The data-driven economy is transforming with data centers becoming a crucial business infrastructure. However, the increasing reliance on data centers is posing a threat to the environment. Climate change activists are focusing on reducing emissions from sectors like automotive, aviation, and energy. Data centers consume more electricity than the UK, accounting for 3% of global electricity supply and 2% of total greenhouse gas emissions. By 2040, digital data storage is projected to contribute to 14% of the world's emissions. The number of data centers worldwide has surged from 500,000 in 2012 to over 8 million, with energy consumption doubling every four years. The rise in internet penetration rates and the introduction of 5G technologies and IoT devices will further exacerbate the issue, increasing the demand for data processing.

In this cashless economy era, Information and Communication Technology (ICT) plays a vital role in making payments using various payment modes. The mobile wallet app is an innovative technology for avoiding the usage of physical cash. The mobile wallet records all kinds of transactions with a clear payment reference and makes it accountable for tax payments. There are countless reasons for using mobile wallets which makes service providers confused and leads them to offer unattractive features in the wallet apps making the offer as a failure. This paper attempts to collect the data from the mobile wallet users and provide a clear understanding of the reasons for using mobile wallets. Secondly, the customer preferences towards Google Pay and PayTm are analyzed in detail with primary data collected from mobile wallet users to suggest a model for improving the business. This research was conducted to understand the customer's inclination towards the use of mobile wallets.

Businesses that engage in sustainable marketing can benefit both the world and their bottom line. Earlier, companies could satisfy many customers by simply providing low pricing and high-quality goods. However, people's concern for the environment and other social concerns have grown, and so has their desire to support groups that share their beliefs. Because they often generate strong market returns and demonstrate durability during economic downturns, many investors want to support businesses that use sustainable business methods. Also, these businesses are more likely to comply with social and environmental laws. Several companies use sustainable marketing to succeed in today's ethical and ecologically sensitive marketplace. Organizations must finance sustainability programs in order to practice sustainable marketing. But, it can also improve employee engagement, promote regulatory compliance, raise revenues, and build brand loyalty.

Data centers and transmission networks are crucial in the digital age, with the market expected to grow from $50 billion in 2021 to $120 billion by 2030. However, their extensive computing infrastructure and continuous operation generate significant heat, necessitating energy-intensive cooling systems. The IEA report revealed that data center power consumption surged by over 60% between 2015 and 2021, with transmission networks experiencing a 60% usage increase. Addressing these growing energy demands poses significant challenges for the industry, with some countries considering restrictions on new data center licenses due to environmental concerns. To mitigate the climate impact, the industry must prioritize the procurement of low-carbon or carbon-free electricity to reduce Scope 2 emissions related to electricity, heating, and cooling. Tech giants like AWS, Google, and Meta/Facebook have already adopted ambitious public targets, either running on carbon-free electricity or investing in global projects for cost-effective and large-scale emissions reduction.

AI-driven decision-making tools have emerged as a novel technology poised to replace traditional agricultural practices. In this chapter, AI's pivotal role in steering the agricultural sector towards sustainability is highlighted, primarily through the utilization of AI techniques such as robotics, deep learning, the internet of things, image processing, and more. This chapter offers insights into the application of AI techniques in various functional areas of agriculture, including weed management, crop management, and soil management. Additionally, it underlines both the challenges and advantages presented by AI-driven applications in agriculture. In conclusion, the potential of AI in agriculture is vast, but it faces various impediments that, when properly identified and addressed, can expand its scope. This chapter serves as a valuable resource for government authorities, policymakers, and scientists seeking to explore the untapped potential of AI's significance in agriculture.

AI-powered decision-making instruments are cutting-edge technology that has the potential to displace conventional banking procedures. This chapter emphasizes the critical role artificial intelligence (AI) has played in guiding the banking industry toward expansion. AI techniques including robotics, deep learning, facial recognition, natural language processing, and more are used to achieve this goal. This chapter provides an overview of the use of AI approaches in several banking functional domains, such as loan approval, customer lifecycle management, customer services, alarm systems, and so on. It also highlights the benefits and difficulties that AI-driven financial apps provide. In summary, artificial intelligence (AI) has enormous promise in banking, but it also confronts several obstacles that, if correctly recognized and overcome, might broaden its use. This chapter is an invaluable tool for researchers, lawmakers, and bank officials who want to learn more about the unrealized potential of artificial intelligence in banking.