Artificial Intelligence in Chiropractic: Shaping the Future of Care

Recorded On: 01/24/2026

This presentation will explore the multifaceted integration of Artificial Intelligence (AI) into chiropractic research, education, and practice. The discussion will highlight the application of AI methods in research relevant to the chiropractor. Specific examples will include highlighting natural language processing for clinical quality monitoring and machine learning for predictive modeling. Additionally, the talk will discuss AI's role in chiropractic education, with examples from the use of chatbots for interactive learning and use of AI tools for continuous professional development. Finally, the presentation will address the integration of AI tools into clinical practice, highlighting the emerging field of ambient AI for streamlining clinical documentation and how automation in the professional workflow can enhance patient care. The talk will conclude with a look forward to the future of AI integration in chiropractic research, education, and practice.

Learning Objectives:

Describe specific applications of Artificial Intelligence (AI) in chiropractic research and their potential use cases.
Illustrate how AI tools, such as interactive chatbots and literature review platforms, can enhance learning experiences and support continuous professional development within chiropractic education.
Identify ways in which AI integration can enhance efficiency and optimize workflows within a chiropractic practice.
Understand AI limitations and articulate the critical importance of human oversight and professional judgement when utilizing AI tools in Clinical or educational settings.
Recognize the broad implications and evolving potential of AI for the future landscape of chiropractic research, education, and diverse aspects of clinical practice.

Hourly Breakdown:

Introduction (5 mins)

AI in Chiropractic Research (15 mins)

AI in Chiropractic Education (10 mins)

AI in Chiropractic Practice (15 mins)

Future Outlook and Conclusion (10 mins)

Q&A (5 mins)

This course is presented as part of the ACA Engage 2026 educational programming.

This course is worth 1 CE credit in ACA-approved and PACE-accepted states. CEUs have been applied for in California, Florida, Georgia, and Texas.

View a list of accepted and approved states.

PACE ID: IP124261

Brian C. Coleman, DC, MHS

Brian C. Coleman, DC, MHS is a clinician-scientist with a primary interest in the application of clinical informatics in pain research. Dr. Coleman’s background as a biomedical engineer, chiropractor, and informaticist has supported his early career work focusing on data mining, machine learning, and natural language processing of electronic health record data. He has published his research in peer-reviewed journals and conference proceedings, including the application of machine learning and natural language processing to data collected in chiropractic clinics. He has also published responses to the COVID-19 pandemic during clinical research, including leading the publication of a measure to assess individual impacts on pragmatic clinical trial study participants. 

Dr. Coleman’s work has focused on pain care and clinical research in the Veterans Health Administration (VA) as part of the Pain Research, Informatics,  Multimorbidities, and Education (PRIME) Center at VA Connecticut. His responsibilities include collaboration with the VA’s National Chiropractic Program Office, the VA Health Services Research & Development Pain/Opioid Consortium of Research, and the NIH-DOD-VA Pain Management Collaboratory Coordinating Center (PMC3). Dr. Coleman also provides chiropractic care to U.S. military veterans at the VA Connecticut Healthcare System. 