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AI For Business is simple version For S.Y.B.C.A(NEP 2020) 224F: AI for Business – II "AI for Business" would introduce Artificial Intelligence as a transformative technology with the potential to...

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AI for Business – II
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AI For Business is simple version For S.Y.B.C.A(NEP 2020) 224F: AI for Business – II "AI for Business" would introduce Artificial Intelligence as a transformative technology with the potential to significantly impact businesses by enhancing efficiency, improving customer experiences, and driving innovation. It would outline that AI uses machine learning and data analysis to automate tasks and provide insights, offering benefits like deeper customer understanding and competitive advantage. The preface would also acknowledge the challenges and ethical considerations of AI adoption and the importance of preparing the workforce to leverage these new tools for sustainable growth.
The Role of AI in Modern Business: AI is fundamentally changing how businesses operate by integrating advanced technologies such as machine learning, natural language processing, and computer vision into daily operations. These technologies allow businesses to:
• Enhance Operational Efficiency: Automate routine tasks, reduce operational costs, and increase productivity by enabling faster and more accurate processes.
• Improve Decision-Making: Use predictive analytics to forecast trends, optimize supply chains, and make data-driven decisions that align with business goals.
• Personalize Customer Experiences: Leverage AI to analyze customer data and behavior, enabling personalized marketing, recommendations, and customer support.

1. AI in Business Operations and Automation.....................................7
• AI in supply chain management and logistics
• Robotic Process Automation (RPA) basics (e.g., invoice processing, customer onboarding)
• AI in CRM systems (personalized responses, lead scoring)
• Use of AI chatbots for customer service
• Business workflow automation tools: Zapier, Microsoft Power Automate
2. AI for Business Decision Support.....................................36
• Data-driven decision-making using AI dashboards
• Introduction to predictive analytics and forecasting tools
• AI in financial analysis: fraud detection, credit scoring
• AI in HR: candidate screening, sentiment analysis in feedback
• Use of Google Looker Studio / Tableau Public for basic AI-driven reports
3. AI Use Cases and Sectoral Applications.......................94
• Retail: product recommendations, inventory prediction
• Banking: AI-powered loan approvals, robo-advisors
• Education: personalized learning platforms
• Healthcare: AI-assisted diagnostics and scheduling
• Capstone mini-project: Create a basic AI-enabled business model for any one sector

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