Mr. Nitin Janki Mamatu Pimparkar, Dr. Ramraj T. Nadar
Page 01 - 16
Abstract
The
rapid digitisation of financial services has fundamentally transformed the
operational framework of banking institutions in India. Urban Cooperative Banks
(UCBs), which serve as vital grassroots financial institutions, play a crucial
role in advancing financial inclusion by extending banking services to small
businesses, middle-income groups, and underserved communities across urban and
semi-urban regions. However, the accelerating adoption of digital banking
platforms, artificial intelligence (AI), cloud computing, and data analytics
has resulted in the extensive collection and processing of personal and
financial information, thereby raising critical concerns related to data
privacy, cybersecurity, and ethical governance. The Digital Personal Data
Protection (DPDP) Act, 2023, enacted by the Government of India, introduces a
comprehensive legal framework for safeguarding digital personal data by
defining the obligations of data fiduciaries, establishing rights for data
principals, and mandating accountability mechanisms for organisations
processing personal data (Government of India, 2023). For UCBs, compliance with
the DPDP Act is not merely a regulatory necessity but also a strategic
opportunity to enhance customer trust, strengthen cybersecurity practices,
improve governance standards, and enable the responsible adoption of AI-driven
banking solutions.
This
research paper examines the readiness of Urban Cooperative Banks to implement
the requirements of the DPDP Act, 2023, particularly in the context of
AI-enabled banking operations. The study adopts a qualitative exploratory
approach based on secondary data collected from regulatory reports, academic
literature, government publications, Reserve Bank of India (RBI) guidelines,
and industry studies. The analysis evaluates UCB preparedness across five key
dimensions: legal compliance, governance capability, AI adoption, cybersecurity
readiness, and ethical responsibility. The study identifies that while UCBs
have made notable progress in digital transformation, significant challenges
remain, including limited technological infrastructure, high compliance costs,
a shortage of skilled professionals, dependence on legacy systems, and
inadequate AI governance mechanisms. To address these issues, the paper
proposes a DPDP compliance framework incorporating privacy-by-design
principles, AI governance practices, cybersecurity enhancement, employee
training, vendor management, and regulatory oversight. The research concludes
that effective implementation of the DPDP Act, 2023 can enable Urban
Cooperative Banks to achieve responsible digital transformation while protecting
customer privacy, strengthening institutional resilience, and enhancing trust
in India’s cooperative banking ecosystem.
Keywords: Data
Privacy, DPDP Act 2023, Urban Cooperative Banks, Artificial Intelligence, AI
Governance, Banking Ethics, Cybersecurity, Data Protection, Digital Banking,
Financial Inclusion.
Cite as
Mr. Nitin Janki Mamatu Pimparkar, & Dr. Ramraj T. Nadar. (2026). Data Privacy in Grassroots Banking – Assessing DPDP Act Readiness in Urban Cooperative Banks in the Era of AI. International Journal of Arts, Social Sciences and Humanities, 04(04), 01–16. https://doi.org/10.5281/zenodo.23011745
Dr. Anita Rane- Kothare, Ms. Mala Topandas Khanchandani
Page 17 - 26
Abstract:
Artificial Intelligence (AI) has revolutionized the education sector with new teaching-learning models, customized learning spaces and enhanced skill development opportunities. Generative AI technologies such as ChatGPT, Gemini, and AI-assisted educational platforms are increasingly being adopted by students, teachers, and educational institutions. At the same time, the focus on the implementation of the National Education Policy (NEP) 2020 has been on technology integration, multidisciplinary learning, experiential learning, and development of digital skills. Additionally, the use of AI-powered interactive exhibits, virtual learning spaces, and digital heritage preservation methods for educational goals has transformed museum practices.
The present study explores the significance of AI in the field of education and skill development, particularly in the context of generative AI, the NEP 2020 and current museum practices in the Mumbai Metropolitan Region. The study aims to gain insights into students’ and teachers’ awareness along with the effectiveness and challenges of using AI tools in education, as well as the awareness and challenges of using AI tools in museum work. A structured questionnaire was used to gather data from 200 respondents from the population, with stratified random sampling. Students (60%), teachers (25%) and museum professionals (15%) were among the respondents.
The results suggest that G.A.I. has made a huge contribution to the learning efficiency, research, creativity and skill acquisition of learners. The study also shows that the goals of NEP 2020 are positively facilitated with AI driven education practices. AI-enhanced digital exhibits were found to engage and enhance learning for visitors, according to museum professionals.
The research concludes that AI is a game-changer in the education and cultural learning landscape. To leverage the potential of AI in education and museum-based learning effectively, implementation strategies, digital literacy programs, and ethical guidelines are crucial. The research provides valuable guidance for policymakers, educators, museum administrators, and researchers in developing innovative, technology-enhanced learning environments that enrich educational experiences and promote greater engagement.
Keywords: Artificial Intelligence in Education, Generative AI, NEP 2020, Museum Innovation and Skill Development.
Cite as
Dr. Anita Rane- Kothare, & Ms. Mala Topandas Khanchandani. (2026). A Study of AI in Education and Skill Development: Exploring Generative AI, NEP 2020, and Modern Museum Practices in MMR. International Journal of Arts, Social Sciences and Humanities, 04(04), 17–26. https://doi.org/10.5281/zenodo.23018463
CA Pravin Pawar, CA Dr. Vijay Satra, CS Gopalkrishna Chodnekar
Page 27 - 35
Abstract
Financial inclusion has become a key part of economic development and is essential for providing easy and low-cost access to financial services to individuals and businesses. From machine learning to AI-powered predictive analytics, AI-driven tools like robo-advisory platforms, biometric authentication, and chatbots have improved financial institutions’ access to previously unreached groups. The use of digital payment systems, mobile banking apps, and AI-powered financial platforms has helped raise awareness and participation in the formal financial system, particularly in urban areas like Dadar, Mumbai. The present study aims to explore the position of AI in financial inclusion for promoting sustainable advancement of FinTech in Dadar. This study aims to shed light on how AI technologies enable financial accessibility, overcome operational challenges, enhance customer engagement, and drive sustainable financial growth. Trends and developments in the financial sector are analyzed using secondary information from government reports, publications of Reserve Bank India, industry reports on FinTech, research articles and statistical databases. The results indicate that AI-driven financial services have incremented the efficiency of transactions, cut the cost of services, strengthened the fraud prevention process, and broadened access to banking services for a variety of user groups. Moreover, the sustainable development of FinTech has also led to economic empowerment, financial literacy, and financial resilience. The study concludes that AI-driven financial inclusion is a critical element in driving sustainable FinTech growth in Dadar, and holds tremendous potential to enhance the financial ecosystem by providing innovation, accessibility, and responsible technological advancements.
Keywords: Artificial Intelligence (AI), Financial Inclusion, FinTech Development, Digital Financial Services and Sustainable Finance.
Cite as
CA Pravin Pawar, CA Dr. Vijay Satra, & CS Gopalkrishna Chodnekar. (2026). A Study of AI-Driven Financial Inclusion and Sustainable Fintech Development in Dadar. International Journal of Arts, Social Sciences and Humanities, 04(04), 27–35. https://doi.org/10.5281/zenodo.23020054
Mr. Pradeep Ramashankar Mali, Dr. Savita Nagar
Page 36 - 47
Abstract
The rapid expansion of cloud kitchens in urban India has reshaped the food service landscape, yet the mechanisms through which food quality translates into consumer purchase intention remain insufficiently understood. This study examines the influence of food quality on consumer intention towards cloud kitchens in Mumbai, with parallel mediating roles assigned to perceived value and trust. Grounded in stimulus–organism–response (S–O–R) theory and signalling theory, a cross-sectional quantitative design was adopted. Data were collected from 400 respondents who had ordered food from cloud kitchens in Mumbai during the preceding six months, using a structured questionnaire measured on a five-point Likert scale. Convenience sampling was employed, and data were analysed using the General Linear Model with parallel mediation in Jamovi. The results indicate that food quality significantly enhanced both perceived value (β = 0.698, p < .001) and trust (β = 0.824, p < .001). Perceived value (β = 0.379, p < .001) and trust (β = 0.476, p < .001) in turn positively influenced consumer intention. The direct effect of food quality on consumer intention was not significant (β = 0.087, p = .059), while both indirect paths were significant, with trust exerting the stronger mediating effect (β = 0.392) than perceived value (β = 0.265). The model explained 75.3% of the variance in consumer intention. The findings establish full parallel mediation, suggesting that cloud kitchen operators should prioritise food quality as a signal that builds trust and value, which subsequently drive repeat patronage.
Keywords: cloud kitchens; food quality; perceived value; trust; consumer intention; parallel mediation; Mumbai.
Cite as
Mr. Pradeep Ramashankar Mali, & Dr. Savita Nagar. (2026). The Influence of Food Quality on Consumer Intention Towards Cloud Kitchens in Mumbai: The Parallel Mediating Roles of Perceived Value and Trust. International Journal of Arts, Social Sciences and Humanities, 04(04), 36–47. https://doi.org/10.5281/zenodo.23038758
Dr. Nitin Dwivedi
Page 48 - 54
This study investigates the influence of
artificial intelligence (AI) awareness, AI adoption, and perceived benefits of
AI on the economic empowerment of women entrepreneurs. A structured
questionnaire was administered to 280 women entrepreneurs across diverse
business sectors, and data were analyzed using multiple linear regression. The
regression model explained 59% of the variance in economic empowerment (R² =
0.59, F(3, 276) = 132, p < .001). AI adoption (β = 0.345, p < .001) and
perceived benefits of AI (β = 0.401, p < .001) emerged as significant
predictors, while AI awareness did not reach statistical significance (β =
0.098, p = .095). The findings underscore the importance of moving beyond
awareness to actual adoption and positive perception of AI as critical pathways
for enhancing women’s economic empowerment. Implications for policymakers and
support organizations are discussed.
Keywords: AI awareness; AI adoption; perceived
benefits; economic empowerment; women entrepreneurs; digital entrepreneurship
Cite as
Dr. Nitin Dwivedi. (2026). Artificial Intelligence and Economic Empowerment of Women Entrepreneurs: The Role of AI Awareness, AI Adoption, and Perceived Benefit. International Journal of Arts, Social Sciences and Humanities, 04(04), 48–54. https://doi.org/10.5281/zenodo.23040705
Ms. Sonia Lal, Ms. Snehal Pandey
Page 55 - 64
Abstract
The rapid diffusion of Artificial Intelligence (AI) tools into higher education has introduced a new axis of inequality that extends beyond the conventional “digital divide.” While earlier scholarship focused on disparities in internet connectivity and device ownership, this study argues that access alone no longer captures the full picture of educational inequality in the AI era. It proposes the concept of an “AI Divide” — a multidimensional gap encompassing who has access to AI tools, who possesses the digital literacy to use them effectively, who derives genuine academic benefit, and how these disparities generate new forms of exclusion.
Situated within Indian higher education — a context marked by significant socioeconomic, regional, and institutional diversity — the study draws on a randomly sampled cohort of 111 students to examine AI tool adoption, competence, and perceived academic impact. It investigates the factors shaping unequal access, disparities in skills required for effective academic use, variation in reported academic benefit, and the mechanisms through which AI adoption creates or reinforces existing educational inequalities.
Drawing on the sociology of education and digital-inequality literature — including cultural capital, the “second-level digital divide,” and algorithmic literacy — this research moves the discourse from a binary understanding of access to a nuanced analysis of usage, skill, and outcome disparities, contributing to policy discussions on equitable AI integration in the Global South.
Keywords: Artificial Intelligence (AI), AI Divide, Digital Inequality, Digital Literacy, Educational Inequality, Cultural Capital.
Cite as
Ms Sonia Lal, & Ms Snehal Pandey. (2026). From Digital Divide to AI Divide: A Sociological Study of Educational Inequality in Indian Higher Education. International Journal of Arts, Social Sciences and Humanities, 04(04). https://doi.org/10.5281/zenodo.23055691
Dr. Sachin Chandrakant Pimple, and CA (Dr.) Kishore Peshori
Page 65 - 74
Abstract
This study examines whether financial literacy is associated with environmental, social, and governance (ESG) awareness and self-reported participation in ESG-themed investments among retail investors in Mumbai.
A structured questionnaire was administered to 224 individual investors with an active demat or trading account and at least one year of investing experience during FY 2025-26. Financial literacy and ESG awareness were measured on 0-20 scales. The analysis used descriptive statistics, correlations, Chi-square tests, t-tests, ANOVA, and supplementary binary logistic regression. Scale reliability was satisfactory (alpha = 0.84 and 0.81, respectively).
Financial literacy was strongly associated with ESG awareness (r = 0.62, p < 0.001) but more modestly with ESG participation (r_pb = 0.28, p < 0.001). Financial-literacy category and participation were associated, chi-square(2, N = 224) = 15.64, p < 0.001, Cramer’s V = 0.26. In the adjusted model, ESG awareness (OR = 1.23, p < 0.001), financial literacy (OR = 1.15, p = 0.005), and income band (OR = 1.36, p = 0.027) were statistically significant; age and gender were not. Among highly ESG-aware respondents, 43.0 per cent reported no ESG holding.
The study links conventional financial literacy with ESG-specific knowledge and behaviour in an emerging-market retail-investor setting. It identifies an awareness-to-action gap and supports clearer ESG disclosures and evidence-based investor education. Because the design is cross-sectional and uses convenience sampling, the findings indicate association, not causation.
Cite as
Dr. Sachin Chandrakant Pimple, & CA (Dr.) Kishore Peshori. (2026). Financial Literacy, ESG Awareness, and Sustainable Investment Participation: Evidence from Individual Investors in Mumbai. International Journal of Arts, Social Sciences and Humanities, 04(04), 65–74. https://doi.org/10.5281/zenodo.23057878
Alwyn Alfred Carvalho, Bhumika Gorakhnath Salvi
Page 75 - 82
Abstract
English Literature departments face a peculiar version of cheating using Artificial Intelligence, particularly Large Language Models (LLMs). Most of the canon these courses teach from is already public domain, already digitized, and already sitting inside the training data of most major language models. A student does not need to ask an AI to think about Hamlet; the model has, in some sense, already read it a thousand times over. This paper looks at what actions departments may take for it, and where those responses tend to fall apart. Timed online examinations have picked up a set of technical countermeasures over the past year or so: hidden prompt injections buried in the question text, watermarked or visually distorted question images, AI-based proctoring. One documented case from July 2026 caught thirty-two of thirty-five students this way. But these tricks have a short shelf life. Students figure them out quickly, model providers patch around them faster, and proctoring software frequently incorrectly flag attempts which may be genuine. Take-home writing is a harder problem, and probably the more important one for a literature department, since AI detectors themselves are unreliable and biased against certain kinds of writers. Our argument, briefly, is that assignments need to stop rewarding a finished essay and start rewarding the visible work behind it including drafts, in-class discussion tied directly into the prompt, or a short oral defence of the argument. None of this is a permanent fix. It is closer to a set of habits that make AI-generated submissions harder to pass off as one’s own, drawn from work in AI security, assessment design, and literary pedagogy that rarely gets read together.
Keywords: Academic integrity, Generative AI in education, Assessment design, Prompt injection, English literature pedagogy
Cite as
Alwyn Alfred Carvalho, & Bhumika Gorakhnath Salvi. (2026). Beyond the Prompt: A Dual-Layer Framework for AI-Resistant Assessment in English Literature Education. International Journal of Arts, Social Sciences and Humanities, 04(04), 75–82. https://doi.org/10.5281/zenodo.23059926
Ms. Susan Maria. Abraham, Dr. Parag Ajagaonkar
Page 83 - 89
Abstract
The fast-growing information technology (IT) industry has offered new employment opportunities to women and new work structures that are demanding and involve long working hours, tight deadlines, global teams, continuous connectivity and high performance expectations. These demands are often compounded for women in the IT profession, especially when married and having children and caring responsibilities. Workplace flexibility, as a tool, has become a significant option to deal with competing work and life demands in this context. To address these issues, the paper investigates two aspects of flexibility – task flexibility and role flexibility – and how they can aid in work–life balance for women working in the IT sector. Task flexibility is the degree of freedom and discretion that workers have in relation to how, when and, in some instances, where work tasks are executed. Role flexibility is the ability to adapt/modify, redistribute or temporarily change professional role due to personal/organisational situations. The paper suggests that these forms of flexibility can help to alleviate work–family conflict, increase autonomy, increase job satisfaction, and support women’s retention and career continuity in the IT sector. But being flexible doesn’t always yield positive results. However, if expectations of availability are too high, if there are career disadvantages for having a flexible working schedule, or if the culture of an organisation promotes long hours, the benefits of EWP can be compromised.
The paper therefore suggests that it is important for the organisations to implement structured gendered flexible policies with inclusive leadership, the implementation of performance-based evaluation and clear work-life boundaries.
Keywords: Task flexibility, role flexibility, Women IT professionals, Work–life balance, Flexible working, Role conflict, Workplace flexibility, Information technology
Cite as
Ms. Susan Maria. Abraham, & Dr. Parag Ajagaonkar. (2026). Task and Role Flexibility as Enablers of Work–Life Balance among Women Information Technology Professionals. International Journal of Arts, Social Sciences and Humanities, 04(04), 83–89. https://doi.org/10.5281/zenodo.23064225
Ms. Bhoomika Jain, Mrs. Harpreet Kaur
Page 90 - 97
Abstract: Artificial Intelligence (AI) is increasingly becoming part of teaching, learning, assessment and skill-development activities. AI tools can support personalized learning, provide rapid feedback, assist with problem solving and help students practise technical and communication skills. At the same time, excessive or uncritical use of AI may create risks such as over-dependence, reduced independent thinking, inaccurate information, privacy concerns and academic-integrity problems. This research paper examines the relationship between AI use in education and student skill development, with particular attention to AI literacy, conceptual understanding, critical thinking, problem solving, communication and responsible use of AI. The study follows a secondary-data research design using a publicly available Kaggle dataset on academic outcomes and AI dependency, supported by findings from recent peer-reviewed research. The proposed analysis uses descriptive statistics, an independent-samples t-test, correlation analysis and regression-based interpretation. The paper argues that the educational value of AI depends less on simple frequency of use and more on purposeful, ethical and guided use that strengthens rather than replaces human skills.
Keywords: Artificial Intelligence, AI in Education, AI Literacy, Skill Development, Critical Thinking, Academic Performance, AI Dependency, Higher Education.
Cite as
Ms. Bhoomika Jain, & Mrs. Harpreet Kaur. (2026). An Analysis of AI in Education and Skill Development. International Journal of Arts, Social Sciences and Humanities, 04(04), 90–97. https://doi.org/10.5281/zenodo.23065807
Dr CA Krishnan Jaikumar
Page 98 - 106
Abstract
The increasing complexity and dynamism of global supply chains have rendered traditional inventory management approaches insufficient for meeting contemporary operational demands. Artificial intelligence (AI) offers transformative capabilities for inventory optimization through enhanced demand forecasting, automated replenishment, cost reduction, and supply chain resilience. This paper examines the integration of AI technologies in inventory management and their impact on operational efficiency through a systematic literature review and analysis of real-world case studies. The findings reveal that machine learning and deep learning models substantially outperform traditional statistical methods in demand prediction accuracy, particularly for intermittent and volatile demand patterns. AI-driven automated replenishment systems reduce stockouts and excess inventory, while predictive analytics enable proactive risk mitigation. Case analyses of Amazon, Walmart, and Zara demonstrate that organizations leveraging AI achieve measurable improvements in inventory turnover, waste reduction, and supply chain responsiveness. The paper concludes with a discussion of implementation challenges and future research directions, including the potential of generative AI and digital twin technologies.
Keywords: Artificial intelligence, inventory management, demand forecasting, supply chain resilience, operational efficiency, machine learning
Cite as
Dr CA Krishnan Jaikumar. (2026). AI-Based Inventory Management and Operational Efficiency. International Journal of Arts, Social Sciences and Humanities, 04(04), 98–106. https://doi.org/10.5281/zenodo.23077668
Komal Ravindra Pawar
Page 107 - 116
Not Available
Cite as
Komal Ravindra Pawar. (2026). Understanding the Role of Artificial Intelligence in Preventing Digital Payment Fraud: A Study of Consumer Awareness, Trust and Perceived Security in Mumbai Suburban Area. International Journal of Arts, Social Sciences and Humanities, 04(04), 107–116. https://doi.org/10.5281/zenodo.23078386
Dr. (CA) Nishesh S Vilekar, Ms. Manmeet Kaur
Page 117 - 123
Not Available
Cite as
Dr. (CA) Nishesh S Vilekar, & Ms. Manmeet Kaur. (2026). An Empirical Study on Awareness and Adoption of AI-Based Accounting Software Among Accountants. International Journal of Arts, Social Sciences and Humanities, 04(04), 117–123. https://doi.org/10.5281/zenodo.23079008
Ms. Khyatee Dilip Lakhani
Page 124 - 130
Not Available
Cite as
Ms. Khyatee Dilip Lakhani. (2026). NEP 2020 and Artificial Intelligence: Transforming Teaching, Learning, and Assessment in Higher Education. International Journal of Arts, Social Sciences and Humanities, 04(04), 124–130. https://doi.org/10.5281/zenodo.23081393
Dr. Sadhana Chhatlani
Page 131 - 138
Abstract
It is evident that Artificial Intelligence (AI) now plays and important role in every students life. It is being adapted progressively becoming an inevitable part of almost every student’s academic performance. The use of AI tools such as ChatGPT, Gemini, Canva, and many more AI-based learning platforms support student learning effectively. These tools aid as search engine machines used to extract information. Students often use AI learning based platforms for synthezising challenging concepts, seeking creative assignment ideas. They also use AI tools for taming writing skills and specifically during preparation of their exam preparation. Generation Z, is known to be digitally native so they have grown up in an environment which is highly digital in nature. So they are highly privileged to secure an environment that not only supports but also openly accepts wide usage of AI based technologies. This adoption of AI based technology learning not only designs their day to day living easy, but also supports them in their learning processes. AI tools facilitate learning quicker in less time and features personalised learning. AI based learning tools are easily accessible for students as they are either free of cost or offered to students at lower costs. Although excessive dependence on AI based tools for learning is not fit for students as, it restricts their independent critical thinking blocking their creativity minds and hinders problem-solving abilities. The main purpose of the research paper was to scrutinize the impact of AI tools on the learning behaviour of Gen Z students. The study is an attempt to focus on gauging the frequency with which the Gen Z students use AI learning tools, understanding the purpose of AI usage. An analysis is done through to pivot lenses on the influence of AI based learning on various parameters like learning efficiency, change academic engagement, and the perception of students. It will give a clear picture whether students hold AI based learning as an advantage or a possible limitation when adopted for educational purposes.
Keywords: Artificial Intelligence, AI Tools, Generation Z, Learning Behaviour, Students, Academic Engagement, Technology in Education
Cite as
Dr. Sadhana Chhatlani. (2026). Impact of Artificial Intelligence Tools on the Learning Behaviour and Academic Engagement of Generation Z Students. International Journal of Arts, Social Sciences and Humanities, 04(04), 131–138. https://doi.org/10.5281/zenodo.23115874
Nisar Saiyed and Sneha Singh
Page 139 - 146
Abstract
Background: As the reliance on AI keeps growing, it becomes important to understand its psychological implications. The study contributes to the growing literature on AI and mental health by investigating the predictive quality of AI dependency and distress tolerance in the use of avoidance coping in response to stressful situations.
Aims: The present research aims to examine the predictive relationship between AI dependency, distress intolerance and avoidance coping among young adults in Mumbai.
Method: 90 participants from Mumbai (60 Females, 29 Males) who were aged between 18-25 years (M=20.8, SD=2.38) and used AI apps like ChatGPT and Gemini, were selected using convenience sampling. All participants completed the Generative AI Dependency Scale (Goh et al., 2025), Distress Tolerance Scale (Simons & Gaher, 2005) and Ways of Coping Scale-Revised (Folkman & Lazarus, 1985). Correlation and simple linear regression was computed for statistical analysis.
Results: Findings of the research indicate that AI dependency showed a significant positive correlation with avoidance coping (p < .01) and hence was a statistically significant predictor. Furthermore, distress intolerance showed a weak correlation with avoidance coping and was therefore not a statistically significant predictor (p > .05) of avoidance coping.
Conclusion: The findings of this study highlight the predictive role of AI dependency in the use of avoidance coping when faced with stressful situations. The role of distress tolerance in avoidance coping needs to be studied further in a more diverse and larger population. The findings may help develop strategies that promote healthy coping skills in stressful situations in the era of increasing AI use.
Keywords: AI Dependency, Distress Intolerance, Avoidance Coping, Young Adults
Cite as
Nisar Saiyed, & Sneha Singh. (2026). Beyond AI Use: Examining The Predictive Quality of AI Dependency & Distress Intolerance in Avoidance Coping Among Young Adults in Mumbai. International Journal of Arts, Social Sciences and Humanities, 04(04), 139–146. https://doi.org/10.5281/zenodo.23116714
Mandeep Singh Ahuja, and Dr. Devendra Lodha
Page 147 - 156
Abstract:
Introduction
The rapid diffusion of financial technology (fintech) has fundamentally reshaped the delivery of retail banking services across urban India, with Mumbai the country’s financial capital serving as an early adopter of digital banking innovation. Mobile banking applications, the Unified Payments Interface (UPI), robo-advisory tools, artificial-intelligence-driven chatbots and contactless payment systems have altered the manner in which customers interact with banks, raising important questions about how these technologies shape perceived service quality and, in turn, customer satisfaction.
Purpose
This study examines the extent to which fintech adoption influences the five SERVQUAL dimensions of service quality reliability, responsiveness, assurance, empathy and tangibles and overall customer satisfaction among retail banking customers in Mumbai.
Methodology
A descriptive and analytical research design was adopted. Primary data were collected from a sample of 100 retail banking customers in Mumbai through a structured questionnaire administered on a five-point Likert scale, supplemented by secondary data drawn from journals, RBI publications, NPCI reports and bank disclosures. Percentage analysis, mean analysis and Karl Pearson’s correlation analysis were used to examine the relationships in the data.
Findings
Fintech adoption was found to be positively associated with customer-perceived service quality and satisfaction, with responsiveness and convenience-related dimensions showing the strongest association among Mumbai’s retail banking customers. Respondents in the 21–40 age group and those with higher digital literacy reported significantly greater satisfaction with fintech-enabled banking channels than with traditional branch banking. All three hypotheses were statistically confirmed: a one-sample t-test showed fintech adoption is significantly related to perceived service quality (t = 12.46, p = 0.000); Karl Pearson’s correlation confirmed a strong positive relationship between fintech-driven service quality and customer satisfaction (r = 0.72, p = 0.000); and a one-way ANOVA confirmed that satisfaction differs significantly across age groups (F = 3.85, p = 0.012).
Implications
The findings carry implications for retail banks seeking to refine digital-channel strategy, for regulators concerned with consumer protection and digital financial inclusion, and for future researchers seeking to extend the service-quality literature into the fintech domain.
Keywords: Fintech, Retail Banking, Service Quality, Customer Satisfaction, Digital Transformation, Mumbai, SERVQUAL.
Cite as
Mandeep Singh Ahuja, & Dr. Devendra Lodha. (2026). Digital Transformation in Retail Banking: Fintech’s Effect on Service Quality and Customer Satisfaction in Mumbai. International Journal of Arts, Social Sciences and Humanities, 04(04), 147–156. https://doi.org/10.5281/zenodo.23117140
Dr. (Mrs). Vaishali Nadkarni
Page 157 - 166
Abstract:
The rapid proliferation of artificial intelligence (AI) and big data analytics has fundamentally transformed how organizations understand, predict, and influence consumer behavior. Despite the growing adoption of AI-driven predictive analytics in marketing, there remains limited theoretical integration explaining how these technologies shape consumer decision-making processes. This paper presents a conceptual framework that examines the relationships among AI-based personalization, predictive analytics capability, consumer data quality, and AI recommendation accuracy as independent variables, consumer trust as a mediator, and purchase intention and customer loyalty as dependent variables. Drawing upon the Technology Acceptance Model, the Theory of Planned Behavior, the Stimulus–Organism–Response framework, and Expectation Confirmation Theory, the study synthesizes current literature across AI in marketing, machine learning applications, recommendation systems, customer segmentation, and consumer journey analytics. The proposed framework contributes to the literature by providing a holistic theoretical model that bridges the gap between technological capabilities and behavioral outcomes. Practical implications suggest that organizations should prioritize data quality and algorithmic transparency to foster consumer trust, while ethical considerations regarding privacy and bias in AI models warrant careful governance. The findings offer actionable insights for marketers, technology developers, and policymakers seeking to leverage predictive analytics responsibly in consumer-facing applications.
Keywords: artificial intelligence, predictive analytics, consumer behaviour, personalization, purchase intention, customer loyalty, consumer trust
Cite as
Dr. (Mrs). Vaishali Nadkarni. (2026). Understanding Consumer Behavior Through AI-Driven Predictive Analytics. International Journal of Arts, Social Sciences and Humanities, 04(04), 157–166. https://doi.org/10.5281/zenodo.23118570
Dr. Sachin Joshi
Page 167 - 174
Abstract:
The rapid integration of artificial intelligence into organisational workflows has introduced unprecedented cybersecurity challenges, necessitating a deeper understanding of how users perceive and respond to AI-related risks. This study investigates the mediating role of AI Risk Perception in the relationship between Cyber Security Awareness and Secure AI Usage Behaviour. Drawing on Protection Motivation Theory and employing a cross-sectional survey design, data were collected from 300 respondents across diverse industries using a structured questionnaire measuring three latent constructs. Mediation analysis, conducted using the PROCESS macro with bootstrap confidence intervals, revealed that Cyber Security Awareness has a strong positive effect on AI Risk Perception (path a: β = 0.712, p < 0.001), which in turn positively influences Secure AI Usage Behaviour (path b: β = 0.444, p < 0.001). The direct effect of Cyber Security Awareness on Secure AI Usage Behaviour remained significant (path c′: β = 0.413, p < 0.001), while the indirect effect through AI Risk Perception was also significant (β = 0.316, 95% CI [0.229, 0.404]). These findings support partial mediation, indicating that AI Risk Perception accounts for approximately 43.3% of the total effect. The results underscore the importance of integrating cybersecurity education with AI risk awareness programmes to foster responsible AI adoption.
Keywords: Cyber Security Awareness, AI Risk Perception, Secure AI Usage Behaviour, Mediation Analysis, Responsible AI Adoption, Protection Motivation Theory
Cite as
Dr. Sachin Joshi. (2026). Cyber Security Awareness and Responsible AI Adoption: A Mediation Analysis of AI Risk Perception. International Journal of Arts, Social Sciences and Humanities, 04(04), 167–174. https://doi.org/10.5281/zenodo.23153773
Dr. Balram Gowda
Page 175 - 183
Abstract
The increasing sophistication and volume of financial fraud in digital banking systems have compelled organizations to adopt artificial intelligence (AI) as a core detection mechanism. This study investigated the influence of three critical AI system attributes—perceived AI accuracy, AI speed, and AI reliability—on the perceived effectiveness of AI-based fraud detection among 300 professionals in the banking and financial services sector. Grounded in the DeLone and McLean Information Systems Success Model, a quantitative cross-sectional survey design was employed, and multiple linear regression analysis was conducted. The regression model explained 85.5% of the variance in fraud detection effectiveness (R² = .855, F(3, 296) = 582, p < .001). All three predictors were statistically significant: AI Speed exhibited the strongest standardized effect (β = .350, p < .001), followed by AI Reliability (β = .319, p < .001) and AI Accuracy (β = .298, p < .001). These findings underscore the importance of optimizing not only the accuracy but also the processing speed and reliability of AI fraud detection systems.
Keywords: Artificial Intelligence, Fraud Detection, AI Accuracy, AI Speed, AI Reliability, DeLone and McLean Model, Financial Services
Cite as
Dr. Balram Gowda. (2026). Factors Influencing the Effectiveness of AI-Based Fraud Detection. International Journal of Arts, Social Sciences and Humanities, 04(04), 175–183. https://doi.org/10.5281/zenodo.23154513
Dr. Manojkumar Gupta
Page 184 - 191
Abstract:
The rapid rise of financial influencers popularly known as finfluencers has been one of the most visible developments in India’s financial ecosystem in the last decade. Social media platforms such as YouTube, Instagram, Telegram, Reddit, Facebook and X (formally known Twitter) have provided ordinary individuals with an opportunity to present investment-related content to mass audiences. As India has witnessed full exponential growth and flowering in retail participation in the stock market and mutual funds. Finfluencers have emerged as a crucial bridge between formal financial institutions and young digitally-savvy investors. By providing simplified complex financial decisions they contribute to financial inclusion and digital literacy where formal financial education remains limited. However, their growing influence has also raised significant regulatory, ethical, and economic concerns. The absence of mandatory registration, instances of biased or sponsored recommendations, and the amplification of behavioral biases have created new challenges for investor protection.
The Securities and Exchange Board of India (SEBI) has in response proposed and implemented multiple guidelines since 2023 to address this phenomenon. These include restrictions on intermediaries’ partnerships with finfluencers, mandatory disclosures for paid promotions, and warnings against unregistered advisory services. This research is based exclusively on secondary data that critically examines the rise of finfluencers in India and their implications for individual investment decision-making & SEBI’s regulatory stance. From academic literature, regulatory reports, media coverage, and expert commentaries the paper provides a holistic understanding of the dual role finfluencers play in democratizing finance and exposing retail investors to new risks. It also situates SEBI’s interventions in a comparative global context by drawing parallels with measures adopted by the U.S. Securities and Exchange Commission (SEC) and the UK’s Financial Conduct Authority (FCA). The findings highlight a regulatory dilemma: how to strike a balance between protecting investors from misleading advice while not stifling the positive role of finfluencers in enhancing financial awareness. The study concludes with policy recommendations, enhanced investor education, platform-level accountability, and adaptive regulatory mechanisms to ensure sustainable financial innovation.
Keywords: Finfluencers, SEBI, Retail Investors, Behavioral Finance, Social Media, Regulation
Cite as
Dr. Manojkumar Gupta. (2026). The Rise of Finfluencers and Their Impact on Individual Investment Decisions in India: A Regulatory Perspective with Reference to SEBI Guidelines. International Journal of Arts, Social Sciences and Humanities, 04(04), 184–191. https://doi.org/10.5281/zenodo.23155812
Dr. Priya Ashok Sapkale
Page 192 - 197
Abstract
Green finance has emerged as a critical mechanism for aligning capital allocation with environmental sustainability goals in India. This study examines how instruments such as green bonds, green loans, sustainability-linked finance, and related regulatory frameworks enable Indian businesses to adopt sustainable practices. This study also indicates that small-scale business organizations face limitations in accessing and benefiting from green finance due to inadequate awareness of the available regulatory frameworks, financial instruments, and related opportunities. The awareness of green finance has not yet reached the desired level within the business environment, which limits its effective adoption among small businesses.
Keywords: Green finance, sustainable business practices, conceptual framework.
Cite as
Dr. Priya Ashok Sapkale. (2026). The Role of Green Finance in Promoting Sustainable Business Practices in India: A Conceptual framework. International Journal of Arts, Social Sciences and Humanities, 04(04), 192–197. https://doi.org/10.5281/zenodo.23156627
Mrs. Amita M. Kulkarni
Page 198 - 204
Abstract: Artificial intelligence (AI) has emerged as one of the most transformative forces in contemporary education, reshaping how knowledge is delivered, assessed, and personalized. This literature review examines the evolution, applications, benefits, and challenges of AI in teaching and learning contexts. Drawing on peer-reviewed research and institutional reports published between 2016 and 2024, the review identifies four principal areas of AI application: intelligent tutoring systems, automated assessment and feedback mechanisms, learning analytics, and generative AI for content creation. The findings reveal that AI holds significant promise for enhancing personalized learning, improving student engagement, and reducing educator workloads. However, critical challenges persist, including concerns about data privacy, algorithmic bias, the digital divide, and the potential erosion of the teacher-student relationship. The review concludes that while AI is unlikely to replace human educators, its thoughtful integration can substantially enrich educational outcomes when guided by ethical frameworks and pedagogical best practices.
Keywords: artificial intelligence, education, intelligent tutoring systems, learning analytics, generative AI, personalized learning
Cite as
Mrs. Amita M. Kulkarni. (2026). Artificial Intelligence in Teaching and Learning: Transforming the Future of Education. International Journal of Arts, Social Sciences and Humanities, 04(04), 198–204. https://doi.org/10.5281/zenodo.23187946
Ms. Indira Ulagaraman, and Dr. H. Moideen Batcha
Page 205 - 214
Abstract
The increasing integration of Artificial Intelligence (AI) into human resource management has transformed traditional performance appraisal through data-driven evaluation, continuous feedback, predictive analytics, and automated decision-making. This study evaluates the impact of AI-enabled appraisal practices on millennial career advancement, with particular emphasis on gender equality in Mumbai workplaces. It examines AI-supported performance evaluation, feedback, competency assessment, and data-driven appraisal decisions in relation to career growth, promotion opportunities, professional development, and advancement. It also considers whether perceived gender equality and fairness are associated with career advancement and mediate the relationship between AI-enabled appraisal practices and career advancement. The study adopts a quantitative approach using a structured questionnaire among millennial employees in selected Mumbai workplaces. The findings indicate positive relationships among AI-enabled appraisal practices, perceived gender equality/fairness, and career advancement. The study contributes to the emerging literature on AI in HRM by connecting technology-enabled appraisal, career development, and gender equality. It also highlights the importance of transparency, consistency, human oversight, and ethical governance when implementing AI-supported appraisal systems.
Keywords: Artificial Intelligence, Performance Appraisal, Millennial Employees, Career Advancement, Gender Equality, Human Resource Management, Mumbai Workplaces.
Cite as
Ms. Indira Ulagaraman, & Dr. H. Moideen Batcha. (2026). Evaluating the Impact of AI-Enabled Appraisal Practices on Millennial Career Advancement: A Gender Equality Perspective in Mumbai Workplaces. International Journal of Arts, Social Sciences and Humanities, 04(04), 205–214. https://doi.org/10.5281/zenodo.23188775
Mansi Sudhir Kadam
Page 215 - 222
Abstract
Artificial Intelligence (AI) is increasingly becoming an enabling technology for the collection, validation, analysis and communication of environmental, social and governance (ESG) information and financial information. At the same time, expanding sustainability disclosure requirements are increasing the volume, variety and frequency of non-financial information that organisations must manage. This paper examines how AI can strengthen the relationship between ESG reporting and financial reporting by improving data processing, anomaly detection, disclosure preparation, forecasting, risk identification and digital reporting. The study uses a qualitative, descriptive and exploratory research design based on secondary sources, including international reporting standards, Indian regulatory publications and recent academic literature. Particular attention is given to IFRS S1, IFRS S2, the IFRS Sustainability Disclosure Taxonomy, India’s Business Responsibility and Sustainability Reporting (BRSR) framework and BRSR Core. The findings indicate that AI can improve reporting timeliness, consistency, scalability and decision usefulness, but its effectiveness depends on data quality, governance, explainability, human oversight, cybersecurity and clear accountability. AI should therefore be treated as a controlled reporting technology rather than an autonomous substitute for professional judgement. The paper recommends an integrated AI-enabled reporting architecture with strong data lineage, model governance, human review, assurance controls and ethical safeguards.
Keywords: Artificial Intelligence; ESG; Sustainability Reporting; Financial Reporting; BRSR; IFRS S1; IFRS S2; Data Analytics; Assurance; AI Governance
Cite as
Mansi Sudhir Kadam. (2026). Artificial Intelligence in ESG and Financial Reporting. International Journal of Arts, Social Sciences and Humanities, 04(04), 115–222. https://doi.org/10.5281/zenodo.23191012
Subhash Motiram Shengale
Page 223 - 233
Abstract
Artificial intelligence (AI) is fundamentally reshaping the financial services landscape in India, from algorithmic credit scoring and robo-advisory platforms to AI-powered chatbots handling customer queries. While the adoption of AI-driven financial products has accelerated, consumer trust remains a critical determinant of sustained uptake. This study investigates the influence of three key factors derived from the Technology Acceptance Model (TAM) on consumer trust in AI-enabled financial services in the Indian context: perceived usefulness (PU), perceived security (PS), and perceived ease of use (PEOU). A quantitative research design was employed, utilizing a structured 15-item Likert-scale questionnaire administered to 300 respondents across diverse demographic groups in India. Multiple regression analysis was used to test the hypothesised relationships. The results indicate that the model explains 73% of the variance in consumer trust (R-squared = 0.728), with all three independent variables demonstrating statistically significant positive relationships with consumer trust. Perceived ease of use emerged as the strongest predictor (standardised beta = 0.375), followed by perceived usefulness (standardised beta = 0.310) and perceived security (standardised beta = 0.236). The findings offer practical insights for fintech providers and policymakers seeking to strengthen consumer trust in AI-driven financial services across India.
Keywords: Artificial Intelligence, Consumer Trust, Technology Acceptance Model, Fintech, Financial Services, India
Cite as
Subhash Motiram Shengale. (2026). Factors Influencing Consumer Trust in AI-Enabled Financial Services in India. International Journal of Arts, Social Sciences and Humanities, 04(04), 223–233. https://doi.org/10.5281/zenodo.23191630
Dr. Devanjali Dutta
Page 234 - 243
Abstract
The rapid expansion of digital payment ecosystems in India, anchored by the Unified Payments Interface (UPI), has been accompanied by a sharp rise in payment fraud, eroding consumer confidence and threatening long-term adoption. Artificial intelligence (AI)-driven fraud prevention mechanisms—real-time anomaly detection, behavioural biometrics, and adaptive authentication—are increasingly deployed by payment service providers to mitigate this risk. Drawing on the Expectation-Confirmation Model of Information Systems Continuance (Bhattacherjee, 2001) and the trust literature (Mayer, Davis, & Schoorman, 1995), this study empirically examines the influence of perceived AI security features on customers’ continuance intention toward digital payment applications. A cross-sectional survey of 350 active digital payment users in India was conducted using a structured, five-point Likert-scale instrument. Pearson correlation analysis revealed a very strong, positive, and statistically significant association between AI security features and continuance intention (r = .900, p < .001, 95% CI [.878, .918]). Simple linear regression confirmed that AI security features significantly predict continuance intention, explaining 76.7% of the variance (R² = .767, F(1, 348) = 1147.00, p < .001; β = .876, t = 33.87, p < .001). The findings substantiate the proposition that visible, intelligent fraud-prevention capabilities function as a salient trust-building cue, thereby reinforcing users’ decision to continue using digital payment platforms. The paper discusses theoretical and managerial implications, acknowledges limitations, and outlines directions for future research.
Keywords: artificial intelligence; fraud prevention; digital payments; customer trust; continuance intention; expectation-confirmation model; UPI; India
Cite as
Dr. Devanjali Dutta. (2026). Impact of AI-Based Fraud Prevention on Customer Trust in Digital Payment Systems: An Empirical Investigation of Continuance Intention among Indian Users. International Journal of Arts, Social Sciences and Humanities, 04(04), 234–243. https://doi.org/10.5281/zenodo.23192478
Dr. Amrita A. Jadhav
Page 244 - 250
Abstract:
Artificial intelligence (AI) is rapidly reshaping educational practice worldwide, raising urgent questions about whether its integration supports or undermines the long-term sustainability of education systems. This paper examines the transformation of teaching and learning through AI from a sustainable education perspective, framed by the United Nations Sustainable Development Goal 4 (Quality Education). Drawing on a narrative synthesis of peer-reviewed literature and policy documents published between 2014 and 2024, the study identifies five thematic areas where AI intersects with sustainability: personalized learning, teacher augmentation, equity and inclusion, ethics and privacy, and the environmental footprint of educational AI infrastructure. Findings indicate that AI-enabled personalized learning can improve outcomes, but risks widening equity gaps if access and digital literacy are unevenly distributed. AI offers significant potential to augment rather than replace teachers, while demanding robust ethical governance to address bias, privacy and transparency. The environmental cost of large-scale AI deployment remains an under-recognised sustainability dimension. The paper concludes that sustainable AI in education requires coordinated policy, educator agency, AI literacy for all stakeholders, and a commitment to inclusive, transparent and ecologically responsible design.
Keywords: artificial intelligence in education; sustainable education; SDG 4; personalized learning; AI ethics; teacher augmentation; educational technology
Cite as
Dr. Amrita A. Jadhav. (2026). Transforming Teaching and Learning through Artificial Intelligence: A Sustainable Education Perspective. International Journal of Arts, Social Sciences and Humanities, 04(04), 244–250. https://doi.org/10.5281/zenodo.23205943
Ms. Shivani Pandya, and Dr. Kedar Bhide
Page 251 - 259
Abstract
The growing use of social media for financial information has changed the way retail investors encounter investment-related opinions, market information and product-related content. This study examines whether age, educational qualification and the frequency of consuming financial or investment content through social media are associated with mutual fund investment decision scores among retail investors represented in the Mumbai and Thane region. Primary data was collected from 67 retail investors through a structured questionnaire. A 10-item Likert-scale measure was used to capture social-media-influenced mutual fund investment decision-making and demonstrated good internal consistency (Cronbach’s alpha = 0.839). Descriptive statistics and Spearman’s rank-order correlation were used for the analysis. The results indicate no statistically significant association between age and investment decision scores (ρ = -0.136, p = 0.283), educational qualification and investment decision scores (ρ = -0.034, p = 0.789), or frequency of financial-content consumption through social media and investment decision scores (ρ = 0.162, p = 0.218) at the 5% level of significance. Thus, the study does not find sufficient evidence to reject the respective null hypotheses. The findings suggest that the frequency of exposure to financial content on social media, considered in isolation, may not adequately explain variation in mutual fund investment decision scores. The study highlights the importance of examining the quality and credibility of digital information, investor characteristics and behavioural factors in future research.
Keywords: Retail Investors; Mutual Funds; Social Media; Investment Decisions; Finfluencers; Behavioural Finance; Mumbai and Thane.
Cite as
Ms. Shivani Pandya, & Dr. Kedar Bhide. (2026). Social Media and Mutual Fund Investment Decision-Making among Retail Investors: Evidence from Mumbai and Thane. International Journal of Arts, Social Sciences and Humanities, 04(04), 251–259. https://doi.org/10.5281/zenodo.23210051
Ms. Ajab Tinwala, and Mr. Ravi Singh
Page 260 - 271
Abstract
Artificial intelligence has been one of the most prominent forces which have entered the marketing world recently. The force of being able to make recommendations to individuals, deploy chatbots while assisting them, create AI generated ads and analyse past data to predict future patterns has fundamentally changed the way in which modern consumers are engaged and influenced. This paper attempts to establish if there is a significant relationship between consumer perception towards the use of artificial intelligence in marketing and their acceptance of such marketing approaches amongst college students.
A questionnaire was administered to one hundred and fifty college students using a five point likert scale. Analysis was done using the SPSS statistical tool. Two of the study’s main constructs Perception of AI powered marketing and acceptance of AI powered marketing together with the student’s age, gender, year of study and level of online interaction with brands were determined and subjected to statistical analysis. Descriptive statistics, cronbach’s alpha test, pearson’s correlation, linear regression, independent sample t-test and ANOVA were performed on the dataset.
The study established that both constructs were positively highly reliable (Perception α = 0.913; Acceptance α = 0.969). Additionally, the study established that the two constructs were moderately positively correlated with each other (r = 0.619, p < 0.001), thus rejecting the null hypothesis. However, the study noted that the acceptance of AI powered marketing was highly dependent on the frequency of online shopping for students (ANOVA p < 0.001), though gender and age had no significant effect on either perception or acceptance of AI powered marketing.
The study ultimately concludes that perception greatly influences the general acceptance of AI powered marketing by college students. The paper provides some suggestions on how marketers could make better impressions on customers’ perceptions of AI powered marketing.
Keywords: Artificial Intelligence; AI Powered Marketing; Perception & Acceptance.
Cite as
Ms. Ajab Tinwala, & Mr. Ravi Singh. (2026). Consumer Perception Towards AI-Powered Marketing: A Study Among College Students. International Journal of Arts, Social Sciences and Humanities, 04(04), 260–271. https://doi.org/10.5281/zenodo.23212121
Mr. Ganesha Gundu, and Mr. Ravi Singh
Page 272 - 281
Abstract:
Artificial Intelligence (AI) and Green Finance have emerged as two of the most important forces that have the potential to drive the world towards a sustainable economy. The current paper attempts to explore the role of AI and Green Finance in promoting and supporting a sustainable economy with reference to building a Viksit Bharat 2047. A survey was conducted among 160 respondents, with the results analysed using descriptive statistics, reliability analysis, correlation, regression, and an independent-samples t-test. The results demonstrated that the population studied had a generally positive perception about how AI can support Green Finance and lead the economy towards sustainability. The analysis identified strong awareness about AI as the biggest predictor of increased perception of the integration of AI and Green Finance (r = 0.78, p < .001). Additionally, participants who were aware of Green Finance had significantly higher scores for the perceived level of integration than those who were not (t = 2.65, p = .009). As such, there is reason to reject the null hypothesis, which claimed that there is no connection between the two concepts. Finally, the paper provides recommendations that financial institutions, regulators, and educators can consider in order to promote and support responsible and AI-enabled Green Finance.
Keywords: Artificial Intelligence, Green Finance, Sustainable Economy, ESG, Sustainable Development Goals, Viksit Bharat 2047
Cite as
Mr. Ganesha Gundu, & Mr. Ravi Singh. (2026). A Study of Artificial Intelligence and Green Finance: Building A Sustainable Economy. International Journal of Arts, Social Sciences and Humanities, 04(04), 272–281. https://doi.org/10.5281/zenodo.23242281
Dr. (CA) Nishesh S Vilekar, Ms. Manmeet Kaur
Page 282 - 288
Not Available
Cite as
Dr. (CA) Nishesh S Vilekar, & Ms. Manmeet Kaur. (2026). An Empirical Study on Awareness and Adoption of AI-Based Accounting Software Among Accountants. International Journal of Arts, Social Sciences and Humanities, 04(04), 282–288. https://doi.org/10.5281/zenodo.23243070