Founder
Founder of The Blue Narwhal. AI governance advisor, author, researcher, and professor of computer science.
JM Wofford founded The Blue Narwhal to close the gap between what organizations claim about their AI and what they can prove. Drawing on over fifteen years of experience across enterprise data platforms, governance, and applied AI, Wofford helps leaders replace confident assertions with verifiable evidence, so that AI programs can withstand the scrutiny of regulators, procurement teams, boards, and the people the systems affect.
Three threads run through everything The Blue Narwhal does: advising organizations, publishing research, and teaching the next generation of technology leaders.
Practical, evidence-first guidance for organizations at every stage of AI adoption: governance program design, vendor and procurement readiness, measurement that means something, and honest assessment of where claims outrun proof.
The Four Lenses of AI Measurement series, published on SSRN, examines how organizations measure AI through compliance, maturity, and capability, and how each lens can flatter as easily as it informs.
Wofford teaches graduate computer science, bringing governance, infrastructure, and applied AI into the classroom, and bringing the discipline of teaching back into advisory work: if it cannot be explained clearly, it is not understood yet.
Two books, one argument: AI needs adults in the room, and evidence beats confidence.
The case that seasoned professionals, the generation that grew up analog and went to work digital, are uniquely suited to lead AI governance. The book introduces practical frameworks for leading well alongside AI, including the Dispatcher Model and the Whatever Filter. Book One of a planned series.
About the book →A working playbook for AI vendors who need to survive enterprise procurement: what evidence buyers actually ask for, how to assemble it before the questionnaire arrives, and how to turn governance readiness into a sales advantage rather than a scramble.
Explore the research →A research series on SSRN examining the ways organizations measure their AI, and the ways those measurements mislead.
How compliance-driven measurement shapes what organizations see, and what it leaves invisible.
Why maturity models can certify progress that has not happened, and how to tell reflection from mirage.
Why capability demonstrated in one context degrades in deployment, and the pathways through which "it worked in the demo" becomes "it failed in the field."
If your organization needs AI governance that stands up to scrutiny, start a conversation. Research-grounded, practically delivered.