Ichsan Kurniawan, Made Sudiarta, Luh Mei Wahyuni, Ida Ayu Ketut Sumawidari · 7 authors
The rise of Decentralized Finance (DeFi) represents a transformative shift in the global financial landscape, challenging traditional financial models and offering new possibilities for a more inclusive and efficient financial system. This study aims to explore the opportunities and challenges that DeFi poses to the conventional financial sector, focusing on its impact on banking, credit systems, investments, and payment systems. A mixed-methods approach was employed, including secondary data analysis, expert interviews, and first-hand experience with DeFi protocols such as lending, borrowing, and arbitrage. The findings highlight the significant potential of DeFi in creating alternative financial models that can increase financial inclusion, enhance access to capital, and reduce transaction costs. Recent data indicates that the Total Value Locked (TVL) in DeFi platforms has surged to over $50 billion as of January 2025, reflecting growing adoption. Additionally, daily transaction volumes across major DeFi platforms have reached approximately $10 billion, with active users exceeding 4 million globally. However, the research also identifies critical challenges, including regulatory uncertainty, security vulnerabilities, and the complexity of DeFi platforms, which pose barriers to mainstream adoption. This paper contributes to the understanding of how DeFi can reshape the financial ecosystem, offering insights into its future potential, the risks involved, and the steps required to address the existing challenges. Furthermore, it underscores the need for ongoing research into the regulatory aspects of DeFi and its collaboration with traditional financial institutions.
Бүгінде қаржы секторы Биткойн және Эфириум сияқты криптовалюталар басқаратын блокчейн технологиясы мен ақылды келісімшарттар ұсынатын мүмкіндіктермен мүлдем жаңа дәуірге аяқ басты. Осы жаңа дәуірде таратылған құрылымға ие және қауіпсіз, ашық және өзгермейтін жазу жүйесін ұсынатын блокчейн технологиясы арқылы қаржы секторына әкелген ең маңызды жаңалықтардың бірі - DeFi деп аталатын орталықтандырылмаған қаржылық қосымшалар. DeFi дәстүрлі қаржылық жүйені түрлендіретін, орталық органдарды алмастыратын жүйені құруға мүмкіндік беретін және негізінде ашық әрі қолжетімді қаржы жүйесін құру үшін блокчейн технологиясын қолданатын экожүйе ретінде қабылдана бастады. DeFi қосымшалары арқылы банктерге немесе әртүрлі қаржылық делдал институттарына жүгінбей-ақ ашық және қауіпсіз транзакциялар жасауға бағытталған. Орталықсыздандырудың арқасында пайдаланушыларға өз активтерін толық бақылау қамтамасыз етіледі және олардың орталық органдарға тәуелділігі төмендейді. Бұл зерттеудің мақсаты DeFi-дің (Decentralized Finance-орталықтандырылмаған қаржы) негізгі принциптері мен мүмкіндіктерін бағалау және оның CeFi-ден (Centralized Finance-орталықтандырылған қаржы) айырмашылығын көрсету болып табылады. Мақалада талдау, индукция және дедукция, салыстырмалы талдау әдістері қолданылды. Зерттеудің теориялық және әдіснамалық негізі шетелдік ғалымдардың ғылыми еңбектері мен Defillama және CoinMarketCap ұйымдарының статистикалық есептері болып табылады. Зерттеу нәтижесінде DeFi экожүйесінің орталықсыздандыру және делдалдық институтсыз транзакция жасау сияқты артықшылықтары бар болса да, оның әртүрлі жүйелі және жүйелі емес тәуекелдері бар (мысалы, реттеу, тұтынушылық, технологиялық және операциялық). Бұл тәуекелдер пайдаланушыларды инвестициялық шығынға ұшыратады. Жүйедегі негізгі технологияны түсіну және күшті қауіпсіздік шараларын қолдану арқылы пайдаланушылар осы ықтимал қауіптерді азайта алады. DeFi пайдаланушылары осы ықтимал тәуекелдерді білуі, жаңа платформаларға қатысуы және инвестициялауда мұқият болуы керек. Нәтижесінде, орталықтандырылмаған қаржы әкелетін инновациялық мүмкіндіктерді кеңінен тану және жүйе ішіндегі ықтимал тәуекелдерді азайту арқылы тезірек, арзанырақ және қолжетімді қаржылық қызметтер ұсынылып, DeFi экожүйесі кеңірек таралуы мүмкін.
Smart contracts are revolutionizing financial transactions by automating contractual agreements through blockchain technology, eliminating the need for intermediaries while enhancing security, efficiency, and accessibility across the financial sector. These self-executing protocols operate on predefined conditions, automatically verifying and executing terms without human intervention. Built on distributed ledger technology, smart contracts inherit key blockchain characteristics, including immutability, transparency, and cryptographic security, creating auditable transaction trails that significantly reduce fraud potential. While offering substantial benefits like reduced operational costs, accelerated settlement times, and enhanced financial inclusion, smart contracts face critical challenges, including security vulnerabilities, regulatory uncertainty across jurisdictions, and scalability limitations. Ongoing developments in security approaches like formal verification and specialized auditing firms are addressing vulnerability concerns, while progressive regulatory frameworks are emerging in forward-thinking jurisdictions. The future integration landscape is being shaped by advancements in cross-chain interoperability, Oracle integration for real-world data feeds, layer-2 scaling solutions, AI-enhanced optimization, and hybrid systems combining traditional legal contracts with automated execution. As blockchain technology matures, smart contracts are positioned to fundamentally transform financial infrastructure, contingent upon the continued evolution of security practices and regulatory frameworks.
This systematic review investigates the transformative impact of artificial intelligence (AI) and financial technology (FinTech) innovations on small and medium-sized enterprise (SME) financing, with a focus on enhancing transparency, efficiency, and financial inclusion. Despite the significant potential of AI and FinTech, substantial gaps remain in understanding their cross-regional and cross-industry effects, as well as in addressing persistent challenges such as AI adoption barriers, regulatory constraints, and decentralized data integration. The review synthesizes findings from peer-reviewed articles published from 2024 onward, sourced from Scopus and Web of Science databases, and examines the role of AI-driven solutions and digital financial platforms in SME financing. Results indicate that AI applications in risk assessment and credit scoring have reduced processing times by approximately 40% and improved loan approval rates by 25%. FinTech innovations have contributed to a 30% increase in financial inclusion, particularly among underserved SMEs in emerging economies. However, critical challenges, including data privacy concerns and limited technological infrastructure, continue to hinder broader adoption. This study contributes to the existing body of knowledge by systematically highlighting the role of AI and FinTech in enhancing SME financial performance and by providing actionable insights for policymakers, financial institutions, and entrepreneurs. The findings underscore the need for future research to address adoption barriers and to conduct cross-country comparative studies. Limitations include the exclusive focus on English-language, peer-reviewed sources, which may restrict the generalizability of the conclusions. Further investigations are recommended to explore the long-term impact of AI and FinTech innovations on SME sustainability and the evolution of regulatory frameworks supporting their implementation.
Financial derivatives are widely recognized for their effectiveness in managing interest rate risk, demonstrating the principle of comparative advantage in finance. However, traditional financial derivative transactions are often complex and can expose participants to market and credit risks. To mitigate these risks, reduce transaction costs, and enhance liquidity, this paper proposes a blockchain-based matching mechanism for financial derivatives that uses smart contracts for decentralized counterparty matching and settlement. Smart contracts facilitate secure data sharing among participants, ensuring the integrity and immutability of transaction data. We design a transaction pool mechanism-based smart contracts for counterparty matching and automatic settlement of financial derivatives involving real fiat currencies and introduce an efficient peer-to-peer counterparty matching method, where the entire trading process is conducted on a decentralized blockchain, ensuring greater security and transparency. A prototype implementation based on Ethereum smart contracts validates the effectiveness of our proposed model, demonstrating its potential to streamline and secure financial derivative transactions.
Iulia Cristina Iuga, Raluca Andreea Nerişanu, Larisa-Loredana Dragolea
This study investigates the risk spillover between clean and dirty cryptocurrencies and their impact on green finance indexes (solar, wind, and nuclear energy) and regional economic indexes (Baltic Dry Index and CRB Index), with data processed using the diagonal BEKK model. The results identify several dirty cryptocurrencies such as: Ethereum Cash (ETC), Litecoin (LTC), and Bitcoin (BIT) as potential diversifiers and hedges with specific green energy and economic indexes. Our findings show that news from the cryptocurrency markets predominantly have a positive, significant effect on the covariance with green finance indices. The study also presents the covolatility spillover effect, showcasing the impact of a return shock in one market, such as the cryptocurrency market or the green finance market, on the co-volatility between markets, including regional economic indices like the Baltic Dry Index and CRB Index. The analysis reveals differential spillover patterns between clean and dirty cryptocurrencies and various green finance indices, highlighting the complexity of their interactions and the varying degrees of influence on regional economic indicators.
This study aims to critically examine the compatibility of Bitcoin and blockchain technology with Islamic economic and legal principles within the context of a rapidly evolving digital financial system. Employing a literature review method based on the PRISMA approach, this research analyzes five authoritative classical Islamic jurisprudence texts alongside 40 scholarly articles from credible academic sources. The primary focus lies in evaluating how these emerging technologies correspond with key Islamic financial values, particularly the prohibitions of riba (interest), gharar (excessive uncertainty), and maysir (speculation/gambling), while also exploring their potential for innovation in building a Shariah-compliant financial infrastructure. The findings demonstrate that while Bitcoin, due to its high volatility and speculative nature, poses significant concerns under Shariah principles mainly due to its proximity to elements of maysir and gharar blockchain technology itself offers considerable promise. As a decentralized and transparent ledger system, blockchain can enhance justice (‘adl), trust (amanah), and efficiency in Islamic financial transactions. It supports the reduction of transaction costs, improves transparency, and eliminates reliance on intermediaries aligning with core objectives of Islamic economic ethics. Furthermore, blockchain technology provides a foundation for innovative financial instruments that uphold Shariah compliance, such as asset-backed stablecoins, automated smart contracts for contracts like murabahah or mudarabah, and real-time Shariah audits. The study finds increasing institutional support across Southeast Asia and the Middle East, where Islamic finance authorities, governments, and fintech developers are actively working to embed blockchain into compliant financial ecosystems. In conclusion, although Bitcoin's speculative characteristics challenge its Shariah compliance, blockchain technology opens significant opportunities to innovate and strengthen Islamic digital finance. The realization of this potential depends on sustained collaboration among Shariah scholars, technologists, regulators, and financial institutions to ensure all developments are guided by the objectives of maqasid al-shariah. This research contributes to the ongoing discourse on how Islamic values can shape the future of ethical and inclusive financial technologies.
This comprehensive article examines the transformative impact of cloud computing and artificial intelligence on regulatory compliance and risk management in the financial services sector. It explores how financial institutions are embracing cloud technologies to enhance operational capabilities while navigating an increasingly complex regulatory landscape. The article details how AI-driven solutions are reshaping compliance frameworks through advanced machine learning for fraud detection, natural language processing for regulatory analysis, and enhanced anti-money laundering systems. The article analyzes architectural considerations and implementation strategies for AI-powered compliance frameworks, supported by real-world case studies that demonstrate significant improvements in efficiency and effectiveness. Furthermore, the article investigates emerging technologies poised to further transform regulatory compliance, including federated learning, explainable AI, quantum computing, and solutions for decentralized finance. By examining both the opportunities and challenges of AI-driven compliance, this research provides valuable insights for financial institutions seeking to optimize regulatory compliance while maintaining operational efficiency in cloud environments.
Purpose The integration of blockchain technology and artificial intelligence (AI) is reshaping the financial services industry, offering transformative solutions in areas such as risk management, fraud detection, regulatory compliance and operational efficiency. Design/methodology/approach This paper presents a systematic literature review of over 100 peer-reviewed studies published between 2020 and 2024, analyzing the benefits, challenges and future directions of blockchain-AI applications in financial services. Our findings reveal that while blockchain enhances data integrity, security and transparency, AI drives predictive analytics, automation and decision-making efficiency. Findings The synergy of these technologies holds significant potential yet faces critical challenges related to scalability, interoperability, regulatory compliance and ethical AI governance. We identify key research gaps, including the lack of standardized regulatory frameworks, limited real-world case studies and technical barriers to integration. To address these gaps, we propose a comprehensive theoretical framework linking technological advancements to regulatory and ethical considerations. This study contributes to both academic discourse and industry practice, offering actionable insights for financial institutions, technology developers and policymakers navigating the rapidly evolving FinTech landscape. Research limitations/implications The rapidly evolving nature of blockchain and AI technologies may limit the long-term applicability of some findings. The study primarily focuses on published academic literature, potentially overlooking some industry-specific developments. Future research should address the identified gaps, particularly in cross-chain interoperability, ethical AI frameworks, and long-term economic impacts. Empirical studies and case analyses could further validate the theoretical insights presented in this review. Originality/value This study provides a novel, comprehensive synthesis of blockchain and AI applications in financial services, offering valuable insights for both academics and practitioners. By critically examining the synergies and challenges of these technologies, it presents a unique perspective on their transformative potential in FinTech. The proposed research agenda addresses crucial gaps in current knowledge, guiding future investigations. The findings contribute to a deeper understanding of the complex interplay between technological innovation, regulatory frameworks and ethical considerations in the evolving landscape of financial services.
This study investigates the impact of blockchain technology adoption on the financial performance of major Australian banks, specifically Commonwealth Bank, Westpac, and ANZ, from 2016 to 2023. Using a descriptive research design and secondary data from annual reports, financial performance was assessed through Return on Assets (ROA) and Return on Equity (ROE). The findings indicate a positive relationship between blockchain adoption and improved financial performance, suggesting gains in efficiency, cost management, and profitability. The study focuses on the Australian banking sector within its unique regulatory and market context. The originality of this research lies in its localized empirical approach, providing context-specific evidence of blockchain’s strategic contribution to financial performance in banking.
This study addresses the critical need for enhanced security in blockchain-based smart contracts, which are vulnerable to various exploits. Building on the existing Smartcheck tool, we conduct a comprehensive analysis of common vulnerabilities, including integer overflow, delegatecall, and timestamp dependence, and propose methodological improvements. We developed SmartETH, an advanced static analysis tool, incorporating improved detection algorithms to effectively identify and mitigate these security risks. Utilizing a dataset of 3,000 verified contracts from Etherscan, SmartETH was evaluated against the original Smartcheck and other tools such as Oyente and Slither. The results demonstrate that SmartETH significantly reduces both false positives and false negatives, achieving higher accuracy and reliability in vulnerability detection. Consequently, SmartETH provides a robust solution for securing smart contracts, thereby enhancing trust and safety in blockchain applications.
This study examines the role of crypto funds (CFs) in enhancing the valuation and performance of decentralized digital platforms (DDPs) by mitigating coordination frictions and information asymmetries. Drawing on panel data from 1,200 Ethereum-based projects and event-study evidence around CF investment disclosures, we find that CF-backed DDPs achieve significantly higher token valuations in the primary market, experience positive cumulative abnormal returns (CARs) around investment announcements, and outperform non-CF-backed peers’ post-issuance. The impact of CFs is stronger when they hold central positions in investor networks and when token ownership is more decentralized. Robustness checks using alternative dependent variables, subsample analyses, and interaction terms confirm the validity of the findings. These results highlight the importance of institutional capital not only in financing but also in signaling quality and enhancing governance in decentralized ecosystems. Policy implications include the need for standard CF disclosure practices, token distribution guidelines, and improved audit standards for smart contracts. The findings contribute to emerging debates on institutional legitimacy, valuation dynamics, and governance in the digital asset economy.
This dissertation explores the evolving landscape of decentralized finance (DeFi), addressing critical challenges such as scalability, consumer protection, front-running, and stablecoin stability. By bridging the gap between technological advancements and regulatory needs, the research provides innovative solutions to enhance DeFi’s accessibility, security, and scalability. The study investigates fast withdrawal mechanisms in optimistic rollups, enabling users to bypass the traditional seven-day dispute period through tradeable exits. By implementing and analyzing these exits on platforms like Arbitrum, the work evaluates their efficiency, scalability, and risks, offering practical insights into dispute management. Decentralized order books form another key focus, with a detailed examination of their feasibility, performance, and front-running vulnerabilities. Through the implementation of the Lissy exchange on Ethereum and Layer 2 solutions, the research demonstrates significant improvements in gas efficiency and scalability while proposing novel strategies to mitigate transaction manipulation. The dissertation also provides a systematized framework for understanding stablecoins, categorizing their stability mechanisms and highlighting vulnerabilities. This analysis lays the groundwork for assessing their role in mitigating volatility and enhancing financial inclusion. Overall, this work contributes to DeFi’s maturation by addressing technical and regulatory challenges, ensuring user centric design while promoting financial innovation. The findings aim to align DeFi with consumer protection frameworks, paving the way for its broader adoption as a reliable alternative to traditional financial systems.
Hassen Louati, Ali Louati, Elham Kariri, Abdulla Almekhlafi
Blockchain technology has transformed modern digital ecosystems by enabling secure, transparent, and automated transactions through smart contracts. However, the increasing complexity of these contracts introduces significant challenges, including high computational costs, scalability limitations, and difficulties in detecting anomalous behavior. In this study, we propose an AI-based optimization framework that enhances the efficiency and security of blockchain smart contracts. The framework integrates Neural Architecture Search (NAS) to automatically design optimal Convolutional Neural Network (CNN) architectures tailored to blockchain data, enabling effective anomaly detection. To address the challenge of limited labeled data, transfer learning is employed to adapt pre-trained CNN models to smart contract patterns, improving model generalization and reducing training time. Furthermore, Model Compression techniques, including filter pruning and quantization, are applied to minimize the computational load, making the framework suitable for deployment in resource-constrained blockchain environments. Experimental results on Ethereum transaction datasets demonstrate that the proposed method achieves significant improvements in anomaly detection accuracy and computational efficiency compared to conventional approaches, offering a practical and scalable solution for smart contract monitoring and optimization.
ABSTRACT The introduction of digital money such as Bitcoin, and the underlying blockchain and distributed ledger technology, created huge interest. The developments have posed the possibility of major implications for the financial system and potentially the whole economy. This article tackles the topic of a central bank ought to issue digital money for widespread use. Defines a benchmark central bank digital currency with characteristics like cash.The implications of such a digital currency are analyzed, with particular attention to central bank title, monetary policy, the banking system, financial stability, and payment. This Study delivers a CBDC that is considerably different from the accepted digital currency is assessed. However, their successful incorporation requires careful consideration of a multitude of issues, not to mention rewarding and balancing risks, to establish firm foundations that minimize these risks and take advantage of CBDCs’ potential to drive a more equal and efficient financial system.
This study explores the transformative potential of Iskargul, an innovative platform that revolutionizes agricultural trade through blockchain integration. It provides a comprehensive analysis of Iskargul, including user interface design principles, the detailed implementation of blockchain technology, transparency, smart contracts, user feedback, and a comparison with traditional systems. The user-centric design principles of Iskargul ensure an inclusive and functional interface for both farmers and consumers. The integration of blockchain technology is systematic, focusing on security, scalability, and efficiency. The findings show that Iskargul effectively addresses transparency and traceability issues by recording and tracking the entire journey of products, thereby fostering trust in the supply chain. Smart contracts automate transactions, resulting in high user satisfaction. Despite positive feedback, the study identifies adoption challenges, particularly related to the blockchain learning curve. In comparison with traditional systems, Iskargul excels in efficiency, cost-effectiveness, and user satisfaction, highlighting the transformative potential of blockchain in optimizing the agricultural supply chain. This study offers valuable insights into agricultural trade and blockchain technology, emphasizing the feasibility of blockchain-powered platforms in reshaping traditional practices. While adoption challenges exist, the positive outcomes suggest that blockchain can revolutionize agricultural trade, creating a more efficient, transparent, and secure ecosystem.
Decentralized Finance (DeFi) remains a complex domain, difficult for newcomers to grasp due to abstract mechanisms like liquidity pools, decentralized exchanges (DEXs), and asset swapping. This paper proposes Black Doge — a multichain digital asset — as a form of "digital stationery" for students to practically learn DeFi concepts. Black Doge, existing across multiple blockchain networks, can simulate real-world DeFi activities in a controlled educational environment. We explore the significance of this approach, its impact on student learning, future blockchain adoption, DEX usability, and broader blockchain ecosystem development.
In recent years, the development of Solidity smart contracts has been increasing rapidly in popularity. Code cloning is a common coding practice, and many prior studies have revealed that code clones could negatively impact software maintenance and quality. However, there is little work systematically analyzing the nature and impacts of code clones in solidity smart contracts. To bridge this gap, we investigate the prevalence, evolution, and bug-proneness of code clones in solidity smart contracts, and further identify the possible reasons for these clones' occurrences. With our evaluation of 26,294 smart contracts with 97,877 functions, we have found that code clones are highly prevalent in smart contracts. Additionally, on average, 32.01% of clones co-evolve, indicating the need for careful management to avoid consistency issues. Surprisingly, unlike in traditional software development, code clones in smart contracts are rarely involved in bug fixes. Finally, we identify three main factors that affect the occurrences of clones. We believe our study can provide valuable insights for developers to understand and manage code clones in solidity smart contracts.
In recent years, cryptocurrencies have attracted growing attention from both private investors and institutions. Among them, Bitcoin stands out for its impressive volatility and widespread influence. This paper explores the predictability of Bitcoin's price movements, drawing a parallel with traditional financial markets. We examine whether the cryptocurrency market operates under the efficient market hypothesis (EMH) or if inefficiencies still allow opportunities for arbitrage. Our methodology combines theoretical reviews, empirical analyses, machine learning approaches, and time series modeling to assess the extent to which Bitcoin's price can be predicted. We find that while, in general, the Bitcoin market tends toward efficiency, specific conditions, including information asymmetries and behavioral anomalies, occasionally create exploitable inefficiencies. However, these opportunities remain difficult to systematically identify and leverage. Our findings have implications for both investors and policymakers, particularly regarding the regulation of cryptocurrency brokers and derivatives markets.
Blockchain-enabled smart contracts have revolutionized secure, automated, and decentralized transaction handling across various industries. However, they face limitations in complex decision-making due to their rigid execution and predefined rules. This paper explores the integration of a hybrid deep learning model with blockchain-enabled smart contracts to enhance their functionality and decision-making capabilities. By embedding deep learning layers within the smart contract framework, this approach enables real-time data analysis, predictive analytics, and adaptive decision-making, fostering a more robust and dynamic contract execution. Through this integration, the hybrid model can analyse transaction data, external conditions, and contextual parameters, improving contract outcomes in applications like finance, supply chain management, and healthcare. Experimental evaluations demonstrated that the proposed model achieved 98% accuracy, with a precision of 97.65%, a recall of 97.4%, and an F1-score of 97.5%, significantly enhancing smart contract flexibility and resilience while maintaining security and transparency.
Cross-border payments face persistent challenges in today's global economy, characterized by high costs, lengthy processing times, and operational inefficiencies within traditional correspondent banking models. The emergence of blockchain technology offers a transformative solution to these long-standing issues through its distributed ledger architecture, smart contracts, and innovative consensus mechanisms. By eliminating intermediaries and automating processes, blockchain implementation in cross-border payments demonstrates the potential to revolutionize international money transfers by reducing transaction times, lowering costs, and enhancing transparency. The technology's inherent features address critical pain points in current systems while providing robust security measures and improved auditability, particularly benefiting developing economies and regions with limited banking infrastructure.
The financial data of educational institutions involves multiple stakeholders, making its security critically important. Traditional financial management models are prone to privacy breaches, unreliable data, and unauthorized access. To address these challenges, this paper proposes a blockchain-based smart contract-driven financial management system for educational institutions. The system integrates an enhanced secret-sharing scheme, the DP-ABE encryption algorithm, and a hierarchical access control mechanism to ensure secure data management. Tests in a multi-node blockchain environment demonstrate that the BC-EIFM system not only enhances encryption strength but also achieves high execution efficiency and system stability. It effectively supports data storage, sharing, and access control in complex educational scenarios.
Mohammad Alauthman, Amjad Aldweesh, Ahmad Al–Qerem, Saad Alateef · 5 authors
Blockchain technology has emerged as a transformative tool for enhancing accountability, transparency, and efficiency in e-government systems. This study explores the integration of blockchain-based architectures within startup-driven e-government models, focusing on secure identity management, automated public service workflows, and tamper-resistant record-keeping. By leveraging smart contracts and permissioned distributed ledgers, blockchain can mitigate corruption, streamline public procurement, and improve citizen trust in digital governance. However, challenges such as scalability, interoperability, legal compliance, and data privacy concerns must be addressed to ensure sustainable adoption. Empirical findings from pilot initiatives suggest that blockchain enhances process integrity, transaction traceability, and interdepartmental collaboration, while startup-driven innovation accelerates agile prototyping and deployment.
Abdelraouf Ishtaiwi, Amjad Aldweesh, Ahmad Al–Qerem, Mouhammd Alkasassbeh
Societies worldwide are reshaping their energy infrastructures to address evolving sustainability targets, economic requirements, and regulatory goals. In this chapter, I examine how artificial intelligence (AI) and blockchain-enabled smart contracts can unify in hybrid intelligence systems to optimize energy grids. This exploration highlights key concepts of distributed ledger technology, AI-driven algorithms, and decision-making processes that combine human expertise with machine-driven insights. The emphasis is on theoretical foundations, yet I also integrate practical viewpoints and selected real-world scenarios to connect these innovations with tangible energy challenges. By bridging smart contracts and AI, the proposed model aims to advance cost-efficient management of grids, enhance trust among participants, and improve operational reliability. I propose that hybrid intelligence facilitates balanced data-driven strategies and human input, creating resilient solutions to energy distribution, consumption, and market interaction.