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“Machine learning (ML)” in business aids in increasing company scalability and boosting company operations for businesses all over the world. “Artificial intelligence (AI)” technologies and several “ML” algorithms have grown in prominence in the business analytics sector. In the era of a huge quantum of data being generated by the virtue of the integration of the various software with the business operations, the relevance of “ML” is continuously increasing. As a result, companies may now profit from knowing how companies may use “ML” and incorporating it into their own operations. “ML” derives useful results from the data to address very dynamic and difficult social and business problems. ML helps in establishing a system that learns automatically and produces results in less time and effort, allowing machines to discover. ML is developing at a breakneck pace, fuelled mostly by new computer technology to competitive advantages during the COVID pandemic.

For firms all around the world, “ML” in business aids in expanding scalability and boosting operations. In the field of business analytics, artificial intelligence (AI) and machine learning (ML) algorithms have become increasingly popular. The importance of “ML” is growing in an era when a massive amount of data is generated as a result of the integration of various applications with company activities. As a result, businesses can now benefit from understanding how other businesses are using “ML” and adopting it into their own operations. In order to handle very dynamic and demanding societal and business challenges, machine learning (ML) extracts valuable results from data. Machine learning (ML) aids in the development of a system that learns automatically and generates outcomes with less time and effort, allowing machines to discover. ML is progressing at a dizzying pace, fueled primarily by new computer technology and used to gain competitive advantages during the COVID pandemic.

According to a new study published by the Accenture Institute for High Performance, “AI” might double yearly economic growth rates in several wealthy nations by 2035. With broad AI deployment, the yearly growth rate in the USA increased from 2.6% to 4.6%, resulting in an extra $8.3tn. In the UK, AI may contribute $814bn to the economy, raising the yearly growth rate from 2.5% to 3.9%. The authors are already in a business period when huge technological development is assisting us in addressing a variety of difficulties to achieve maximum development. AI technology has enormous developmental consequences. In addition, big data analytics is helping to make AI more enterprise ready. Future developments in “ML” cannot be understated. Machines will very certainly eventually be smarter than humans in practically every way.

The introduction of AI into the market has enabled small businesses to use tried-and-true strategies for achieving greater business objectives. AI is continually offering a competitive advantage to start-ups, whilst large corporations provide a platform for building novel solutions. AI has become an integral component of reality, from functioning as a robot in a production unit to self-driving automobiles and voice activated resources in complex medical procedures. As a consequence, solving the difficulties highlighted below and finding out how to collaborate with robots will be a constant problem for the human species (Sujaya and Bhaskar, 2021).

Plastic waste is one of the long-standing global issues in the recent era. Unfortunately, India is one of the countries which has been affected by the mismanagement of the use of plastics. India has recorded a substantial growth in the production of plastic and is considered a country of increased consumption of plastic. Due to the absence of an appropriate waste collection and segregation process, it has created the major issue of waste management and discarded used plastic items used for packaging application. There are various plastic waste management laws and programmes that have a cascading effect on almost every sector of business. In 2016, two years after the new union government took power in New Delhi, The Ministry of Environment, Forest and Climate Change (MoEFCC) has made some improvements in rules for the collection, segregation, processing, treatment and disposal of the waste. In the pandemic era, effective plastic waste management became more important than ever. The COVID-19 pandemic has created an increased demand for single-use plastic because of pressure on the already out-of-control global plastic waste problem. It is recorded to be large, and the magnitude of this pandemic related to mismanaged plastic waste is unknown. However, understanding the changing landscape and alarming need for effective plastic waste management, the government of India has proposed certain changes to prohibit imports, handling, manufacturing and use of single-use plastics in the country. This is in line with the government's intent to phase out single-use plastic by 2022. Considering this, this chapter highlights the changes in the rules and regulations in India related to plastic waste management and its effects on various sectors of business.

This case discusses the issue and challenges faced by MoveInSync during the COVID-19 pandemic lockdown and its Corporate Social Responsibility (CSR) initiative that contributed to the employees’ wellbeing. India was significantly hit by the pandemic and the impact has been severe. The corporate sector of India irrespective of the company size has worked for hand in hand with the government to contribute to handling the pandemic. One such company is MoveInSync which offers transport and security operations to enhance employee commute space. Despite the COVID-19 pandemic severely impacting their business operations, MoveInSync continued its CSR effort to help the needy and cared for its own employees.