Dr. Curtis Rasmussen

Dr. Curtis Rasmussen, PhD, is a retired U.S. Navy Chief and keynote speaker who helps leaders make AI work in the real world. As a human-machine teaming architect and industrial-organisational psychologist, he is known for turning high-risk AI programmes into practical, people-centred systems that deliver measurable results. His defining achievement is helping shape federal workforce and hiring practice through his work as Senior Industrial-Organisational Psychologist at the Cybersecurity and Infrastructure Security Agency (CISA), bringing rigour, ethics, and operational realism to complex transformation.

Curtis built his foundation in environments where mistakes carry consequences. He spent 22 years in the U.S. Navy, rising to Chief Petty Officer, with experience that included rescue diving, instruction, and leadership under pressure. That military discipline shaped how he thinks about teams, accountability, and decision-making. Alongside service, he invested heavily in education, completing a PhD in Industrial-Organisational Psychology with a 4.0 GPA, plus earlier degrees in homeland security and intelligence studies. Those formative years gave Curtis a rare blend of operational leadership and behavioural science, which now defines his speaking, evidence-based, and focused on what leaders can change immediately.

Curtis’ career achievements sit at the intersection of cybersecurity, workforce strategy, and applied AI. In government, he served as Data Scientist, then as Senior Industrial-Organisational Psychologist at the U.S. Department of Homeland Security, supporting CISA, where he contributed to workforce frameworks and helped leaders approach ethical AI with a clear view of adoption risk. In the private sector, he is Owner of Focal Point Mid-Atlantic, delivering executive coaching and performance systems that strengthen trust and execution. He is also Owner of Human-Cyber Performance Tech, LLC, advising organisations on selection, organisational health, and human-centred AI integration. Curtis is the author of ‘Artificial Intelligence and Machine Learning in Human Resources, A Concise Guide’, and he continues to innovate with patent-pending concepts including MAS for algorithm selection and XAIC for explainable AI evaluation, designed to reduce over-reliance and improve decision quality.

Organisations hire Curtis because he speaks to the real problem behind most AI disappointments, the human system around the tool. He covers topics such as derisking AI implementation, building high-trust human-machine teams, explainable AI and trust, and veteran leadership in the AI era. These themes matter because leaders are under pressure to automate fast, yet trust, workflow fit, and role clarity decide whether AI delivers value or creates costly reversals. For example, Curtis can show an HR and technology leadership team how to keep ‘human-in-the-loop’ decisions in hiring, while still using AI to speed screening and improve consistency, without damaging culture or compliance.