Phil Loatman

About Phil Loatman

I lead AI initiatives at Lincoln Financial, where I\'m the technical lead for enterprise generative AI projects. My current work focuses on building production RAG systems, LLM evaluation frameworks, and generative AI tools that help investment and product teams access information faster and make better decisions. Lately, I\'ve been deep in agentic architectures—designing AI agents for entity resolution and automated workflows that go beyond simple retrieval. At Lincoln, I\'ve led projects across the full AI lifecycle—from real-time pricing models to retention systems to the company\'s first generative AI chatbot. My work spans retail and distribution across financial services and insurance, giving me a broad view of how AI creates value across the enterprise. Before moving into AI leadership, I built data platforms, machine learning pipelines, and customer analytics systems. My path to AI leadership started in cognitive science. I have a PhD from Stony Brook University, where my research focused on building computational models of decision-making under uncertainty using machine learning. That work was my entry point into AI, and it still shapes how I build systems that humans need to trust and use effectively. Early in my career, I was a UX researcher at athenahealth, where I learned about design thinking and how to translate technical capabilities into products that people actually use. I still bring that product-focused, design thinking approach to the AI systems I build today. Visit my website for more at

Experience

1. AVP, Ai & Data Science

   Lincoln Financial

   Nov 2023 — Present · Boston, MA, US

   Technical lead for enterprise Generative AI projects, including production RAG systems, LLM evaluation frameworks, and generative AI chatbots* Designing agentic AI systems for entity resolution and automated workflows* Lead cross-functional teams from research through production deployment across retail, workplace, and distribution business lines* Built a real-time pricing model that predicts fees for prospective retirement funds, eliminating 95% of custom pricing requests

Education

• Stony Brook University

  Master's degree, Cognitive Science

  2014 — 2016

• Rowan University

  Bachelor of Arts - BA, Political Science and Government

  2007 — 2011

• Stony Brook University

  Advanced Certification, Quantitative Methods

  2014 — 2019

• Stony Brook University

  Doctor of Philosophy - PhD, Cognitive Science

  2014 — 2019

• Rowan University

  Bachelor of Arts - BA, Psychology

  2007 — 2011

• Rutgers University

  Master's degree, Psychology

  2011 — 2013