Enterprise AI
Program

My approach is informed by research into past technological transitions. Analysis of the printing press, the industrial revolution, and the internet reveals consistent patterns.

Historical Pattern: (1) Transformative technology emerges that can significantly increase productivity. (2) Early adopters benefit while others lack awareness of opportunities. (3) Stakeholders act independently—educators, businesses, communities, and government operate in silos. (4) Gaps can persist—communities without coordinated support face barriers to participation.

AI exhibits similar patterns at accelerated pace. By applying lessons from history, I'm taking proactive steps to ensure inclusive access to AI education and opportunity. Evidence-based coordination among stakeholders creates the most equitable outcomes.

Technical Research Focus: Advanced ETL pipelines combining LLMs and machine learning for NLP and knowledge graph construction. RAG workflows for personalized knowledge production. AI-augmented QA review systems. Generative AI techniques for training, augmenting, and automating software engineering processes.

"AI will democratize access to specialized knowledge and skills. The age of AI will challenge long-held assumptions about education, work, and expertise."

Success in this era requires not just technical literacy, but communication, collaboration, accountability, and strategic thinking. The Enterprise AI program develops all these capabilities through integrated coursework that mirrors real-world professional environments.