Creating an AI Academy

Session Resources + Slides

Summary

Creating an AI Academy is essential for organizations aiming to scale AI skills across their workforce. This session is designed for learning and development professionals, business leaders, and AI enthusiasts.

Richie Cotton and Marcela Schrank explore the challenges and strategies involved in building an AI Academy within an organization. They discuss the importance of aligning AI training with business goals, ensuring compliance, and promoting a culture of continuous learning. Marcela, with her extensive experience, emphasizes the need for a comprehensive approach that includes executive buy-in, personalized learning paths, and community building. The session highlights the shift from traditional data skills to AI fluency, the importance of measuring training impact, and the role of curiosity in driving engagement. Real-world examples and practical insights are shared to guide organizations in successfully implementing AI training programs.

Key Takeaways:

• AI training should be aligned with business goals and involve executive buy-in.
• Customized and domain-specific learning paths are crucial for effective training.
• Building a community and celebrating success enhances engagement and motivation.
• Compliance and ethical considerations are vital in AI training programs.
• Measuring the impact of training requires a multi-level approach.

Detailed Insights

Aligning AI Training with Business Goals

Aligning AI training with business objectives is key for demonstrating its value and securing executive support. Marcela emphasizes the importance of conducting a maturity assessment to identify AI pockets within the organization. This helps in determining which roles and functions require prioritization in terms of upskilling. By aligning training with critical business use cases, organizations can ensure that AI initiatives contribute to strategic goals. Marcela notes, "Identifying critical use cases should be part of your scope definition and goals because it will also determine how you measure success."

Customized Learning Paths

Customized and domain-specific learning paths are essential for effective AI training. Marcela highlights the shift from general AI education to more focused programs that address specific roles and functions. This approach ensures that employees acquire relevant skills that can be directly applied to their jobs. She shares an example from her experience at Allianz, where functionally specific learning content was developed by connecting technical experts with instructional designers. This collaboration resulted in specialized curricula that met the unique needs of different departments.

Building a Community and Celebrating Success

Creating a sense of community and celebrating achievements are key strategies for maintaining engagement in AI training programs. Marcela discusses the use of open house events, competitions, and graduation ceremonies to encourage a culture of learning. These initiatives not only motivate participants but also help build connections across different geographies and roles. "We found there were so many different people connected by this joint topic of data and today AI," Marcela explains, highlighting the importance of skill-based interactions in building a supportive community.

Compliance and Ethical Considerations

Ensuring compliance and addressing ethical considerations are vital components of AI training programs. Marcela stresses the importance of training employees on data privacy, security, and biases to mitigate compliance risks and protect the organization's reputation. She notes that upskilling in these areas is not optional but a necessity, as it helps prevent potential legal and ethical issues. By embedding these topics into the training curriculum, organizations can ensure that employees are well-equipped to handle AI technologies responsibly.