Christopher is a Senior Director Analyst covering artificial intelligence and analytics. His research focuses on AI strategy, economics, governance, and related topics in Data Science and Machine learning. He advises data, analytics, and AI leaders on the strategic, economic, and technical decisions involved in developing, governing, and scaling enterprise AI and Machine Learning applications. His background spans economics, data science, and hands-on AI engineering, with expertise in machine learning, knowledge representation, and causal inference.
Prior to joining Gartner, Christopher held leadership and technical roles spanning AI strategy and consulting, data science, machine learning and AI engineering. His work included advising organizations on AI strategy, governance, and operating models; designing and implementing machine learning and generative AI solutions, leading data science and AI product initiatives; and conducting applied economic and quantitative research. He has also taught at the university level and published peer reviewed research.
AI, Agents and Analytics
Enterprise AI Strategy
AI Governance
Ph.D. in Economics, Georgia Tech
M.S. in Economics, Georgia Tech
B.B.A. in Economics, Kennesaw State University
AI Strategy, Economics, Operating models
AI Governance
AI Value Realization
AI/ML/DS Algorithm Development and Evaluation
AI Agents, Agentic Systems, and Knowledge Representation