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Artificial Intelligence

How Leaders Build AI Skills at Scale

October 2025

Seu(s) apresentador(es)

Amber Marcu

Sr Director of Digital Skills & Capabilities at Bristol Myers Squibb

Colleen Young

Data Science & Digital Fluency Strategist at Bayer

Dr. Colleen B. Young is a Data Scientist who specializes in strategizing digital modernization and transformation at companies. She received her B.A. in Anthropology from the University of California at Berkeley and a Ph.D. in Biological Anthropology from the University of Missouri, where she contributed to understanding the biological and behavioral corollaries of living in island environments. She currently works at Bayer where she identifies employee data science and digital fluency training needs to maintain company progress as a leader in solving the complex issue of Hunger for None and Healthcare for All. She supports curriculum development and delivery in science, technology, and data asset platforms and strategies. Her close partnership with DataCamp is an integral resource to support and expand this initiative at Bayer.

Andy Eyherabide

Chief AI Officer at Wizeline

Session Resources

Summary

How Leaders Build AI Skills at Scale is a session designed for professionals interested in enhancing AI capabilities within their organizations. The discussion explores the practicalities of implementing AI training programs across diverse industries. It highlights the importance of identifying specific skill needs based on roles, promoting engagement, and measuring the return on investment. Leaders from Bristol Myers Squibb, Bayer, and Wiseline share their experiences in scaling AI skills, emphasizing the need for customized learning paths and executive sponsorship. They discuss the challenges of keeping employees engaged amidst other work commitments and the significance of aligning AI training with business goals. The session also touches on the use of AI to automate processes and improve productivity, showcasing real-world applications and success stories.

Key Takeaways:

AI training should be customized to specific roles and business needs.
Executive sponsorship is essential for successful AI skill scaling.
Engagement can be enhanced through mentorship and real-world applications.
Measuring ROI involves both quantitative and qualitative assessments.
AI can be a transformative tool across various business functions.

Insights

Customizing AI Training to Roles

Understanding who needs what skills is fundamental to effective AI training. Amber Marcu from Bristol Myers Squibb emphasizes the use of personas to identify training needs across different functions. By conducting needs assessments and leveraging self-assessments, organizations can personalize learning paths. This approach ensures that scientists, business professionals, and IT staff receive relevant training, enhancing their ability to apply AI in their specific roles. The use of tools like DataCamp's skill assessments allows for continuous refinement of training programs, ensuring they remain aligned with evolving business needs.

Importance of Executive Sponsorship

Executive sponsorship plays a key role in the success of AI training programs. Amber Marcu highlights the impact of having support from top-level executives, including the CEO and CTO, at Bristol Myers Squibb. This backing not only provides the necessary resources but also encourages a culture of learning and innovation. Leaders actively participating in training and sharing their experiences can inspire employees to engage with AI learning. The visibility of executive involvement highlights the strategic importance of AI skills development within the organization.

Engagement and Real-World Application

Keeping employees engaged in AI training amidst other commitments is a challenge. Colleen Young from Bayer discusses the effectiveness of mentorship and capstone projects in maintaining engagement. By integrating real-world applications and providing support through mentors, learners can transition from theory to practice. This approach not only enhances skill retention but also demonstrates the tangible benefits of AI training. The use of capstone projects allows employees to apply their learning to actual business challenges, reinforcing the relevance of their new skills.

Measuring Return on Investment

Calculating the ROI of AI training involves a mix of quantitative and qualitative measures. Colleen Young mentions the use of post-course surveys to assess productivity gains and career advancement. These surveys provide insights into the practical impact of training on employees' work. Amber Marcu adds that tracking utilization and engagement metrics helps demonstrate the ongoing value of training programs. While hard numbers are important, understanding the broader impact on employee capabilities and business outcomes is vital for justifying the investment in AI skills development.