How to Successfully Scale GenAI in Big Organizations

Overview

Discover how Deloitte scales GenAI from proof of concepts to impactful business solutions, addressing blind spots and showcasing live demos of successful implementations for large organizations.

Syllabus

• Introduction to Scaling GenAI in Big Organizations
Overview of GenAI and its potential in large enterprises
Key challenges in scaling AI solutions
• Proving the Concept: From Idea to Pilot
Identifying viable AI projects within your organization
Designing and executing proof of concepts (PoCs)
Evaluating PoC success and value proposition
• Infrastructure and Technology Considerations
Choosing the right platforms and tools for scalability
Data management strategies for scaling AI
Integrating GenAI into existing IT infrastructure
• Building a Cross-Functional Team
Roles and responsibilities for scaling GenAI
Skills and training necessary for team members
Facilitating effective communication and collaboration
• Governance and Ethical Considerations
Establishing AI governance frameworks
Addressing ethical concerns and bias in AI models
Compliance with regulations and data privacy standards
• Implementing GenAI at Scale: Strategies and Case Studies
Transitioning from PoCs to full-scale deployments
Overcoming common barriers to scaling
Live demos of successful GenAI implementations in large organizations
• Monitoring, Maintenance, and Continuous Improvement
Setting KPIs and measuring the impact of GenAI solutions
Ongoing model monitoring and lifecycle management
Continuous feedback loops for improvements
• Addressing Blind Spots and Mitigating Risks
Identifying and addressing common blind spots in AI projects
Risk management strategies in AI deployments
Lessons learned from past implementations
• Future Trends and Innovations in GenAI
Emerging technologies influencing GenAI scalability
Preparing your organization for future AI advancements
• Conclusion and Key Takeaways
Recap of critical success factors for scaling GenAI
Actionable insights and next steps for participants
• Interactive Q&A and Final Thoughts
Open floor for questions and discussion
Sharing of personal experiences and insights

Subjects

Computer Science