industry, energy and households. The review showed that interest in the use of AI and ML in energy efficiency has grown significantly: over 60% of the documents have been published in the last two years, with the topics of sustainable construction and climate change forecasting attracting the most interest. Most of the articles are published by researchers from China, India, the UK and the USA, (28–33 articles). This is more than twice the number of publications from researchers around the rest of the world; 58% of research is concentrated in three areas: engineering, computer science and energy. In conclusion, the review also identifies areas for further research aimed at minimizing the negative impacts of AI and maximizing its contribution to sustainable development, including the development of more energy-efficient AI architectures and new methods of energy management.

The integration of artificial intelligence (AI) technologies is reshaping diverse domains of human activity, including natural resource management, urban and rural planning, agri-food systems, industry, energy, education, and healthcare. However, the impact of AI on the sustainability of local ecosystems remains insufficiently systematized. This highlights the need for a comprehensive review that considers spatial, sectoral, and socio-economic characteristics of regions, as well as interdisciplinary approaches to sustainable development. This study presents a scoping review of 198 peer-reviewed publications published between 2010 and March 2025, focusing on applied cases of AI deployment in local contexts. Special attention is given to the role of AI in monitoring water, forest, and agricultural ecosystems, facilitating the digital transformation of businesses and territories, assessing ecosystem services, managing energy systems, and supporting educational and social sustainability. The review includes case studies from Africa, Asia, Europe, and Latin America, covering a wide range of technologies—from machine learning and digital twins to IoT and large language models. Findings indicate that AI holds significant potential for enhancing the efficiency and adaptability of local systems. Nevertheless, its implementation is accompanied by notable risks, including socio-economic disparities, technological inequality, and institutional limitations. The review concludes by outlining research priorities for the sustainable integration of AI into local ecosystems, emphasizing the importance of cross-sectoral collaboration and scientific support for regional digital transformations.

Achieving sustainable development in the low-carbon transition requires securing critical raw materials (CRMs) while reducing environmental burdens and strengthening industrial resilience (SDGs 7, 9, 12, 13). This review synthesizes 2016–2025 evidence on how the European Union’s policy package—the Critical Raw Materials Act (CRMA), the Batteries Regulation, the Ecodesign for Sustainable Products Regulation (ESPR) with Digital Product Passports (DPPs), and the recast Waste Shipments Regulation (WSR)—shapes markets for secondary supply in battery-relevant metals such as lithium, cobalt, nickel, copper, aluminum, and rare earths. We apply a structured scoping review protocol to map the state of the art across policy instruments (EPR, ecodesign/DPP, recycled content mandates, recovery targets, shipment controls) and value chain stages (collection, preprocessing, refining, manufacturing). The analysis highlights benefits, including clearer investment signals, improved traceability, and emerging opportunities for industrial symbiosis, but also identifies drawbacks such as heterogeneous standards, compliance costs, and trade frictions. Evidence gaps remain, especially in causal ex post assessments, price pass-through, and interoperability of MRV/DPP systems. The paper contributes by (i) providing an integrative framework linking policy instruments, value chain stages, and investment signals for secondary CRM supply, and (ii) outlining a research agenda for rigorous ex post evaluation, improved MRV/DPP data architectures, and better alignment between EU trade rules, circularity, and a just energy transition.

This paper explores the elements of support and development of entrepreneurship in Ukraine. It suggests that digitalization is an important organizational component in the development of the business sector in the knowledge economy. The authors present a comprehensive study of the most advanced domestic business ecosystems (Diia, UNIT.CITY, Genesis) and highlight their key characteristics, i.e., type of ownership, structure, mission and vision, services for entrepreneurs, investment fund availability, and areas and types of investment. The paper concludes that support for entrepreneurship in Ukraine is based on the principles of efficiency, accessibility, social security, openness, and transparency. Entrepreneurship support is considered as a set of measures of the state-funded and private institutions and organizations aimed at ensuring the sustainable functioning of small and medium-sized business entities and stimulating their development by creating the following favorable conditions: building a competitive environment and increasing competitiveness; fostering investment and innovation efforts; promoting manufactured goods (works, services) or knowledge-based products in domestic and foreign markets; ensuring employment by supporting the citizens’ entrepreneurial initiatives. Areas of public and private support of domestic entrepreneurship include provision of information, consultancy, and special services. Moreover, the paper pays special attention to the forms and methods of supporting businesses and entrepreneurship under martial law in Ukraine in 2022.

Amidst the growing challenges of climate change, the advancement of bioenergy in Ukraine emerges as a strategic imperative for achieving sustainable development, energy independence, and compliance with international climate commitments. As one of the key pillars of Ukraine’s economy, the agricultural sector holds vast potential for renewable energy production, utilizing both crop residues and dedicated energy crops. This study provides a comprehensive assessment of the current state and potential of agrobiomass, taking into account the destruction of infrastructure and the urgent need for soil restoration. The novelty of this research lies in its in-depth evaluation of Ukraine’s bioenergy potential under conditions of energy system destabilization and in the introduction of innovative solutions aimed at strengthening sectoral resilience. The findings highlight the critical importance of expanding bioenergy production while identifying key institutional and regulatory barriers that hinder its progress. This study proposes actionable strategies to overcome these challenges, including the adaptation of international best practices, regulatory framework enhancements, and the implementation of targeted government support programs. The insights are valuable not only for policymakers in Ukraine but also for other countries striving to accelerate the transition to renewable energy and establish sustainable decentralized energy systems. Future research directions include the development of cutting-edge biomass processing technologies, a thorough economic evaluation of bioenergy’s long-term impact on energy and environmental sustainability, and an in-depth exploration of bioenergy’s cross-border potential to enhance the energy security and resilience of the European Union.

The purpose of the article is to analyze the impact of the openness of a company to stakeholders on the effectiveness of the business model of the enterprise. The hypothesis. We believe that conducting a socially responsible business, i.e., disclosing non-financial information about the activities of enterprises, leads to the improvement of their financial indicators and is therefore evidence of a more effective implementation of their business models. Methods of the study. The following methods were used in the study: analysis and synthesis, comparative, induction and deduction, scientific abstraction, decomposition and logical generalizations in the analysis of scientific literature; computational–analytical, diagnostic, tabular and economic–statistical methods to assess the effectiveness of the implementation of business models of enterprises; diagnostic, statistical, index, method of expert assessments and rating to assess the corporate sustainability and transparency of enterprises; the use of the method of integrated indicators allowed the grouping of enterprises by classes of efficiency of business models, corporate sustainability and transparency. According to results of the study, it was determined that an effective business model is formed on the basis of maximum transparency and corporate sustainability in conditions of unpredictability and instability of the external environment.