This paper examines how Artificial Intelligence is transforming English Language and Literature education by challenging the dominance of traditional pedagogical methods and introducing innovative approaches to learning, teaching, and research. In this paper, AI’s origins in early computational linguistics and rule-based language systems are first outlined to establish a foundation for today’s range of digital tools. Next, a survey is provided on how AI is presently deployed within the study of English-from smart tutoring and automated feedback to plagiarism checks, text analytics, digital humanities, and AI-assisted literary interpretation. These technologies enhance student engagement, personalize instruction, and refine critical reading and writing while also disrupting the teacher-centered paradigm. The discussion considers where AI will take the future of English education, from adaptive learning platforms, generative AI, and multimodal storytelling, to finally using AI thoughtfully and ethically. Also, concerns are raised with regard to academic integrity, data privacy, bias, and changes to the teacher’s role. Through a critical examination of AI’s changing status, the paper calls for a symmetrical ethical inclusion of artificial intelligence that can enrich English Language and Literature-fuelling creativity, critical thinking, and inclusive learning in our digital era.

The National Education Policy (NEP) 2020 emphasizes comprehensive reforms in teacher education with a focus on competency-based learning, multidisciplinary perspectives, digital integration, and continuous professional development. In this evolving educational landscape, Artificial Intelligence (AI) offers significant potential to support pedagogical transformation and institutional change in teacher education. This paper explores how AI-enabled practices can contribute to aligning teacher education reforms with the vision and objectives of NEP 2020. The study examines key applications of AI in personalized learning, intelligent lesson planning, adaptive assessment and feedback, virtual teaching simulations, and data-driven professional development for both pre-service and in-service teachers. AI tools are shown to facilitate reflective teaching, inclusive pedagogy, and outcome-based education by addressing diverse learner needs and enhancing instructional effectiveness. At the same time, the paper critically discusses challenges related to ethical concerns, data privacy, digital divide, and the preparedness of teacher educators to meaningfully integrate AI technologies. The paper argues that responsible and strategic integration of AI can act as a catalyst for pedagogical innovation and quality enhancement in teacher education. Aligning AI-enabled practices with NEP 2020 has the potential to strengthen teacher preparation programs and better equip future teachers for the demands of 21st-century classrooms.

Predicting student academic performance has long been a critical concern in education, as early identification of at-risk students enables timely interventions and improved learning outcomes. With the increasing availability of educational data and advancements in artificial intelligence (AI), data-driven student performance prediction has become both feasible and impactful. AI-based prediction models utilize machine learning, deep learning, and learning analytics to analyse academic, behavioural, and demographic data for forecasting student success. This paper presents a comprehensive review of AI-based student performance prediction systems, discussing underlying techniques, system architectures, applications, challenges, and ethical considerations. The study highlights the effectiveness of AI models in enhancing academic decision-making while emphasizing the importance of fairness, transparency, and privacy. Future research directions are proposed to improve accuracy, interpretability, and responsible deployment in educational contexts.

This paper explores the transformative potential of technology-enabled systems, particularly those integrating artificial intelligence (AI) and blockchain, in revolutionizing teacher education and professional development. It addresses the limitations of traditional models and highlights the benefits of AI-driven analytics, virtual reality, and personalized learning pathways in cultivating technological and pedagogical fluency. The study emphasizes the urgent need for expanded frameworks prioritizing AI literacy training, enabling teachers to leverage tools effectively and ethically. It introduces the 'Enabled System,' a conceptual framework that positions teacher education as a dynamic, AI-enhanced ecosystem fostering collaborative reflection and dialogic knowledge creation. The paper discusses the system's role in enhancing content knowledge, its perceived usability and effectiveness, and the challenges and limitations in its implementation. It also provides recommendations for practice and policy, advocating for structured training on ethical and pedagogical AI use, certification standards for AI literacy, and collaborations between educators and AI experts. The conclusion underscores the importance of evidence-based refinements and longitudinal studies to ensure the scalability and efficacy of AI-enabled professional development models, ultimately cultivating a legacy of responsible innovation that bridges technological advancement with humanistic educational values.

We are living in an era characterized by rapid technological advancement. The time when most activities were performed manually has passed, as technology now plays a significant role in everyday life. One of the most influential technologies shaping modern society is Artificial Intelligence (AI). AI has seamlessly integrated into daily activities and is continuously transforming the way people work and interact, often without users realizing its presence. Its applications are evident in-home automation systems, self-driving vehicles, smartphone applications, wearable devices, and many other areas. Wherever it is applied, AI brings significant transformation, making it one of the most progressive technologies witnessed in the contemporary world. Similarly, the e-commerce industry has revolutionized the way business is conducted in India. India has emerged as one of the fastest-growing e-commerce markets globally and is expected to expand at an even faster pace in the coming years. The integration of AI into e-commerce has further accelerated this transformation. AI now plays a crucial role in the e-commerce sector, marking a major technological shift over the past decade. E-commerce platforms increasingly rely on AI to manage large volumes of customer data, interact with consumers through chatbots, and enhance product search, sorting, and recommendation processes. AI enables efficient data capture, processing, and analysis at scale, offering greater accuracy and operational efficiency. Moreover, e-commerce companies are leveraging AI to develop customer-centric search systems, retarget potential buyers, optimize sales processes, enable voice-based search, enhance personalized recommendations, and detect and manage fake reviews. The proposed paper aims to examine the application of AI in the e-commerce industry and analyze its impact on e-commerce portals.

Artificial Intelligence (AI) is rapidly transforming the landscape of academic research by enabling advanced data analysis, accelerating innovation, and facilitating new pathways for knowledge discovery. In contemporary higher education, AI-driven tools are reshaping research design, literature review, data interpretation, and scholarly communication. This paper examines the role of AI in enhancing research efficiency, fostering interdisciplinary innovation, and supporting evidence-based knowledge creation. Anchored in recent scholarly literature and aligned with the vision of NEP 2020, the study highlights how AI contributes to predictive analytics, pattern recognition, and intelligent decision-making in educational research. At the same time, the paper critically addresses emerging challenges related to research ethics, data integrity, algorithmic bias, and academic responsibility. The paper concludes by emphasizing the need for capacity building, ethical frameworks, and institutional readiness to harness AI for sustainable and inclusive research advancement.

The swift progress of AI (Artificial Intelligence) in recent times has led to copious inventive applications in science. AI's capacity to analyse vast datasets, detect patterns, and generate predictions has significantly accelerated scientific research and discovery. AI is a powerful enabler that is reshaping the way scientists work, collaborate, and innovate, creating a more dynamic, responsive, and interconnected research ecosystem. The future of science hinges on the powerful synergy between human creativity and artificial intelligence, where AI serves as a visionary partner that amplifies human ingenuity, sparks new discoveries, and unlocks unprecedented potential. This paper examines key applications, case studies, challenges, and future directions, drawing on recent advancements to illustrate AI's transformative role. While AI boosts efficiency across disciplines, ethical issues like bias and accountability must be tackled to enable its responsible adoption. This paper also discusses the intersection of AI and scientific discovery, acknowledging the predominant focus on data-driven techniques in modern AI for science research.

Artificial Intelligence (AI) is transforming labor markets globally by redefining skill requirements, occupational structures, and employability standards. In India, where demographic advantage intersects with rapid digital expansion, AI adoption is reshaping workforce readiness across sectors such as information technology, banking, healthcare, manufacturing, and education. According to the India Skills Report (2026), national employability has risen to 56.35%, with more than 40% of the IT and gig workforce using AI tools, reflecting accelerated digital integration. Government initiatives including FutureSkills PRIME, Skill India Digital, and reforms under the National Education Policy (2020) aim to institutionalize AI literacy from school to professional levels. However, disparities in AI adoption, infrastructure gaps, and skill mismatches persist. This study analyzes secondary data, policy frameworks, and Indian case examples to evaluate AI’s role in future job readiness. It concludes that systematic reskilling, industry–academia collaboration, and inclusive AI governance are essential to harness India’s demographic dividend in the AI-driven global economy.

Artificial Intelligence (AI) is fundamentally transforming global workforce landscapes, creating both disruption and unprecedented opportunities. This research examines AI's dual role as driver of workforce transformation and solution for preparing workers to thrive in AI-enabled economies. Analysis reveals that nearly half of workers' core skills will be disrupted by 2027, yet AI-powered personalized learning can accelerate reskilling at unprecedented scale[1][2]. We examine critical skills for 2026—including AI literacy, data analytics, and adaptive learning—while exploring how organizations can leverage AI-driven learning systems, microlearning platforms, and intelligent skill gap analysis[3][4]. Policy frameworks from India's AI Talent Mission and World Economic Forum initiatives provide implementation roadmaps[5][6]. Achieving workforce readiness requires coordinated investment in AI-powered education infrastructure, continuous learning ecosystems, equitable access, and collaborative partnerships. Strategic integration of AI into skill development, while maintaining human-centered approaches, enables adaptive, resilient workforces prepared for future digital economies.

The rapid evolution of generative Artificial Intelligence has significantly transformed pedagogical practices, particularly in lesson planning and instructional strategy design. This paper explores the integration of generative AI tools such as large language models and AI-driven content generation platforms into contemporary teaching frameworks. The study examines how generative AI supports educators in designing structured lesson plans, creating differentiated instructional materials, developing formative assessments, and enhancing student engagement through personalized learning pathways. The research paper analyzes opportunities including time efficiency, curriculum alignment, adaptive content generation, multilingual support, and data-informed instructional decisions. It further discusses pedagogical transformation from teacher-centered approaches to AI-assisted collaborative learning environments. However, the integration of generative AI also presents challenges such as ethical concerns, data privacy risks, over-dependence on automation, and the need for teacher digital competence. Using conceptual analysis and emerging classroom case insights, the study proposes a balanced AI-integrated lesson planning framework that maintains teacher agency while leveraging AI capabilities. The paper concludes by outlining future pathways, including AI literacy training & strategies for educators, policy development, responsible AI governance in education, and hybrid human-AI pedagogical models. The findings suggest that generative AI, when used responsibly and strategically, can enhance instructional design, foster creativity, and contribute to more inclusive and adaptive educational ecosystems.

Artificial intelligence (AI) is increasingly transforming educational systems worldwide, influencing not only student learning but also teacher education and professional development (PD). This study explores the integration of AI-enabled systems in teacher professional learning and examines their impact on instructional improvement, reflective practice, and collaborative engagement. Using a qualitative research design, data were collected from 25 educators across primary, secondary, and higher education institutions who actively used AI-powered professional development platforms. Findings indicate that AI systems enhance personalized learning pathways, provide real-time feedback, strengthen data-driven decision-making, and promote professional collaboration. However, concerns related to data privacy, ethical governance, digital literacy, and infrastructure inequities present challenges to effective implementation. The study recommends the development of ethical AI policies, structured digital competency training, equitable infrastructure investment, and blended human–AI PD frameworks. The research contributes to emerging scholarship on AI in teacher education and offers practical implications for policymakers, teacher educators, and institutional leaders aiming to create sustainable and inclusive professional development ecosystems.

As green finance becomes more popular around the world, concerns are growing about companies making false claims about their environmental practices—commonly known as greenwashing. This study explores how “Artificial Intelligence” (AI) can help detect and prevent such dishonest behavior in green banking and finance. As sustainable finance gains momentum globally, concerns over greenwashing and fraudulent “Environmental, Social, and Governance” (ESG) practices have intensified, posing significant risks to the credibility and transparency of green banking. This study investigates the pivotal role of “Artificial Intelligence” (AI) in detecting such fraudulent activities in the context of green finance. By employing a qualitative, case-based research methodology, the paper examines how AI technologies are being leveraged to scrutinize ESG claims, analyze sustainability reports, and identify inconsistencies indicative of greenwashing. The study also explores the synergistic integration of AI with blockchain and predictive analytics to create robust, tamper-resistant systems that ensure the authenticity of green financial transactions. Moreover, it emphasizes the growing relevance of “Explainable AI” (XAI) in fostering stakeholder trust and regulatory compliance. Findings reveal that AI not only enhances fraud detection capabilities in green finance but also promotes accountability, reduces reputational risk, and supports long-term sustainable development goals. The research concludes that AI is a transformative enabler of integrity in sustainable finance, essential for navigating the complexities of ESG verification in an era of heightened environmental scrutiny.

Artificial Intelligence (AI) is increasingly reshaping educational practices and redefining instructional roles within academic libraries. This paper examines the integration of AI in information literacy instruction, a core responsibility of libraries in supporting critical thinking, ethical information use, and lifelong learning. As digital information environments grow more complex, AI-driven tools are being adopted to enhance the effectiveness, accessibility, and personalization of information literacy education. The paper explores the use of AI technologies such as conversational chatbots, intelligent tutoring systems, adaptive learning platforms, and recommender systems in delivering information literacy instruction. These tools enable personalized learning pathways, real-time instructional support, and continuous learner engagement beyond traditional classroom settings. AI-based systems also assist librarians in curriculum integration, assessment of learning outcomes, and identification of students’ information-seeking challenges. Despite these opportunities, the adoption of AI in library instruction raises important challenges related to data privacy, algorithmic bias, transparency, and the potential over-reliance on automated guidance. The evolving pedagogical role of librarians and the need for AI-related competencies are highlighted as critical considerations. Adopting a conceptual and analytical approach, this paper emphasizes the importance of responsible and ethical AI integration and positions academic libraries as key contributors to information-literate and digitally competent learners in AI-driven educational environments.

Artificial Intelligence (AI) is transforming education by enhancing teaching effectiveness, student engagement, and learning outcomes. In health sciences education, including physiotherapy and rehabilitation sciences, AI-enabled tools support lesson planning, personalized learning, assessment, and skill development. This paper explores the ethical, safe, and fair use of AI in teaching and learning processes. It highlights how AI tools assist educators in developing interactive content, generating case-based learning scenarios, and providing timely feedback to students. The integration of AI also supports competency-based education aligned with NEP 2020 by promoting critical thinking, clinical reasoning, and digital literacy. Additionally, AI-driven systems can help identify learning gaps and support student well-being through adaptive learning strategies. Despite these benefits, responsible use, data privacy, and academic integrity must be ensured. The paper concludes that ethical integration of AI can enhance educational quality while preparing students for future healthcare practice.

Stress is a natural response to changes in life but Workplace stress has emerged as one of the most critical challenges in contemporary organizations. Rapid digital transformation, competitive performance expectations, hybrid work structures, and constant connectivity have significantly intensified psychological pressure among employees. Artificial Intelligence (AI) is increasingly being adopted as a strategic tool to detect, monitor, and manage workplace stress. This research paper provides a comprehensive analysis of AI-driven stress management systems, including predictive analytics, AI chatbots, workload optimization algorithms, and personalized wellness platforms. Using hypothetical survey-based organizational data, the study evaluates measurable outcomes such as stress reduction percentages and employee satisfaction improvements. The findings suggest that AI, when implemented ethically and responsibly, significantly enhances employee well-being while improving productivity and organizational sustainability. However, concerns related to data privacy, algorithmic bias, and over-surveillance require strong governance frameworks. The paper concludes by recommending a hybrid human-AI model for effective stress management in modern enterprises.

Over the past few years, Artificial Intelligence (AI) has made deep inroads into education, and one of its most hopeful applications is in the area of student mental health. This is especially relevant in India, where millions of students struggle silently with academic pressure, anxiety, and depression, often without any meaningful support. Indian universities and colleges are grappling with a rising tide of psychological distress among students, made worse by social stigma, a shortage of trained counsellors, and uneven access to mental health services. This paper looks at how AI tools—such as chatbots, sentiment analysis systems, predictive analytics, and wellness apps—can offer practical, scalable help to students who need it. Drawing on published research, real-world case studies, and policy discussions, the study explores how AI-based interventions have been used across Indian institutions to catch early signs of distress, offer timely emotional support, and connect students with professional help. It also takes a critical look at serious concerns around privacy, bias in algorithms, unequal digital access, and the need for strong ethical guidelines. The overall finding is that AI holds real promise for narrowing the mental health gap in Indian higher education—but only if these tools are designed with cultural awareness, built for multiple languages, and governed responsibly.

Artificial Intelligence (AI) is changing education by making learning more personalized and effective. AI tools like smart tutoring systems, automatic grading and data-based analysis help teachers plan better lessons and help students learn according to their needs. These developments create many opportunities to improve student engagement and learning results. However, along with these benefits, some serious ethical challenges also come. Issues like student data privacy, bias in AI systems, lack of transparency, accountability and digital inequality create concerns about fairness and safety. If proper rules and safeguards are not followed, AI systems may increase social differences and put students’ personal information at risk. This paper studies AI in education by looking at its opportunities, challenges and future pathways, with special focus on ethical, safe and fair use. Based on recent international research and policies, the study explains the importance of human-centered AI design, clear rules and regulations and proper ethical guidelines. It also highlights the need for teacher training, AI awareness and regular monitoring of AI systems to maintain transparency and responsibility. The paper concludes that responsible and inclusive use of AI can positively change education if strong ethical standards and fair policies guide its use. A balanced and regulated approach is necessary to build trustworthy AI systems that support quality education for everyone.

The use of Artificial Intelligence (AI) in academic research is rapidly transforming the landscape of knowledge generation, data analysis, and scholarly communication in India and across the globe. AI-powered tools assist researchers in conducting systematic literature reviews, managing large datasets, performing advanced statistical analyses, and generating predictive models with improved speed and accuracy. Machine learning algorithms and natural language processing technologies enable the identification of patterns, trends, and relationships that may not be easily detected through traditional methods. AI enhances research productivity by automating repetitive tasks such as data coding and citation management. Despite these advantages, the integration of AI in research raises important concerns related to data privacy, algorithmic bias, transparency, authorship, and academic integrity. Responsible use and clear ethical guidelines are essential to maintain credibility and accountability in scholarly work. This paper provides a comprehensive review of AI's role in academic research with a particular focus on the Indian higher education context, aligned with the National Education Policy (NEP) 2020.

Artificial Intelligence (AI) is rapidly transforming the landscape of academic and scientific research by enhancing efficiency, accuracy, and innovation across disciplines. From automated literature reviews and data mining to predictive modelling and advanced analytics, AI-driven tools are reshaping research methodologies and accelerating knowledge production. These technologies enable researchers to handle large datasets, identify complex patterns, and generate insights that were previously difficult to obtain. However, the integration of AI in research also presents significant challenges, including issues of algorithmic bias, data privacy, transparency, intellectual property, and academic integrity. Ethical concerns surrounding authorship, accountability, and over-reliance on automated systems require careful governance and regulatory frameworks. This paper critically examines the opportunities AI offers for improving research productivity and interdisciplinary collaboration while highlighting the limitations and ethical dilemmas that accompany its adoption. It argues for a balanced, responsible, and policy-guided approach to ensure that AI strengthens, rather than compromises, the integrity and credibility of research.

Artificial Intelligence (AI) is reshaping educational landscapes worldwide, and financial education is among the sectors undergoing profound transformation. This paper examines the role of AI technologies in enhancing financial literacy, accessibility, personalization, and practical learning. Drawing on literature from educational technology, data analytics, behavioural finance, and AI pedagogy, we identify opportunities, challenges, ethical considerations, and future research pathways. We argue that while AI presents significant benefits for learners and educators, careful design, privacy safeguards, and equitable access are critical for long-term success.

Generative AI is transforming lesson planning and teaching strategies by enabling educators to design more personalized, efficient, and innovative learning experiences. AI-powered tools assist teachers in creating structured lesson plans, generating learning objectives aligned with curriculum standards, and developing diverse instructional materials such as quizzes, case studies, and interactive activities. By analyzing student performance data, generative AI supports differentiated instruction, allowing teachers to tailor content to varied learning styles and abilities. It also facilitates real-time feedback, adaptive assessments, and the integration of multimedia resources to enhance student engagement. Furthermore, AI encourages creative pedagogy by suggesting collaborative tasks, problem-based learning scenarios, and interdisciplinary approaches. While generative AI improves efficiency and instructional quality, its responsible use requires digital literacy, ethical awareness, and human oversight to ensure accuracy and inclusivity. Ultimately, generative AI serves as a supportive partner, empowering educators to focus more on mentorship, critical thinking development, and meaningful classroom interaction.

The rapid integration of Artificial Intelligence (AI) into education has generated an urgent need for structured competency frameworks guiding ethical adoption, pedagogical transformation and governance alignment. However, comparative global analysis of AI competency frameworks remains limited. This study conducts a systematic comparative policy review of six major AI competency frameworks developed by UNESCO, OECD-European Commission, the European Digital Education Hub, India and Lebanon. Using a structured screening and analytical comparison approach (PRISMA-informed document analysis), frameworks were examined across competency domains, progression levels, ethical orientation, governance emphasis, technical depth and implementation strategies. Findings reveal strong convergence around AI literacy, human-centered ethics, pedagogical integration and professional development. Divergences emerge in regulatory embedding, governance centrality and technical specialization. The study identifies critical gaps in empirical validation, assessment design, contextual adaptation and measurable proficiency benchmarks. The findings contribute to AI education policy scholarship by proposing a structured comparative model for evaluating AI competency frameworks and offering implications for global AI literacy governance.

The integration of artificial intelligence (AI) into special education practice presents unprecedented opportunities and challenges for educators responsible for developing Individualized Education Programs (IEPs) and Behavior Intervention Plans (BIPs). This theoretical paper introduces a comprehensive, multidimensional framework for understanding special educator readiness to implement AI-generated educational plans. Drawing on Theory of Planned Behaviour, Social Cognitive Theory, and Technology Readiness Theory, the model integrates four hierarchical levels: (1) Individual-level factors including knowledge, self-efficacy across three domains, attitudes, and professional judgment; (2) Organizational factors encompassing institutional support, culture, and leadership; (3) Systemic factors including policy frameworks, professional standards, and legal requirements; and (4) Implementation quality outcomes with continuous feedback loops. The framework advances beyond technical competence models by positioning professional judgment and ethical orientation as central dimensions, acknowledging that effective AI implementation requires sophisticated integration of technical knowledge with pedagogical expertise and ethical decision-making. Eight distinct educator readiness profiles are identified, each requiring differentiated professional development approaches. The model provides practical applications for professional development design, organizational implementation planning, and policy development. This framework contributes to educational technology theory by offering a context-specific, values-aligned model that honors the complexity of special education practice while embracing technological innovation.

This paper examines the ethical, safe, and responsible use of Artificial Intelligence in education with specific focus on inclusive education and teacher education. AI presents significant opportunities for supporting diverse learners through personalized instruction, assistive technologies, and adaptive assessment practices. However, its use also introduces challenges such as data privacy risks, algorithmic bias, unequal access, and limited teacher preparedness. Using a conceptual and analytical approach, the study reviews existing literature, policy perspectives, and emerging classroom practices to highlight the central role of teachers in ensuring fair and human-centered AI integration. It emphasizes teacher AI literacy, professional ethics, and informed decision-making as essential for safeguarding learner rights. The paper further outlines future pathways that include inclusive AI design, continuous teacher capacity building, and ethical governance frameworks. By integrating inclusion and teacher responsibility, the study argues that AI can reimaging education only when guided by equity, safety, and pedagogical values globally today.

Artificial Intelligence (AI) is reshaping higher education not merely as a technological innovation but as a structural force influencing pedagogical design, institutional governance, strategic positioning, and epistemic practices. While prior scholarship has examined discrete applications of AI—such as intelligent tutoring systems, learning analytics, or automated assessment—there remains limited integrative analysis that synthesizes pedagogical, managerial, and ethical dimensions within a unified theoretical framework. Addressing this gap, the present systematic review advances a multi-level conceptualization of AI integration in higher education institutions (HEIs), positioning AI adoption as an organizational capability transformation embedded within socio-technical systems. Drawing upon interdisciplinary theories including Diffusion of Innovations (Rogers, 2003), Technology Acceptance Model (Davis, 1989), Resource-Based View (Barney, 1991), Dynamic Capabilities (Teece et al., 1997), Constructivism (Piaget, 1970; Vygotsky, 1978), and Human Capital Theory (Becker, 1964), the study develops a theoretically grounded analytical framework. Using a PRISMA-guided systematic review of peer-reviewed literature (2015–2025) from Scopus, Web of Science, ERIC, and UGC-CARE databases, 74 high-quality studies were synthesized to examine AI’s pedagogical impact, institutional transformation effects, and governance implications across global and Indian contexts. The findings indicate that AI enhances personalization, operational efficiency, and data-driven decision-making; however, its transformative potential is contingent upon institutional readiness, faculty digital competencies, ethical safeguards, and infrastructural equity. The analysis reveals persistent research fragmentation, underrepresentation of Global South perspectives, and insufficient longitudinal assessment of AI’s long-term academic and labor market effects. The study contributes theoretically by proposing a three-tier AI Integration Model (pedagogical–institutional–governance alignment) and offers managerial and policy pathways for responsible, sustainable, and equity-oriented AI implementation. AI’s future in higher education depends less on technological sophistication and more on strategic stewardship, ethical governance, and adaptive institutional capability.

The integration of financial management and Human Resource Management has emerged as a critical pathway for business growth and tactical decision-making. Driven by rapid development in Artificial Intelligence (AI), Organizations can significantly reduce operating cost/expenses and increase cost effectiveness through automated processes in all the HR functions as Talent acquisition, Training & Development, performance management, etc. This study investigates the relationship between financial implications of Artificial Intelligence in Human Resource Management. This systematic review explores the impact of AI technology in the transformation of HRM into strategic role in cost efficiency, budget allocation in operation and decision-making. It will also focus on the economies resulting from data analysis and decision-making, as well as problems encountered in this technology. Research results have shown that AI maximizes efficiency in HR activities by streamlining repetitive tasks, thereby reducing operational costs substantially. Predictive models have also allowed technology driven decision-making. Consequently, there has been effective synchronization of human capital with financial outcomes. Nonetheless, the sustainability of AI strategy in human capital development has posed some risks that need to be effectively mitigated. In the summing up, integration needs to be balanced, so that long-term organizational viability is assured as well as the ability to bargain the best way through the intricacies of the contemporary digital economy.

Artificial Intelligence (AI) is increasingly influencing educational practices worldwide, leading institutions to reconsider how teachers are prepared and supported in their professional roles. Traditional professional development models, often limited to periodic workshops and general digital training, do not adequately address the demands of AI-enabled classrooms. This paper examines how AI can enhance teacher professional development by enabling personalized learning pathways, strengthening instructional design, and supporting data-informed decision-making. It also analyses key ethical concerns associated with AI integration, including data privacy, algorithmic bias, teacher autonomy, and equitable access to technology. Drawing on international perspectives, particularly UNESCO’s ethical AI framework and India’s National Education Policy 2020, the study proposes a human-centered approach to integrating AI in teacher education. The paper argues that AI can support meaningful professional growth when implemented responsibly, with strong ethical safeguards and sustained institutional commitment.

The rapid development of Artificial Intelligence (AI) is reshaping education, presenting both opportunities and challenges for teachers. AI tools personalizing teaching, analyze student performance, streamline assessment, making instruction more effective and engaging. Data-driven approaches help teachers better understand students’ individual needs. However, significant challenges remain, including a lack of technical training, limited resources, digital inequality, data privacy, and ethical issues. Striking a balance between technological innovation and human sensitivity is crucial to avoid overreliance on technology. This research paper examines these opportunities and challenges through teacher experiences and educational data, emphasizing the importance of teacher training, responsible AI use and, teacher-centered integration. The study argues that AI should complement, not replace teachers, ultimately enhancing teaching effectiveness.

Artificial Intelligence (AI) is emerging as a transformative force in higher education governance. This study investigates how AI technologies influence financial and administrative decision-making processes and how such integration impacts institutional governance. Through a mixed-method research design involving surveys, interviews, and case studies from multiple institutions, the study examines AI’s role in enhancing transparency, efficiency, accountability, and strategic planning. Findings indicate that AI significantly improves financial forecasting, resource allocation, administrative workflows, and compliance monitoring, thereby strengthening governance structures. However, challenges such as ethical concerns, data privacy, skill gaps, and policy limitations are identified. The research proposes a governance framework that integrates AI capabilities with institutional leadership practices to support evidence-based decision making and sustainable institutional growth.

Artificial Intelligence (AI) is transforming higher education and academic research by reshaping teaching practices, learning processes, and knowledge production In higher education, Al-driven tools such as adaptive learning systems, intelligent tutoring, and automated assessment enhance instructional efficiency and promote personalized, student-centered learning environments. Al also improves administrative decision-making through data analytics and process automation. In academic research, Al accelerates literature synthesis, large-scale data analysis, and predictive modeling, thereby increasing the speed, scope, and accuracy of scholarly inquiry and supporting interdisciplinary innovation. Despite these benefits, Al integration raises significant concerns, including algorithmic bias, data privacy, academic integrity, and digital inequality. This paper critically examines both the transformative potential and ethical challenges of Al adoption in academia. It argues that effective implementation requires transparent governance, robust regulatory frameworks, and sustained human oversight to ensure that technological advancement aligns with academic values and equity.

The convergence of artificial intelligence (AI) and library science has catalyzed the emergence of a new paradigm: the smart library—a dynamic, data-driven ecosystem capable of adapting to learners' individual needs in real time. This article examines how AI technologies, including machine learning, natural language processing (NLP), intelligent recommendation systems, chatbot-assisted reference services, and adaptive learning platforms, are being integrated into academic and public library infrastructures to support personalized learning. Drawing on peer-reviewed literature, institutional case studies, and emerging theoretical frameworks, the paper argues that smart libraries represent a fundamental transformation in how knowledge is curated, accessed, and pedagogically leveraged within smart education environments. The study explores the technical architecture of AI-enabled library systems, their pedagogical implications, ethical considerations surrounding data privacy and algorithmic bias, and the challenges of implementation across diverse institutional contexts. Findings suggest that while AI-enhanced libraries significantly improve learning outcomes, engagement, and resource discovery efficiency, their success depends on equitable design principles, robust digital infrastructure, and ongoing collaboration between library professionals, educators, and technology developers. The article contributes an integrated conceptual model—the Smart Library Learning Ecosystem (SLLE)—as a framework for understanding and guiding the development of next-generation library services in the context of smart education.

Domestic violence is a term that refers to the unsafe condition of women at home. It is present in almost every society in the world. It is not only a problem of developing countries but very prevalent in the developed countries also. The Protection of Women from Domestic Violence Act, 2005 (PWDV Act) was enacted in India to provide effective legal protection to women who are facing domestic violence and to ensure their right to live in a violence-free environment. The implementation of the Act continues to face numerous challenges, including a lack of awareness, underreporting of cases, delays in relief and inadequate coordination among implementing agencies. Artificial Intelligence has emerged as a powerful tool in governance and public policy implementation. This research paper examines the role of Artificial Intelligence in strengthening the implementation of the PWDV Act, 2005.

This research investigates the influencing determinants of evaluating performance of Readymade Garments Industries such as strategic orientation, digital engagement, and market dynamism. Given the industry's pivotal significance in the national economic landscape and its susceptibility to international competitive dynamics, it is imperative to comprehend how both internal capabilities and external conditions influence organizational performance. The study employed a quantitative research methodology to gather data from 400 participants who held diverse managerial and operational positions within the RMG industry. Statistical findings employing Pearson correlation coefficients along with multiple linear regression showed that the three variables notably and positively impact organizational performance, with strategic orientation recognized as the main predictor. Additionally, digital engagement was determined to be essential for augmenting operational efficiency and responsiveness, while market dynamism highlighted the necessity of adaptability in unpredictable contexts. These findings enrich the strategic management literature about emerging markets and provide practical recommendations for business leaders and policymakers striving to enhance competitiveness, sustainability, and resilience within Bangladesh’s garment sector.

Artificial Intelligence (AI) in today's world has become a very powerful tool because it has the ability to understand, verify and examine a large amount of data and based on this it can make predictions and accomplish works that would require a long time for humans to finish. AI devices and supercomputers are great additions to these tools as they help teachers to use a wide range of teaching ideas, individualize learning for every student, and especially change some recurring activities that teachers must do constantly. Instructors must command AI awareness, new usage possibilities and assessments to get the most out of this intelligent resource. Such a design should not only be dedicated to technology skills, but a wide scope of purposes, whose impact on education should be emphasized accordingly. Educators ought to understand the AI ability, find new conduit to apply this technology into the teaching process, and think about ways for teachers to do tasks respectively to give AI directions. Objective of this paper to discuss the contribution of machine learning in assisting and significant impact in teacher education and professional development for teachers and will also advise its prospects of giving more qualified teaching aids and aid continuous learning.

Education performs a progressive role in framing overall societal upliftment, establishing holistic growth and enhancing economic prosperity of the nation. The NEP 2020 (National education policy) reflects a systematic changes oriented toward ensuring higher excellence, equal opportunities, policy responsiveness and global level competitiveness in the educational structure of India. Consistent with the targets of NEP 2020, SDG-4 (quality education) focus on student achievement-oriented learning, diverse disciplinary learning approach, digital transformation strategies and equal access to opportunities for all in learning. On the other side even with holistic policy formulation, the learning ecosystem still deal with obstacles for instance, improper execution, scarcity of skilled staff, resource deficit and unbalanced administrative frameworks. These shortcomings restrict the working performance of institutions and constraint advancement towards balanced and well-rounded education. The study explores regulatory frameworks, educational governance systems and execution strategies that determines the performance of country’s education system. It examines how, policymakers, government agencies, transparency and accountability frameworks, governance structure of institutions affect the outcomes of academic quality standards and universal access. The study helps in comprehensive understanding of how country can improve its education environment and step nearer to fulfilling national objectives as well as global learning standards.

Equitable access to quality education remains one of the most pressing challenges in contemporary global society, directly impacting sustainable development and social justice. This research paper examines the multifaceted barriers preventing equitable educational access and explores evidence-based interventions to promote inclusive learning opportunities for all students. Through comprehensive analysis of funding disparities, digital divides, systemic inequities, and policy frameworks, this study reveals that educational equity requires more than equal treatment—it demands differentiated support tailored to individual student needs. The findings demonstrate that funding inequities, technological gaps, teacher quality disparities, and socioeconomic factors create persistent achievement gaps across different student populations [1][2]. This paper analyzes international policy frameworks including UNESCO's Education for All initiative and the United Nations Sustainable Development Goal 4, while examining practical solutions such as needs-based funding reforms, teacher professional development programs, and technology integration strategies[3][4]. The research concludes that achieving educational equity necessitates coordinated action among policymakers, educators, communities, and technology providers to dismantle structural barriers and create truly inclusive learning environments. By prioritizing equity-focused reforms and resource redistribution, education systems can fulfill their transformative potential to reduce inequality and foster sustainable economic growth for all learners, regardless of their background, location, or circumstances.

The growing skills gap between higher education outcomes and labour market demands has intensified the need for innovative approaches to prepare students for future employment. Artificial Intelligence (AI) has emerged as a transformative tool in enhancing skill development and improving job readiness through personalized learning pathways, adaptive training systems, virtual simulations, and data-driven career guidance. This paper examines key AI applications that support both technical and soft skill development in higher education and explores their role in aligning academic learning with evolving workforce requirements. Drawing on case examples from Indian universities and leading international institutions, the study highlights effective AI-driven practices that enhance employability and workforce preparedness. The paper further discusses how successful global models can be adapted within the Indian higher education context to address large-scale skill gaps, promote inclusive learning, and strengthen industry–academia linkages. By synthesizing current applications and practical experiences, this study underscores the potential of AI to transform higher education into a more responsive and future-oriented system capable of producing skilled, job-ready graduates.

Advancements in Artificial Intelligence (AI) are reshaping inclusive and special education by providing personalized, adaptive, and scalable solutions for diverse learning needs. AI-driven technologies such as speech-to-text systems, language processing tools, computer vision, and predictive analytics support learners with disabilities by enhancing accessibility, engagement, and individualized instruction. This paper examines how AI tools assist in identifying learning challenges, customizing educational content, supporting communication for students with hearing or visual impairments, and offering data-driven insights for educators and specialists. It also discusses teacher preparation, ethical considerations, and the potential digital divide among learners. Findings suggest that, when carefully implemented with inclusive design principles and stakeholder collaboration, AI-enhanced practices can improve learning outcomes, promote autonomy, and foster equitable education opportunities. The paper concludes with recommendations for policy development, teacher training, and future research to harness AI benefits while safeguarding ethical and accessibility standards in inclusive education.

Artificial Intelligence (AI) is reshaping global workforce dynamics by redefining skill requirements and transforming professional training systems. As automation, machine learning, and data-driven technologies become integral to industries, AI-enabled platforms are playing a critical role in developing future-ready competencies. This paper explores how AI supports skill development through personalized learning pathways, intelligent tutoring systems, virtual simulations, and predictive analytics. It highlights the importance of digital literacy, critical thinking, creativity, and socio-emotional skills in preparing individuals for emerging job markets. The study also examines global initiatives promoting AI-based workforce training and lifelong learning. While AI enhances accessibility and efficiency in professional development, concerns regarding job displacement, digital inequality, and ethical implications require strategic policy responses. The paper concludes that AI, when integrated responsibly with education and vocational systems, can significantly strengthen employability, adaptability, and sustainable economic growth in the rapidly evolving digital era.

The rapid integration of Information and Communication Technology (ICT) into educational systems has significantly transformed teaching and learning practices worldwide. The present study investigates the extent and pattern of educational technology usage among senior secondary school teachers. A descriptive survey method was adopted, and a randomly selected sample of 100 teachers participated in the study. Data were collected through a structured questionnaire focusing on the use of smart boards, daily PowerPoint presentations, and teacher-managed YouTube channels. Statistical techniques including percentage analysis, mean, and standard deviation were applied to interpret the data. The findings reveal moderate but uneven adoption of digital tools. Infrastructure-supported technologies such as smart boards show relatively higher usage, while routine digital practices such as daily presentation preparation remain limited. The study emphasizes the need for sustained professional development, institutional encouragement, and policy-level interventions to strengthen effective technology-integrated pedagogy at the senior secondary level.

Artificial Intelligence (AI) has emerged as one of the most influential technologies of the twenty-first century, significantly transforming education, employment, and workforce development. As industries increasingly adopt automation and intelligent systems, the demand for new skills and competencies continues to rise. This research paper examines the role of AI in skill development and its importance in preparing individuals for future job readiness. The study discusses how AI supports personalized learning, lifelong skill acquisition, and career adaptability while also addressing challenges such as job displacement, ethical concerns, and the digital divide. The paper emphasizes the need for balanced human–AI collaboration, inclusive education policies, and continuous up skilling to ensure sustainable employment in a rapidly changing world.

ਆਧੁਨਿਕ ਡਿਜ਼ਿਟਲ ਯੁੱਗ ਵਿੱਚ ਕ੍ਰਿਤ੍ਰਿਮ ਬੁੱਧੀ (Artificial Intelligence) ਸਿੱਖਿਆ ਦੇ ਖੇਤਰ ਵਿੱਚ ਇਕ ਨਵਾਂ ਮੋੜ ਲੈ ਕੇ ਆਈ ਹੈ। ਭਾਸ਼ਾ ਸਿੱਖਣ ਦੀ ਪ੍ਰਕਿਰਿਆ ਹੁਣ ਪਰੰਪਰਾਗਤ ਕਲਾਸਰੂਮ ਤੱਕ ਸੀਮਿਤ ਨਹੀਂ ਰਹੀ, ਸਗੋਂ ਡਿਜ਼ਿਟਲ ਪਲੇਟਫਾਰਮਾਂ ਅਤੇ AI ਆਧਾਰਿਤ ਐਪਲੀਕੇਸ਼ਨਾਂ ਰਾਹੀਂ ਵਿਅਕਤੀਗਤ ਅਤੇ ਇੰਟਰਐਕਟਿਵ ਬਣ ਗਈ ਹੈ। ਪੰਜਾਬੀ ਭਾਸ਼ਾ ਦੇ ਅਧਿਐਨ, ਸਾਹਿਤਕ ਵਿਸ਼ਲੇਸ਼ਣ ਅਤੇ ਸੰਚਾਰ ਕੌਸ਼ਲਾਂ ਦੇ ਵਿਕਾਸ ਵਿੱਚ AI ਮਹੱਤਵਪੂਰਨ ਭੂਮਿਕਾ ਨਿਭਾ ਰਹੀ ਹੈ।। Duolingo, Google Translate ਅਤੇ OpenAI ਦੁਆਰਾ ਵਿਕਸਿਤ ਵਰਗੇ ਸਾਧਨ ਭਾਸ਼ਾ ਸਿੱਖਣ ਨੂੰ ਆਸਾਨ ਅਤੇ ਰੁਚਿਕਰ ਬਣਾਉਂਦੇ ਹਨ। ਇਹ ਅਧਿਐਨ ਇਸ ਗੱਲ ਦਾ ਵਿਸ਼ਲੇਸ਼ਣ ਕਰਦਾ ਹੈ ਕਿ ਕਿਵੇਂ AI ਤਕਨਾਲੋਜੀ ਪੰਜਾਬੀ ਭਾਸ਼ਾ ਦੇ ਪਾਠਨ, ਲੇਖਨ, ਸੁਣਨ ਅਤੇ ਬੋਲਣ ਦੀਆਂ ਕੌਸ਼ਲਾਂ ਨੂੰ ਵਿਕਸਿਤ ਕਰ ਸਕਦੀ ਹੈ। ਨਾਲ ਹੀ ਇਸ ਵਿੱਚ ਲਾਭ, ਚੁਣੌਤੀਆਂ ਅਤੇ ਭਵਿੱਖੀ ਸੰਭਾਵਨਾਵਾਂ ਦਾ ਵੀ ਅਧਿਐਨ ਕੀਤਾ ਗਿਆ ਹੈ।

The concept of Artificial Intelligence (AI) is fast disrupting assessment practices in education by changing the traditional approaches to measuring students to dynamic, data-driven evaluation ecosystems. In this paper, the author will discuss the role of AI-based evaluation and personal feedback systems in determining the future of assessment by improving accuracy, relevance, and engagement of learners. Standardized test and manually graded systems have been traditionally criticised as being too inflexible, slow to provide feedback, and failing to represent the complex learning patterns of individual students. On the contrary, using machine learning, natural language processing, and predictive analytics, AI systems provide real-time feedback, ongoing assessment, and personalized learning journeys. The ability of AI to extract a large amount of data during educational interactions can enable educators to learn more about the strengths of the learners, their misconceptions, and the emotional interactions they have. However, amid the benefits, which are strong, such as scalability, efficiency and personalization, there are obstacles such as ethical issues of data privacy, algorithmic fairness and the probability that the human judgment in education will be eroded. To develop an equilibrium model that ensures that AI-supported assessment practices do not marginalize human educators, this paper takes a multidisciplinary approach by integrating the pedagogical theory with technological innovation. This study envisions an assessment ecosystem that is both adaptive, equitable, learner-centered and ethically sound through an analysis of the present AI assessment tools, pedagogical implications, case studies, and future trends of AI assessment. Finally, assessment in the future will be in balancing the intelligent systems with human wisdom to increase meaningful feedback and deeper learning among every learner.

Artificial Intelligence (AI) is transforming research processes and accelerating knowledge discovery across disciplines. By leveraging machine learning, natural language processing, and big data analytics, AI enables researchers to analyze vast datasets, identify hidden patterns, generate predictive models, and automate complex tasks. This paper explores the role of AI in enhancing literature review, data mining, hypothesis generation, experimentation, and interdisciplinary collaboration. AI-powered tools facilitate faster decision-making, reduce human error, and support innovative breakthroughs in fields such as healthcare, education, environmental science, and social research. While AI enhances efficiency and creativity in research, challenges related to data ethics, algorithmic bias, transparency, and intellectual ownership require careful consideration. The study concludes that AI, when integrated responsibly with human expertise, has the potential to revolutionize research methodologies, foster innovation ecosystems, and significantly expand the boundaries of global knowledge production in the digital age.

The rapid integration of Artificial Intelligence (AI) in education has transformed teaching, learning, assessment, and administration. However, its widespread adoption raises significant ethical, safety, and fairness concerns. This paper examines the principles guiding the responsible use of AI in educational settings, focusing on data privacy, transparency, accountability, inclusivity, and bias mitigation. It explores international policy frameworks and regulatory guidelines that promote human-centered AI systems while protecting learners’ rights. The study highlights potential risks such as algorithmic discrimination, surveillance concerns, academic integrity issues, and unequal access to digital resources. By emphasizing ethical design, stakeholder participation, and regulatory oversight, the paper argues that AI can enhance educational outcomes without compromising equity and safety. The paper concludes that ensuring ethical, safe, and fair AI implementation requires collaborative efforts among educators, policymakers, technologists, and institutions to create trustworthy and inclusive digital learning environments.

The National Education Policy 2020 (NEP 2020) represents a comprehensive reform aimed at improving equity, quality, affordability, and accountability in India’s education system. Simultaneously, Artificial Intelligence (AI) has emerged as a transformative force capable of reshaping educational planning, delivery, and governance. This paper examines the role of AI in facilitating the implementation of NEP 2020 with specific reference to the state of India. The study analyses existing and emerging AI-enabled initiatives in India’s school and higher education sectors and evaluates their alignment with the objectives of NEP 2020. It highlights the potential of AI in promoting personalized learning, strengthening assessment mechanisms, enhancing administrative efficiency, and supporting teacher professional development. However, the paper also identifies key challenges in the India context, including infrastructural limitations, rural–urban digital disparities, data privacy concerns, and gaps in teacher readiness. The study offers policy-oriented recommendations emphasizing context-sensitive AI integration, capacity building, and institutional collaboration to ensure inclusive and sustainable educational transformation in India.

Artificial intelligence (AI) hold a significant importance for India across various sectors due to its potential to drive innovation, improve efficiency and address the complex challenges. It is crucial for development of India across various dimensions like economic, social and technological. As India continues to navigate the challenges of the 21" Century, embracing and leveraging Al will be key to unlocking the new opportunities aiming at fostering innovation, and positioning India as a global leader in rapidly evolving landscape of technology & Al. The National Policy of Education (NEP), 2020 has acknowledged the significance and role of disruptive technologies in shaping the landscape of education. In such a technology-driven knowledge environment, it becomes imperative to acquaint oneself with different disruptive technologies like "Artificial Intelligence (AI), Block Chain Technology, Machine Learning and Data Science etc. "The policy emphasizes that India must take a leading role in preparing its professionals in areas like AI. The rapid advancement of artificial intelligence (AI) has permeated various facets of our lives, including education. In the realm of teacher professional development, AI presents both opportunities and challenges. This article delves into the role of AI in supporting teacher training and development programs, exploring how educators can harness AI to enhance teaching practices, improve student outcomes, and optimize administrative processes. As artificial intelligence becomes more common in our daily lives, its effect on education calls for both enthusiasm and caution.Supporters believe that AI offers great opportunities for personalized learning, making administrative tasks easier and bringing new ways to teach. However, there are still worries about privacy, fairness and the possibility of replacing traditional teaching jobs. A study by the Digital Education Council found that 86% of students admit to using AI in their studies. To further that, 24% use it daily and 54% use it weekly.

Artificial Intelligence (AI) is increasingly shaping contemporary education systems, with recent reports indicating that over 60-70% of higher education institutions globally have adopted or are piloting AI enabled tools for teaching, learning or administration. The global AI in education market are projected to surpass 20-25 billion U.S. dollars by 20-30, reflecting rapid growth in adaptive learning platforms, automated assessment systems, and intelligent tutoring applications. Evidence suggests that AI supported personalized learning can improve student engagement by 30-40% and reduce teacher’s administrative workload by nearly 20-30%, enabling educators to focus more on student centered instruction and mentoring. AI driven assistive technologies also enhance accessibility for learners with disabilities and support inclusive education in remote and underserved areas. However, significant challenges reflected. Nearly 35-40% of educational institutions in developing regions report inadequate digital infrastructure, while concerns related to data privacy, algorithmic bias, and ethical governance continue to affect trust in AI adoption. Studies indicate that more than 50% of teachers feel insufficiently trained to effectively integrate AI tools into pedagogy, highlighting the need for professional development and digital literacy initiatives. Future pathways emphasize evidence-based policy making, investment in infrastructure, teacher capacity building and development of ethical AI frameworks to ensure responsible and equitable implementation. By combining technological innovation with human centered educational values, AI has the potential to transform learning ecosystems, enhance academic performance, and prepare learners for the demands of an increasingly digital and knowledge-driven society.

Artificial Intelligence (AI) is no longer a distant technological concept; it has become an integral part of contemporary educational systems worldwide. From adaptive learning platforms and automated grading tools to intelligent tutoring systems and predictive analytics, AI is reshaping the way knowledge is delivered, consumed, and evaluated. These technologies promise more personalized learning experiences, improved efficiency in educational administration, and wider access to knowledge. However, alongside these opportunities, AI introduces a range of ethical, safety, and fairness challenges that cannot be ignored. Issues such as data privacy, algorithmic bias, surveillance, digital inequality, and the erosion of human-centered education demand critical reflection. This research paper examines the ethical, safe, and fair use of AI in education from a human-centered perspective. It argues that while AI can significantly enhance educational outcomes, its use must remain grounded in transparency, accountability, and inclusivity. The study highlights how unequal access to technology may widen educational gaps and how biased algorithms can reinforce existing social inequalities. It further emphasizes the importance of safeguarding student privacy, promoting responsible data governance, and ensuring that educators remain central to the learning process. The paper concludes that ethical AI in education must prioritize human dignity, equity, and social justice, ensuring that technological progress benefits all learners rather than a privileged few.

In today’s time, AI has become very dominant. AI has established its important place in almost every field-where it is education, agriculture, marketing or any other sector. In teacher education AI plays a very significant role. Artificial Intelligence (AI) is transforming teacher education and professional development by introducing very effective learning systems. AI-enabled platforms provide real-time feedback. This paper explores the role of AI in pre-service and in-service teacher education, highlighting its impact on instructional design, reflective practice, and continuous professional growth. It examines global initiatives such as UNESCO frameworks on AI in education and adaptive learning systems used by platforms like Coursera and Google for Education. The study discusses benefits including personalized training pathways, skill gap analysis, and administrative efficiency, while addressing ethical concerns such as data privacy and algorithmic bias. The paper concludes that AI-enabled systems, when implemented responsibly, can significantly strengthen teacher preparation and lifelong professional development in the evolving digital education ecosystem.

कृत्रिम बुद्धिमत्ता (Artificial Intelligence) के तीव्र विकास ने शिक्षा के क्षेत्र में व्यापक परिवर्तन की संभावनाएँ उत्पन्न की हैं। विशेष रूप से जनरेटिव आर्टिफ़िशियल इंटेलिजेंस (Generative AI) ने शिक्षण-अधिगम प्रक्रिया को अधिक प्रभावी, लचीला एवं छात्र-केंद्रित बनाने में महत्वपूर्ण भूमिका निभाई है। वर्तमान शिक्षा प्रणाली में शिक्षकों को पाठ योजना निर्माण, विविध अधिगम स्तरों के अनुरूप शिक्षण रणनीतियाँ विकसित करने, मूल्यांकन प्रक्रिया को सुदृढ़ बनाने तथा समय प्रबंधन जैसी अनेक चुनौतियों का सामना करना पड़ता है। ऐसे में जनरेटिव AI एक सहायक एवं सशक्त उपकरण के रूप में उभरकर सामने आया है। यह शोधपत्र जनरेटिव AI द्वारा सशक्त पाठ योजना एवं शिक्षण रणनीतियों का समग्र विश्लेषण प्रस्तुत करता है। अध्ययन का उद्देश्य यह समझना है कि किस प्रकार AI आधारित उपकरण शिक्षकों को पाठ उद्देश्यों के निर्धारण, शिक्षण सामग्री के सृजन, गतिविधि-आधारित अधिगम, वैयक्तिक शिक्षण तथा सतत मूल्यांकन में सहायता प्रदान करते हैं। जनरेटिव AI शिक्षकों को विभिन्न प्रकार की शिक्षण सामग्री—जैसे कार्यपत्रक, प्रश्नोत्तरी, परियोजना कार्य, केस स्टडी तथा डिजिटल संसाधन—तैयार करने में समर्थ बनाता है, जिससे कक्षा शिक्षण अधिक रोचक और सहभागितापूर्ण हो जाता है। शोधपत्र में यह भी स्पष्ट किया गया है कि जनरेटिव AI शिक्षण रणनीतियों को नवाचारी स्वरूप प्रदान करता है। सहयोगात्मक अधिगम, समस्या-समाधान आधारित शिक्षण, अनुभवात्मक अधिगम तथा मिश्रित शिक्षण (Blended Learning) जैसी विधियों को AI के माध्यम से अधिक प्रभावी ढंग से लागू किया जा सकता है। यह तकनीक विद्यार्थियों की आलोचनात्मक सोच, रचनात्मकता एवं डिजिटल दक्षताओं के विकास में सहायक सिद्ध होती है। राष्ट्रीय शिक्षा नीति 2020 के संदर्भ में जनरेटिव AI का विशेष महत्व है, क्योंकि यह नीति तकनीक-समर्थ, कौशल-आधारित एवं अनुभवात्मक अधिगम पर बल देती है। जनरेटिव AI इन उद्देश्यों की प्राप्ति में एक सशक्त माध्यम बन सकता है, बशर्ते इसका उपयोग संतुलित एवं नैतिक रूप से किया जाए। हालाँकि, जनरेटिव AI के उपयोग से संबंधित कुछ चुनौतियाँ भी सामने आती हैं, जैसे डेटा गोपनीयता, तकनीकी निर्भरता, नैतिकता तथा शिक्षकों में डिजिटल दक्षता का अभाव। शोधपत्र में इन चुनौतियों के समाधान हेतु प्रशिक्षण, नीति-निर्देशों तथा मानव-तकनीक के संतुलित समन्वय पर बल दिया गया है। अतः यह अध्ययन दर्शाता है कि जनरेटिव आर्टिफ़िशियल इंटेलिजेंस शिक्षक सशक्तिकरण का एक प्रभावी साधन है, जो शिक्षण-अधिगम प्रक्रिया को आधुनिक, समावेशी एवं गुणवत्तापूर्ण बना सकता है।

वर्तमान डिजिटल युग में कृत्रिम बुद्धिमत्ता शिक्षा के क्षेत्र में एक महत्वपूर्ण परिवर्तनकारी तकनीक के रूप में उभरकर सामने आई है। शिक्षा में कृत्रिम बुद्धिमत्ता के प्रयोग से पारंपरिक शिक्षण अधिगम प्रक्रिया अधिक प्रभावी, तकनीक-आधारित तथा छात्र-केंद्रित बनती जा रही है। यह तकनीक शिक्षण, अधिगम, मूल्यांकन और शैक्षिक प्रशासनकृसभी स्तरों पर व्यापक प्रभाव डाल रही है। इस शोध पत्र का उद्देश्य शिक्षा में कृत्रिम बुद्धिमत्ता के प्रभाव, उसकी भूमिका, लाभ, नुकसान तथा भविष्य की संभावनाओं का विस्तृत अध्ययन करना है। कृत्रिम बुद्धिमत्ता आधारित तकनीकों जैसे अनुकूली शिक्षण प्रणाली, बुद्धिमान मूल्यांकन प्रणाली, लर्निंग एनालिटिक्स तथा प्रशासनिक स्वचालन ने शिक्षा व्यवस्था को अधिक व्यवस्थित, पारदर्शी और परिणामोन्मुख बनाया है। इन तकनीकों के माध्यम से छात्रों को उनकी क्षमता, रुचि और सीखने की गति के अनुसार शिक्षण सामग्री उपलब्ध कराई जाती है, जिससे अधिगम की गुणवत्ता में उल्लेखनीय सुधार होता है। शिक्षकों के लिए भी कृत्रिम बुद्धिमत्ता सहायक सिद्ध हुई है, क्योंकि इससे मूल्यांकन, रिकॉर्ड संधारण तथा अन्य प्रशासनिक कार्यों का बोझ कम हुआ है। परिणामस्वरूप शिक्षक शिक्षण, मार्गदर्शन और परामर्श पर अधिक ध्यान दे पा रहे हैं। हालाँकि, शिक्षा में कृत्रिम बुद्धिमत्ता के प्रयोग से कुछ चुनौतियाँ भी उत्पन्न हुई हैं, जैसे डेटा गोपनीयता, तकनीकी असमानता, नैतिक प्रश्न तथा छात्रों में तकनीक पर अत्यधिक निर्भरता। यह शोध पत्र माध्यमिक स्रोतों पर आधारित है और यह निष्कर्ष प्रस्तुत करता है कि यदि कृत्रिम बुद्धिमत्ता का उपयोग संतुलित, नैतिक और मानव-केंद्रित दृष्टिकोण से किया जाए, तो यह शिक्षा की गुणवत्ता में सुधार लाने का एक प्रभावी माध्यम बन सकती है।

Context: This research paper adds to existing literature that it is essential to become aware of the cons and pros of AI, before applying it in any field. Artificial intelligence is used in scientific research, social research and education. Stakeholders are generally unaware of the proper applications and limitations of artificial intelligence. AI has advantages like high accuracy, speed and convenience along with drawbacks like intermixing and fabricated content. Objectives: 1. To study the level of artificial intelligence awareness of stakeholders of higher education institutions of Sirsa District. 2. To study the significance of differences in mean scores of artificial intelligence awareness of stakeholders of higher education institutions of Sirsa District based on demographic variables. Methodology: Descriptive research was used as a survey by investigators through a self-developed Google form. A sample of 131 stakeholders was selected through a purposive sampling from Sirsa District of Haryana state. Both qualitative and quantitative data were used in this study. Statistical techniques- p-p plots, K-S test, Shapiro-wilk test, Percentage analysis, Mean, S.D., t- test and ANOVA one-way were applied in this study to compute results. Results: It was found that 25.95% (N = 34), 45.80% (N = 60) and 28.24% (N = 37) stakeholders of higher education institutions of Sirsa District had respectively a below average, average and above average level of artificial intelligence awareness. Qualitative analysis suggested that stakeholders of higher education institutions of Sirsa District had different levels of artificial intelligence awareness that depended on their personal perceptions. The quantitative analysis suggested that there were no significant differences in the artificial intelligence awareness of stakeholders of higher education institutions of Sirsa District based on demographic variables. These results are useful for higher educational institutions to improve artificial intelligence awareness among stakeholders of their institutions.

The rapid evolution of artificial intelligence (AI) and digital transformation is reshaping the global employment landscape, placing unprecedented demand on learners to acquire smart skills that enhance employability. In India, strategic educational reforms — notably the National Education Policy (NEP) 2020 and the Skill India Mission — emphasize integrating skill development, industry engagement, and future job readiness. This paper explores how AI-enabled learning systems can promote smart skills (cognitive, digital, socio-emotional) aligned with India’s education policy goals. It discusses adaptive learning, predictive analytics, virtual simulations, and competency mapping that enhance personalized education and workforce readiness. The study also examines challenges such as infrastructure, ethical AI use and equitable access. Integrating AI with NEP 2020 and Skill India frameworks can bridge the skills gap, foster lifelong learning, and create a future-ready workforce. Strategic policy implementation and stakeholder collaboration are essential to maximize positive outcomes.

The National Education Policy (NEP) 2020 marks a transformative shift in India's educational landscape, emphasizing the integration of technology, particularly Artificial Intelligence (AI), to enhance learning outcomes and bridge educational disparities. This paper explores the opportunities and challenges associated with embedding AI within the NEP 2020 framework, drawing insights from recent literature and studies. While AI offers personalized learning, efficient administrative processes, and improved accessibility, it also presents challenges such as data privacy concerns, infrastructural limitations, and the need for teacher training. A comprehensive understanding of these facets is crucial for the successful implementation of AI in India's education system.

The advent of Artificial Intelligence (AI) has significantly transformed the teaching and learning landscape. AI-powered tools and techniques offer personalized learning experiences, automate routine tasks, and provide new opportunities for enhancing educational outcomes. This paper explores the applications, benefits, challenges, and future prospects of AI in education. Drawing upon recent studies and technological advancements, the paper highlights how AI-driven systems can foster more effective, engaging, and inclusive learning environments.

Shrimp farming is a rapidly expanding component of global aquaculture, contributing significantly to food security, rural livelihoods, and export earnings. However, the sector faces persistent challenges, including water quality fluctuations, disease outbreaks, feed inefficiency, environmental degradation, and market volatility. This study examines the transformative role of Artificial Intelligence (AI) in enhancing productivity, profitability, and sustainability in shrimp farming systems. AI-driven technologies such as machine learning, IoT-based sensors, computer vision, and predictive analytics enable real-time monitoring of water parameters, optimized feeding strategies, early disease detection, biomass estimation, and automated farm management. Comparative analysis indicates substantial improvements in production growth and feed conversion efficiency under AI-integrated systems. Furthermore, AI supports climate-resilient aquaculture through adaptive management and resource optimization. Despite its potential, adoption remains constrained by high investment costs, limited technical expertise, and infrastructural gaps. Overall, AI-based shrimp farming represents a significant shift toward precision and sustainable aquaculture development.

The increasing presence of Artificial Intelligence (AI) in higher education has transformed pedagogical practices in language and literature classrooms. While conceptual scholarship highlights its potential for enhancing interpretation and communication, empirical classroom-based perspectives remain limited. This study integrates theoretical analysis with student perception data to evaluate AI’s role in literary learning. A survey of thirty postgraduate literature students was conducted to examine AI’s impact on interpretation, critical thinking, writing development, classroom participation, and ethical awareness. Findings reveal strong student support for AI as a tool for contextual understanding and vocabulary development, alongside concerns regarding overdependence and originality. The study concludes that AI functions most effectively as a cognitive scaffold within human-guided pedagogy rather than as a replacement for traditional literary engagement.

Parental engagement plays a vital role in enhancing students’ academic performance, motivation, and overall development. With the increasing shift toward digital and home-based learning, especially after the COVID-19 pandemic, parents are required to take a more active role in their children’s education. Artificial Intelligence (AI) has emerged as a powerful tool to support and strengthen parental involvement in home learning environments. This research paper explores how AI-based educational technologies can increase parental engagement by providing personalized learning support, real-time feedback, learning analytics, and collaborative learning opportunities. The study reviews existing literature on AI-mediated family learning, discusses benefits and challenges, and highlights how AI can foster effective parent-child collaboration. The paper concludes that while AI has significant potential to enhance parental engagement, careful implementation, digital literacy, and ethical considerations are essential for successful outcomes.

As higher education institutions prepare students for the workforce, so the emergence of generative AI has caused a major dilemma. In the Present scenario, development of digital skills must become a normative aim in students, while simultaneously preserving academic integrity and credibility. The challenges, which are facing by them, is not simply a matter of using AI responsibly because of typically of reconciling i.e. preparing students for the future of work and maintaining the traditional role of developing personal academic skills. Because of critical thinking, the ability to acquire knowledge and the capacity to produce original work. Objectives must be typically balanced in Higher education institutions while addressing financial considerations, creating value for students and employers, and meeting accreditation requirements. There are multiple-case study of fifty universities across eight countries examined institutional response to generative AI. As proposed actions varied widely, the content analysis revealed apparent confusion and a lack of established best practices, from complete bans on generated content to the development of custom AI assistants for students and faculty. We concluded that timely innovation will be required for the apparent confusion of higher education institutions and suggest every possible approaches to that. However our results will suggest that their top concern now is the potential for irresponsible use of AI by students to cheat on assessments. In the short term and long term, We, therefore, recommend that, the credibility of awards is urgently safeguarded and argue that this could be achieved by ensuring at least some human-proctored assessments are integrated into courses, e.g., in the form of real-location examinations and viva voces.

Artificial intelligence (AI) and drone technologies are driving a significant shift in agriculture. Precision agriculture has become more popular due to the growing need for food worldwide, the effects of climate change, the reduction of productive land, and the requirement for sustainable farming methods. In agricultural systems, real-time monitoring, data-driven decision-making, and optimal resource management are made possible by AI-powered analytics in conjunction with unmanned aerial vehicles (UAVs), commonly known as drones. By enhancing crop productivity, lowering input costs, and minimising environmental effect, this research paper investigates how Artificial Intelligence (AI) and drone technology might support smart and sustainable agriculture.The study investigates applications include crop health monitoring, yield prediction, soil analysis, precision spraying, irrigation management, insect detection, and climate adaption startegies.The challenges it evaluates include high implementation costs, data privacy concerns, technical skill gaps, legislative barriers, and infrastructure limitations, especially in developing countries. AI-integrated drones greatly increase operational efficiency and sustainability parameters, according to case studies and recent technology developments.

Artificial Intelligence is now a potent instrument for transforming the educational system in our digital world. It has significantly influenced teaching methods, learning processes, and professional development practices. The National Education Policy (NEP) 2020 has substantially promoted the integration of technologies like artificial intelligence in order to ameliorate the norms of school teacher According to NEP 2020, this review article examines the effects of artificial intelligence on teacher training and professional growth. It examines how advancements in virtual classrooms, learning analytics, intelligent tutoring systems, adaptive learning platforms, and AI-based technologies have transformed teaching strategies and educational methodologies. The study also shows how AI facilitates personalized knowledge, nonstop evaluation, and the ongoing professional development of preceptors. The research also examines the major advantages, challenges, and constraints of using artificial intelligence in teacher training schools. Topics covered include data security, digital literacy, ethical concerns, resistance to technological progress, and a lack of sufficient technological infrastructure. The review concludes that there's a large eventuality for artificial intelligence to ameliorate school teacher education and professional development programs. Still, careful drug, respectable training, and ethical execution are still necessary for long- continuing and successful issues.

Teacher education in the digital era requires innovative approaches that ensure continuous skill development and instructional effectiveness. AI provides dynamic platforms where teachers can access customized professional development resources, participate in interactive workshops and receive instant feedback on lesson planning and assessment strategies. Such technologies enable educators to engage in self directed learning. Furthermore, AI also supports reflective practice by generating analytics on classroom engagement and student outcomes. In other words, the integration of AI in teacher education not only enhances efficiency but also promotes innovation and sustained professional growth in the 21st century.

The accelerated integration of Artificial Intelligence (AI) into contemporary educational systems has reshaped pedagogical methodologies, institutional governance, and assessment cultures worldwide. While AI-powered adaptive platforms, predictive analytics, generative systems, and automated evaluation tools promise efficiency and personalized learning, their implementation raises urgent ethical concerns related to algorithmic bias, surveillance, accountability, transparency, and psychological well-being. Drawing upon critical theory, the capabilities approach, surveillance studies, democratic theory, and recent global AI regulatory frameworks including the UNESCO 2021 Recommendation on the Ethics of Artificial Intelligence and the 2024 European Union AI Act, this study proposes a comprehensive human-centred governance model for educational AI. It argues that without ethical safeguards, AI risks institutionalizing structural inequalities and weakening human creativity and agency. Responsible AI integration must prioritize fairness auditing, explainability, regulatory oversight, inclusive data practices, and AI literacy to ensure educational justice in digitally mediated learning environment.

Teaching culture in language classes needs a fresh approach. Old methods, like just using textbooks, can't keep up with our fast-changing, connected world, where culture evolves quickly through social media and global conversations. This paper suggests a team-based approach where Artificial Intelligence (AI) helps the human teacher, instead of replacing them. In this team, AI is great at finding real, up-to-date cultural materials and making custom, life-like situations for students to practice in. It can look through huge amounts of information to find current trends, giving students a view into culture as it is right now. The human teacher, however, gives the important social and cultural background that computer programs miss. They carefully lead tricky conversations about difficult subjects, help clear up confusion, and show students how to communicate with understanding. A key job for the teacher is to show students how to question what the AI finds, checking for any unfairness, which builds both digital and cultural smarts. This teamwork creates a major shift in teaching. It moves students from just memorizing cultural facts to actively building real intercultural skills. Learning changes from simply collecting information to a process of thinking deeply about it and reflecting on oneself. Being good with other cultures isn't just about knowing facts; it's about understanding different viewpoints, seeing your own cultural biases, and knowing how to act in different situations. The main goal is to raise students who are not just good speakers, but also thoughtful and caring global citizens. We want to create people who can handle the natural uncertainty of meeting other cultures—to be flexible and think carefully when the rules aren't clear. This education gives them the power to go beyond shallow talk and form real, meaningful bonds. This builds the trust, respect, and teamwork needed to succeed in our more global world. Basically, this model gets students ready not just to speak a language, but to build bridges of understanding between different cultures.

Artificial Intelligence is a one types of machine learning which modified according to mental process as like the Human being. Today this is very importance in this 21st century Modern era. Because Intelligence might be defined as the ability to learn and perform Suitable techniques to solve problems and achieve goals, appropriate to the context in an Uncertain, ever varying world. A fully pre-programmed factory robot is flexible, accurate and Consistent but not intelligent. Autonomous systems can independently plan and decide sequences of steps to achieve a specified goal without micro-management. Human-Centered Artificial Intelligence is AI that seeks to augment the abilities of, address the societal needs and draw inspiration from human beings. It researches and builds effective partners and tools for people, such as a robot helper and companion for the learning in education points of views. When we talk about the importance in education sector, its play different ways as mental, social and technical in the education sector. So researcher, want to know about the importance of AI in education in different way such as technical, social and mental process.

आधुनिक हिंदी साहित्य के क्षेत्र में महिला साहित्यकारों का योगदान महत्वपूर्ण रहा है। इन महिला लेखिकाओं ने अनेक अनछुए पहलुओं को उद्घाटित किया है। नासिरा शर्मा वर्तमान समस्याओं,भाव बोध, परिवेशगत अनुभूति और संवेदना आदि को लेकर साहित्य सृजन करने वाली महत्वपूर्ण लेखिका है। हिंदी, उर्दू, पश्तो, फ़ारसी और अंग्रेजी भाषा की ज्ञाता नासिरा शर्मा का जन्म 22 अगस्त 1948 ई. को इलाहाबाद में पढ़े लिखे परिवार में हुआ। आज के दौर में नासिरा शर्मा ही एक ऐसी प्रचलित लेखिका हुई है जिन्होंने विभिन्न परिवेश के समय और समाज, देश–देशांतर की सामाजिक सोच व ताने बाने को ईमानदारी और प्रामाणिकता से प्रस्तुत किया है। ‘जिंदा मुहावरे’ (1994) उपन्यास 1947 के विभाजन के दंश को पूरी जीवंतता से उद्घाटित करता है। बंटवारा चाहे घर का हो या देश का, सच्चाई यही रही है कि कोई भी खुशी प्राप्त नहीं कर सकता है, उसी तरह जिंदा मुहावरे उपन्यास भी एक घुटन, पीड़ा और दर्द की कहानी को अपने कलेवर में समेटे हुए है। इसमें बंटवारे की कोख से जन्मी एक चीख है,जिसकी अनुगंज आज भी सुनाई देती है।

आज विश्वभर में कृत्रिम बुद्विमता का प्रचार जोर-शोर से श्ुारू हो चुका है। आज के अनुसार भविष्य में इसके द्वारा सारे काम किये जा सकते है जो प्रत्येक मानव आज कर रहा है, इसमे कोई संदेह नही होगा क्योकि जिस प्रकार इसका उपयोग तेजी से विभिन्न क्षेत्रों में हो रहा है, चाहे वो शिक्षा के क्षेत्र मे, व्यापार में आदि अनेक हर क्षेत्र में भविष्य में अपार सम्भावनाए देखने को मिलती है। विश्वभर मेें जितने भी प्राणी रहते है उन सबसे ज्यादा बुद्विमान मानव है क्योकि मानव ने अपनी बुद्वि और अटूट इच्छा से नए-नए अविष्कार किए है। जिसमें से एक कृत्रिम बुद्विमता का अविष्कार आज तेजी से हो रहा है। जैसे किसी को देखकर, सुनकर या फिर स्पर्श करके, यह पता लगाया जा सकता हैै कि अब क्या करना है, इस तरह यह सारी प्रक्रिया एक मशीन के द्वारा की जाती है जिसे हम आज कृत्रिम बुद्विमता कहते है।

Artificial Intelligence (AI) has recently been recognized as a revolutionary trend in the financial sector, impacting the way people interact with, process, and make financial decisions. This research paper investigates the growing interface between AI and financial literacy, discussing the ways in which intelligent technologies like machine learning algorithms, robo-advisors, natural language processing engines, and generative AI tools are improving financial education and decision-making. Based on recent research and theoretical works, this paper examines the application of AI in personalizing financial education, achieving financial inclusion, and facilitating real-time decision-making. This paper also discusses the issues related to bias, trust, dependency, and digital inequality. A systematic review of academic sources indicates that AI can greatly enhance financial literacy outcomes, especially when combined with adaptive learning platforms and transparent financial technology. However, long-term behavioural effects are still unexplored. The results indicate that although AI has the potential to make financial education more inclusive and empowering, there is the need for ethical AI governance, regulation, and digital literacy development that can ensure effective implementation.

Artificial intelligence is transforming education systems world wide. It has rapidly transformed modern education, influencing not only cognitive learning but also the moral and ethical development of students. As AI-powered tools such as intelligent tutoring systems, chatbots, personalized learning platforms and automated assessment system become integral to classroom, their impact extends beyond academic performance into ethical reasoning, value formation and moral decision making. This article critically examines how AI shapes students’ moral and ethical values by exploring its positive contributions, ethical challenges, psychological implications and educational responsibilities. The paper highlights issues such as academic integrity, algorithmic bias, digital responsibility, empathy, critical thinking and ethical literacy. It also discusses the role of teachers, policy makers and institutions in guiding ethical AI usage. The study concludes that AI is neither inherently moral nor immoral; rather, its influence on students’ ethical values depends on its design, implementation and guided use in educational setting.

AI has transformed language learning, literature engagement, and communication skill development in India. Tools like chatbots, virtual tutors, and NLP systems provide personalized feedback and interactive learning, enhancing vocabulary, grammar, and communication. AI enables interactive analysis, content creation, and multilingual access in literature, which deepens critical thinking. Supporting regional languages, AI broadens inclusive education and digital literacy. Adaptive AI learning fosters autonomy, motivation, and creativity. AI enriches language learning, deepens literary understanding, and builds communication skills for diverse contexts.

As the name suggests Artificial Intelligence is not real but artificial. It doesn’t belong to human beings.It belongs to technologically developed devices and machines, mainly computers. It is imitation of human intelligence process by machines. Machines are built and developed which imitate human brain processes like learning, reasoning and self- correction etc. Alexander Pope in his poem, An Essay on Criticism (1711) says: “To Err is Humane; to forgive, Divine” means that humans are most likely to make mistakes. Now-a-days these mistakes are corrected through use of AI Machines. It has become integral part of human life. AI has provided all facilities to us, making our life a boon. It is used in almost every field of life to crack the complex problems in various disciplines like science, engineering, business, education, health, safety, driving, gaming, medication, meditation and weather forecasting etc. It has affected all domains of our life and proved itself as a boost in both quality and efficiency. It has changed our life style tremendously. It is now visible even in schools, colleges, hospitals, hotels, transportation and houses also. In future, these AI or smart machines can replace the humans in various domains. This paper presents working of AI, its application in various areas mainly in Education, its benefits and challenges.

प्रस्तुत शोध पत्र भारतीय राष्ट्रवाद पर विशेष रूप से विनायक दामोदर वीर सावरकर की दृष्टि में प्रस्तुत विचार तथ्य के अध्ययन के संदर्भ में लिखा गया है। भारत में अनेक ऐसे क्रांतिकारी हुए हैं जिन्होंने भारत माता को ब्रिटिश सरकार की बेड़ियों से स्वतंत्र कराने के लिए अपना घर परिवार त्याग दिया और जेल की यातनाएं सहन की लेकिन भारत के इतिहास में ऐसा केवल एक ही क्रांतिकारी हुआ है जिसे कालापानी की सेलुलर जेल की 25-25 वर्ष की दो आजीवन कैद की सजा हुई हो। जिसने सबसे पहले ब्रिटिश साम्राज्य के केंद्र लंदन में उसके विरुद्ध क्रांतिकारी आंदोलन संकलित किया हो, जो स्वतंत्रता सेनानी होने के साथ-साथ एक चिंतक, समाज सुधारक, इतिहासकार, विपुल साहित्यिक लेखक, संवेदनशील कवि तथा दूरदर्शी नेता जिसने भारतीय राष्ट्रवाद की राजनीतिक विचारधारा को विकसित किया