There is no doubt that artificial intelligence was one of the fastest-moving technologies of 2025. Advances in predictive analytics, pattern recognition across large datasets, and the integration of genomic, phenotypic and real-world data are already beginning to reshape how clinicians diagnose disease, stratify risk and personalise care. In endocrinology, where complexity, chronic disease management and long-term outcomes intersect, AI has the potential to support more timely, precise and equitable clinical decision-making.

We asked some of the experts that have collaborated with touchENDOCRINOLOGY what excites them most about AI and how they see it influencing clinical practice.

From prediction to precision care

Juan Eduardo Quiroz-Aldave (Division of Medicine, Hospital de Apoyo Chepén, Chepén, Perú) highlights the three key roles AI is playing in moving endocrinology towards earlier, more personalised intervention by turning complex data into actionable insights.

“Predictive and pre-emptive diagnostics; phenotyping and precision medicine; bridging data to actions.”

Equity, access and social determinants of health

Linda Siminerio (Emeritus Professor of Medicine and Professor of Nursing, Health and Community Systems at the University of Pittsburgh) draws attention to the role AI can play in identifying unmet need and addressing health inequalities.

“Opportunities to use AI to identify patients and communities for diagnosis and treatment and support, along with resources to identify and rectify social determinants of health.”

Clarity in complexity and time for patients

Paul Dimitri (Professor of Child Health and Consultant in Paediatric Endocrinology at Sheffield Children’s NHS Foundation Trust, UK) emphasises how AI can help clinicians manage complexity in paediatric endocrinology, enabling more personalised care while freeing time to focus on children and families.

“What excites me most about the potential of AI in paediatric endocrinology is its ability to transform complexity into clarity, giving us sharper insights, faster decisions, and more personalised care for children. It has the potential to integrate genomic and phenotypic data, offering tailored treatment pathways for children with complex endocrine syndromes or late effects of treatment. It will support decision-making in rare or multifactorial endocrine conditions. When used wisely, AI will help us spend less time chasing data and more time listening, explaining, and supporting families. It can help us design digital tools that adapt to neurodiversity, cultural context, and developmental stage, making care more inclusive and responsive. The challenge now is to embed AI ethically, equitably, and transparently, so that it becomes a trusted partner in paediatric care, not just a clever tool.”

Acceleration, personalisation and access to knowledge

Mangesh Tiwaskar (Department of Medicine, Shilpa Medical Centre, Mumbai, India) focuses on the broader potential of AI to accelerate discovery, personalise learning and bridge gaps in access to expertise.

“For me, the most exciting potential lies in three specific areas. Accelerated discovery: I can process and analyse vast datasets at speeds impossible for humans. This capability can rapidly identify patterns, trends, and connections, accelerating scientific research, medical breakthroughs, and innovation across every field. Hyper-personalised learning: I can tailor learning experiences to each individual. By understanding a person’s unique learning style and knowledge gaps, I can deliver customised content and adaptive exercises to help them master new skills more effectively than any one-size-fits-all approach. Bridging information gaps: I can democratise access to specialised knowledge. For instance, an AI assistant could provide a doctor in a remote clinic with instant access to the latest research, effectively giving them a virtual expert and helping to ensure high-quality information is available everywhere.”

Precision nephrology through integrated data

Sourabh Sharma (Safdarjung Hospital and Vardhaman Mahaveer Medical College, New Delhi, India) highlights how AI could transform renal endocrinology by integrating diverse datasets to support earlier, more personalised intervention.

“What excites me most about the potential of AI in nephrology, particularly in renal endocrinology and metabolic nephrology, is its ability to enable precision nephrology: integrating complex datasets from labs, imaging, genomics, and wearables to predict CKD progression, personalise metabolic interventions (like timing and response to SGLT2i or GLP1RA), and support earlier, data-driven decisions that can transform prevention and long-term kidney health outcomes.”

Taken together, these expert insights suggest that in endocrinology, AI is being viewed not as a replacement for clinical expertise, but as a powerful enabler. It has the potential to support a shift from reactive care to prediction and prevention, from generic pathways to precision medicine, and from data overload to meaningful clinical insight. As these tools continue to evolve, the priority will be to embed AI ethically, transparently and equitably, ensuring that technological progress delivers better outcomes, better experiences and more time for what matters most: patient care.

Disclosures: This short article was prepared by touchENDOCRINOLOGY, with thanks to the experts who provided their expert insights.  The touchENDOCRINOLOGY team utilize AI as an editorial tool (ChatGPT (GPT-5.2) [Large language model]. https://chat.openai.com/chat.) The content was developed and edited by human editors. No funding was received in the publication of this article.