Event Name: Generative AI Business Use Cases for Management Studies	Event Date: April-23-2024
Resource Person: Mr. Alok Gupta	Event Timings:3 pm to 5 pm
Number of Participants:300	Venue:Seminar Hall, Lloyd Campus 1

OBJECTIVE:

To provide an in-depth exploration of Generative AI (Gen AI) and its transformative impact across various business sectors. Management students were introduced to the potential of Gen AI to revolutionize traditional business practices and create new opportunities.

Key Learnings from the Expert Talk

Internet of Things (IoT)

• Integration of Gen AI with IoT is creating smarter ecosystems for businesses.
• Predictive maintenance and real-time analytics are some of the key benefits.
• Gen AI’s integration with IoT is paving the way for innovative applications. Businesses may boost productivity and spur innovation by utilizing real-time data from linked devices.

Synthetic Data

• Synthetic data is crucial for training AI without compromising privacy.
• It enables risk-free simulations and testing in various business scenarios.
• The use of synthetic data in business is gaining traction as it offers solutions to data privacy concerns and enables the training of machine learning models without compromising sensitive information.

Cloud Computing

• Cloud-based Gen AI services are making AI more accessible and scalable.
• They facilitate cost-effective and efficient data processing and storage solutions.
• Cloud computing has become a cornerstone for businesses, offering scalable and cost-effective solutions.
• Gen AI is enhancing cloud services by providing advanced data processing capabilities.

Prompt Engineering

• Prompt engineering is essential for directing AI to generate desired outcomes.
• It’s a skill that combines creativity with technical knowledge.
• Prompt engineering is emerging as a critical skill in business, particularly in software development. It involves crafting prompts that guide Gen AI models to generate useful outputs.

Gen AI in Business

• Gen AI is used for automated trading, fraud detection, and personalized financial advice.
• It’s transforming the fintech sector by adding efficiency and precision.
• In the fintech sector, Gen AI is being used to analyze market data, automate trading strategies, and provide personalized financial advice.

Gen AI in HR

• AI is streamlining recruitment processes and employee training.
• It’s also raising questions about ethics and workplace dynamics.
• HR departments are leveraging Gen AI for recruitment, employee engagement, and training, while also considering ethical implications and future trends.

Gen AI in Marketing

• Personalized content creation and customer insights are major applications.
• Gen AI is revolutionizing customer engagement and campaign management.
• Marketing teams are utilizing Gen AI to create personalized campaigns and content, analyze customer feedback, and drive engagement.

Gen AI in Sales

• AI tools are automating sales tasks and providing valuable customer insights.
• They’re enhancing the effectiveness of sales strategies.
• Gen AI is transforming sales processes by automating routine tasks, providing insights about customers, and supporting sales teams throughout the sales cycle.

Machine Learning

• Predictive analytics are being used for decision-making and strategy development.
• Machine learning is a key component of business intelligence.
• Machine learning is being applied across various business problems, offering predictive analytics for customer churn, fraud detection, and more.

Cyber- Security

• Gen AI is crucial for threat detection and automated security responses.
• It’s improving the resilience of businesses against cyber threats.
• Gen AI is enhancing cybersecurity by automating threat detection and response, thereby improving the overall security posture of businesses.

Ethics in AI

• The workshop highlighted the importance of ethical AI development and deployment.
• Issues like bias, fairness, and transparency were discussed.
• The workshop emphasized the importance of ethical considerations in the deployment of Gen AI, addressing issues such as bias, fairness, and data privacy.

Feedback

• The workshop was well-received, with participants appreciating the breadth of topics covered.
• Some attendees desired more hands-on examples and case studies.

Recommendation

• Future workshops could include interactive sessions with AI tools.
• Incorporating real-world case studies would provide practical insights into the applications of Gen AI.

Conclusion

The expert talk concluded that Gen AI holds immense potential for businesses. However, it also highlighted the need for responsible implementation and adherence to ethical standards to ensure sustainable and beneficial outcomes for all stakeholders.

This comprehensive overview provided management students with a clear understanding of how Gen AI can be applied in various business contexts, preparing them for the challenges and opportunities in the evolving landscape of AI in business.