Jim Young is Global Chief Data Officer at American International Group (AIG), where he leads the architecture, development, and advancement of the company’s global data and analytics capabilities. With more than 25 years of experience across banking, consulting, and insurance, Jim has built a career focused on translating data strategy into measurable business outcomes.
Jim began his career as a financial analyst at US Bank, where he was responsible for financial, operational, and marketing campaign analysis supporting telemarketing and direct mail operations. Working as an early business user of data exposed him to the complexity and potential of integrating disparate datasets to generate stronger insights and more effective decision-making.
He later moved into management consulting, leading initiatives to implement data analytics capabilities for large financial services organizations. After a brief experience in the start-up world, Jim joined Allstate, where he led the creation of one of the world’s first business intelligence competency centers and oversaw data warehousing, data management, and database administration teams.
Over the following two decades, Jim held senior data and analytics leadership roles across the insurance industry, including positions at Travelers and AIG. At AIG, he leads global teams responsible for data architecture and engineering, data governance and management, data science and AI, and business insights and analytics across the enterprise.
Throughout his career, Jim has partnered closely with senior executives to embed data intelligence across organizations, improving financial performance, operational efficiency, and innovation at scale.
As a data and AI leader, which traits and skills do you think matter most, and which of those have been most influential for you in your current position?
“I believe that the combination of strong leadership skills such as the ability to attract and lead talent, the ability to build strong and trusting business relationships and the ability to dive into technical and complex detail with teams when needed are most essential to driving outcomes.
“As is often cited, success with data and AI is often more of a people problem than a technical problem. Therefore, a leader with strong people skills but is also credible with business and technical teams alike, is most effective.”
Reflecting on your career, what is one non-traditional piece of advice (outside of technical skills) you would give to an aspiring data or AI leader aiming for the C-suite?
“Focus on developing your leadership skills and understanding your strengths and weaknesses. Hire great people that you can trust to cover your weaknesses.”