The transformative impact of artificial intelligence (AI) in green finance is revolutionizing the landscape of sustainable development in India. This chapter explores how AI-driven technologies are enhancing the efficiency, transparency, and effectiveness of green finance initiatives. By leveraging advanced data analytics, machine learning algorithms, and predictive modeling, AI is facilitating better decision-making, risk assessment, and investment strategies that align with environmental, social, and governance (ESG) criteria. The integration of AI in green finance is not only accelerating the transition to a low-carbon economy but also promoting inclusive growth and resilience against climate change. This study highlights key case studies, technological innovations, and policy frameworks that demonstrate AI's potential as a catalyst for achieving India's sustainable development goals. Through comprehensive analysis, the chapter underscores the critical role of AI in driving systemic changes in financial practices, thereby fostering a sustainable and prosperous future for India.

Artificial intelligence (AI) is becoming an inseparable part of our daily lives as it can solve tough problems in a competent way in manifold areas like bank, insurance, healthcare, education, operations, etc. This chapter explains how financial institutions are implementing AI, algorithm trading, and intelligence that is adaptive to their financial processes. The banking sector in India has gone through significant transformations with the infusion of technology. Technological innovation has played a crucial role in reshaping the landscape of banking operations, bringing about positive changes in various aspects such as cost effectiveness, productivity and efficiency, small value transactions, digital payment systems, mobile banking apps, and online transfers. Adoption of technology has given customers a wide range of choices in terms of banking services from online banking to mobile apps.

Purpose : This study examined how trade openness interacted with foreign direct investment (FDI) within G20 countries and analyzed their combined impact on GDP growth. It aimed to explore immediate and long-term relationships to inform sustainable growth strategies. Design/Methodology/Approach : The analysis employed the autoregressive distributed lag (ARDL) methodology, complemented by Johansen cointegration tests, vector error correction model (VECM), and Granger causality tests for robustness. Time-series data from the World Development Indicators (WDI) were used to assess the effects of trade openness on FDI inflows and GDP growth across G20 nations. The study considered data from 1990 – 2019. Findings : The findings indicated that trade openness maintained a long-run equilibrium relationship with GDP, highlighting that liberal trade policies contributed positively to FDI and economic performance. However, the short-run dynamics were marked by instability due to geopolitical uncertainties, exchange rate fluctuations, and institutional weaknesses. The results also revealed immediate causal linkages between trade openness and GDP. Practical Implications : The results suggested that G20 policymakers should prioritize reducing non-tariff barriers and improving regulatory transparency to attract FDI and sustain growth. The ARDL-based insights provided concrete guidance for shaping effective trade and investment strategies. Originality/Value : This research used advanced panel econometric techniques to offer empirical evidence of time-dependent, reciprocal relationships between trade openness, FDI, and GDP growth. It contributed to the trade-growth literature by clarifying how trade liberalization could drive growth via investment channels and institutional reform.

This article discusses the question, does trade openness (TO) lead to economic growth in the Quadrilateral Security Dialogue (QUAD) countries (including the USA, Japan, India and Australia). Being driven by the paucity of the existing empirical data that targets QUAD countries as a strategic economic bloc, thus the study fills a valuable gap in the work on trade and economic growth. For the filling gap, this article studied a panel data set for 23 years (2000–2022). The analysis comprises a combination of both short and long-run dynamics of the variables using annual panel data through the autoregressive distributed lag (ARDL) framework, including pooled mean group (PMG), mean group (MG) and dynamic fixed effects (DFE) estimators. The empirical findings indicate that TO and foreign direct investment (FDI) inflows have positive and significant effects on economic growth in the long run and the macroeconomic stability, which is indicated by the controlled inflation and proper reserves, has a complementary effect. It has been found that the PMG estimator is the most efficient, which means that there are homogeneous long-run relations over all the economies of the QUAD countries with heterogeneous short-run adjustment. These results are solid arguments that trade-led growth theory applies in relation to developed and emerging markets in the framework of QUAD countries. The results point to trade liberalization, FDI magnetism and exchange rate stability as essential drivers of sustained economic growth. Policymakers can use them to create targeted policies that are less likely to drive trade barriers, create investor-friendly conditions, and stabilize the monetary balance. This study also points to the importance of restrained inflation and institutional transparency in long-term economic resilience and stability.

Nature-based tourism is gaining popularity as people seek meaningful experiences that combine adventure, leisure, and personal growth. This study explores how novelty, self-improvement, nature connection, knowledge, fitness, and escape influence tourists' perceptions in ecotourism. This study offers a thorough framework for comprehending tourist pleasure and engagement by combining several definitions of nature-based tourism and examining these motivating factors. SEM was used to analyze the relationship among the factors and the indicators. The results indicate that all four motivating elements have a major influence on travelers' overall opinions, highlighting their need for unusual experiences, closer linkages to the natural world, opportunities for personal growth, and a break from everyday life. These observations emphasize how crucial it is to provide tourist experiences that satisfy the psychological and emotional requirements of visitors. Offerings that are in line with the reasons behind travel can improve tourist experiences, encourage brand loyalty, and guarantee sustainable tourism growth, all of which are advantageous to industry stakeholders and long-term viability. This study has important ramifications for legislators, tourism planners, and destination marketers, recommending that ecotourism destinations modify their offerings to improve tourist pleasure and encourage environmentally friendly travel methods.

The primary area of tourism that is considered for the study revolves around nature based tourism which is highly prevalent in the present times. India is naturally endowed with flora and fauna which allows it to promote nature base to raising across tourists around the world. .The study here however considers the region of East Khasi Hills in Meghalaya to be investigated specifically as a part of this quantitative study. The region has shown tremendous tourist footfalls in the past few years and holds the potential of being one of the prominent nature based tourism spots. There are 395 primary responses collected from tourists who have been to make earlier in the past years. The collected data has been analysed using appropriate statistical tools which has led to the identification of the factors established in the study. The overall perception held by the respondent towards the region has been estimated by understanding their social media engagement, the information quality on social media and the social media influence on them. The role of trust has been established as important when considering the social media information by researchers and this study has also found the impactful role of it. The trust on the social media information generated and used for the purpose of tourism can effectively mediate the relationship between the overall perception derived and the established independent variables. The partial mediation reflects that the rule of trust can be significant when trying to establish the perception about nature-based tourism spots using social media.