AI will personalize marketing. Analysis of client behavior and preferences customizes product and service suggestions. AI-powered CRM solutions can automate customer service, help customers, and boost satisfaction. AI improves marketing targeting. Technology can improve client behavior targeting. AI will also impact digital marketing. Personalization boosts client engagement and sales. Virtual assistants and chat bots will increase marketing. Apps can swiftly answer customer questions, improve service, boost satisfaction, and develop brand loyalty. AI can enhance price by studying market trends, competition, and customer behaviour. Machine learning algorithms help organizations set rates, increasing sales and profit. Marketers may create more engaging content with AI. AI can analyze client data and behavior to determine which content performs best for target demographics, improving content marketing. AI marketing will develop in the future. Companies will benefit from AI-powered, tailored, and data-driven marketing that boosts customer engagement, loyalty, and revenue.

The phrase “digital learning” refers to any type of learning that uses technology in its broadest sense. Hence, everything that involves digital platforms, tools, systems, and applications used by learners is considered to be part of digital learning. This suggests that using digital tools and gadgets in a traditional classroom while attending online classes, conducting internet research, watching online videos, or communicating in person with their instructor are all considered kinds of digital learning. It varies from online learning in that the latter only comprises learning via the internet. The former is a more general term that includes employing digital devices, software, and applications in addition to the Internet. For learning and communication during online learning, utilize the m.geetha@sru.edu.in internet. Online learning is thus an option when the teacher, students, and both are present in the same location.

Recently, machine learning-based task automation framework have been gaining attention in human resource management of Multi-National Companies (MNCs). Task automation framework helps MNCs to automate repetitive HR tasks, analyse data quickly and accurately, forecast workforce, and recognize employees. MNCs are now beginning to use ML algorithms in combination with Artificial Intelligence (AI) to streamline the HR processes. Most MNCs have large-scale operations and decentralized organization structures which put additional pressure on HR teams to carry out intricate and tedious manual processes. To ease the process, ML-based task automation framework facilitates HR teams to leverage the power of AI and perform HR management tasks in a more effective and efficient manner. The ML-based task automation framework utilizes automation bots which can simulate all processes of HR management such as recruitment, time attendance, tracking employee records, scheduling calendar, and office administration tasks. The machine learning-based task automation framework utilizes predictive analytics to identify trends, patterns, behaviour, anomalies, and important insights from the large volumes of structured and unstructured data.

Science increasingly acknowledges technology's environmental impact. Artificial intelligence has the greatest transformational potential. This study uses AI to provide sustainable, eco-friendly solutions. The report covers climate change, pollution, and resource depletion worldwide. These difficulties inspire change, and the chapter suggests using AI to invent solutions. Numerous case studies demonstrate how AI may help environmental sustainability. Waste management, energy efficiency, biodiversity management, and natural catastrophe prediction are examples. Each case study explores AI principles, problems, and sustainability. In the next section, the chapter discusses AI's ethical and practical implications. These concerns include data privacy, AI inclusion, and automation-related job loss. It provides well-defined legal frameworks and AI integration with other tech and societal solutions. The chapter finishes with AI's future in sustainable development. Governments, AI developers, and the public must collaborate to achieve AI's potential.

AI employs complex algorithms and processing power to mimic human reasoning and perform tasks like recognition, interpretation, and decision-making. Artificial intelligence is helping more commercial and industrial sectors boost capacity, optimize operations, and provide better products and services to customers. Tourism has being transformed by AI. The travel industry has created adaptable and responsive environments using AI, machine learning, and deep learning to meet customer needs. The chapter discusses how artificial intelligence (AI) is being used in tourism to enable information processing, intelligent predictive applications, social media opinion deciphering, accommodation, personalized experiences, and destination management. AI's real-time data analysis has revolutionized how travelers plan and start their trips. AI will likely improve traveler experiences and sector organizations' management and services. AI-powered technology also assigns realistic responsibilities to employees, saving time, money, and effort, allowing firms to establish more competitive rates.

Computers are part of our everyday life. Advances in technology allow these machines to duplicate human skills with remarkable accuracy. AI managed all global business functions. Progress is mostly due to AI. Using AI, computers can automate human work. Many organizations employ AI to simplify. Business uses it extensively. Companies use AI to automate, analyze, and interact with consumers and workers. Companies want market domination and industry growth. Business insights are gained by many successful global firms using AI, automation, big data analytics, and NLP. AI is transforming business by automating processes, analyzing data, improving decision-making, and connecting customers. AI may improve corporate chatbots, inventory management, fraud protection, and predictive maintenance. AI can raise productivity, cut expenses, and increase profits by speeding up procedures and enhancing customer service. However, businesses must use AI responsibly and protect data. This chapter discusses AI's business impacts.