AACE Endocrine AI is here: Why you need this now
Artificial intelligence (AI) is rapidly reshaping medicine—from radiology to pathology to primary care. Yet few fields are as uniquely positioned to benefit from AI as endocrinology.
Endocrinology is inherently complex and deeply data-driven. Unlike organ-based specialties, it deals with interconnected systems—hormones, feedback loops, and signaling pathways. Physicians are constantly interpreting layers of data, often in real time. Add the rising prevalence of diabetes, obesity, and thyroid disease, along with workforce shortages and a flood of patient-generated data, and it’s clear: The demands are growing faster than what clinicians can reasonably manage on their own.
That’s where AI comes in.
AI can analyze large datasets, detect patterns, and generate predictive insights, helping physicians make more informed decisions and deliver more personalized care. It can also reduce administrative burden and improve patient engagement. And that’s only the beginning.
There are almost daily updates on new AI developments and their impact on endocrinology.
So the question is, Where can endocrinologists learn about everything AI?
That’s where AACE Endocrine AI comes in.
“AACE Endocrine AI exists because our field needs a dedicated, trusted space to understand how AI is shaping endocrinology,” says Editor-in-Chief Johnson Thomas, MD, Section Chair of Endocrinology at Mercy Hospital Springfield. “The goal is to distill the most relevant developments, provide practical guidance, and create a community where endocrinologists can engage with AI in a meaningful way.”
There is also a growing sense of urgency.
“If we don’t engage proactively with AI, we risk having AI tools built for us rather than with us,” Dr. Thomas explains. “The question is no longer whether AI will shape endocrinology—but how we will shape AI.”
Where AI Is Already Making an Impact
AI is already influencing many aspects of endocrinology clinical care.
In diabetes management, closed-loop insulin delivery systems use real-time glucose monitoring and predictive algorithms to automatically adjust insulin dosing. These systems are reducing hypoglycemia and improving glycemic control in ways that were not possible before.
In thyroid disease care, AI-assisted ultrasound can match the diagnostic accuracy of experienced radiologists. That means more consistent interpretations and potentially fewer unnecessary biopsies. AI is also being used in diabetic retinopathy screening and automated bone age assessment, with promising results.
“On the horizon, we’re seeing multi-omics integration—combining AI with genomics, metabolomics, and proteomics—to enable truly personalized medicine,” says Dr. Thomas. “We’re also seeing AI-driven patient engagement tools, clinical trial matching, and even ‘digital twins’—virtual models that can simulate individual treatment responses.”
Challenges Endocrinologists Must Navigate
For all its promise, AI also brings many challenges for endocrinologists. For example:
The Knowledge Gap. Most endocrinologists haven’t had formal training in AI, and the pace of innovation can feel overwhelming, making it difficult to know where to start.
Evaluating What to Trust. Not all AI tools are created equal. Some are well-validated and regulated; others are still experimental. “Without clear guidance, endocrinologists risk either adopting tools too early or unnecessarily dismissing them altogether,” says Dr. Thomas.
Ethics, Bias, and Transparency. Concerns around privacy and data bias, privacy are well-founded. Algorithmic transparency remains a major issue—“black box” models that cannot explain their outputs and AI programs that produce confident but incorrect results (“hallucinations”).
Foundation Literary. Dr. Thomas emphasizes that endocrinologists do not need to become AI experts, but they do need a working understanding of the technology. “At a minimum, physicians should evaluate AI tools the same way they would a new drug or diagnostic test,” he says. “What data was the model trained in? How was it validated? Does it apply to my patient population?”
How AACE Endocrinology AI Supports Physicians
AACE Endocrine AI is designed to make this learning process practical and approachable. Key resources of the site include:
AI Education Center. Structured step-by-step learning from the basics to advanced topics.
Research Digests. Curated summaries of high-impact studies across endocrine subspecialties.
Tool Assessments. Independent evaluations of AI tools, focusing on validation, regulatory status, and real-world usefulness.
Implementation Guidance. Practical expert advice on integrating AI into clinical workflows, documentation, decision support, and patient engagement.
“Coverage will grow organically as AI continues to evolve," says Dr. Thomas. Possible future topics include AI-assisted guideline development, regulatory updates, integration into fellowship training, and much more.
“The goal is to make the site feel like a knowledgeable colleague who’s tracking AI and highlighting what matters most,” Dr. Thomas explains. “We want endocrinologists to leave informed—not overwhelmed.”
Reframing the Role of AI in Endocrinology
AACE Endocrine AI also wants to reframe how endocrinologists think about AI. It's often viewed as potentially disruptive, but it’s best understood as a tool that supports and enhances care.
“AI isn't likely to replace endocrinologists, but it will reshape how we work," says Dr. Thomas. "By reducing administrative burden and supporting routine decisions, AI has the potential to free physicians to focus more on their patients. But that success will depend on careful validation, workflow integration, and ongoing vigilance against the risks of overreliance and loss of clinical skills."
Building a Collaborative Community
AACE Endocrine AI is not intended to be a one-way conversation.
“We want this to be a true dialogue with the endocrinology community—clinicians, researchers, academics, and trainees,” says Dr. Thomas. “That means sharing experiences, asking questions, and helping shape how AI is used in real-world practice. This collaborative approach will be critical as both AI and endocrinology continue to evolve.”
Looking Ahead
AI will continue to accelerate. For endocrinologists, the path forward is clear: stay informed, thoughtful, and engaged. AACE Endocrine AI aims to support that journey.
“Integrating AI into endocrinology is not just a technological shift—it’s an opportunity to redefine how we deliver care,” says Dr. Thomas. “The endocrinologist who uses AI effectively will ultimately provide better care.”
AACE Endocrine AI is published by Conexiant under a license arrangement with the American Association of Clinical Endocrinology, Inc. (AACE®). The ideas and opinions expressed in AACE Endocrine AI do not necessarily reflect those of Conexiant or AACE. For more information, see Policies.