Partner Training - Advantages of Gen AI with Data Intelligence

Generative AI (GenAI) is changing business by moving from general, broad models to specialized, data-driven systems that solve real problems. The focus is on building AI “agents” that can use company data, perform tasks, and continuously improve, all while keeping data secure and following rules. Real-world examples from industries like finance, telecom, and healthcare show how GenAI boosts productivity, reduces costs, and helps people work smarter.

Desired Learning Outcomes:

• Specialization Matters: GenAI is most valuable when tailored to specific business needs and data, not just general knowledge.

• AI Agents Are the Future: Instead of relying on one big AI model, companies build systems of smaller agents that work together, use tools, and handle complex tasks.

• Continuous Improvement: AI systems get better over time by learning from user feedback and real-world use, not just from training data.

• Data Security and Governance: Keeping data private and following rules is essential for building trust and making AI work safely in business.

• Standard Patterns and Tools: There are proven ways to set up, monitor, and improve GenAI systems, making it easier for businesses to adopt and scale AI.

• Common Use Cases: GenAI is used for:

  • Turning messy documents into structured data (document processing)

  • Letting people search and ask questions about company knowledge (knowledge search)

  • Detecting fraud and risks faster (fraud detection)

  • Automating routine tasks so people can focus on creative work

• Preparing for the Future: Success with GenAI means investing in your own data, using secure platforms, and being ready to adapt as technology evolve.