Understanding artificial intelligence: Barriers and potential in wound care

The global wound burden is rising at an alarming pace due to increases in the ageing population and comorbidities and complications, such as obesity, diabetes and complex surgeries (Sen, 2021; Chen et al, 2024; Reifs et al, 2025). The World Health Organization (WHO) estimates there will be a global shortage of 18 million healthcare professionals (HCPs) by 2030 (WHO, 2016) to deliver care. To address these increasingly complex challenges, it is crucial to improve efficiency of healthcare systems, clinician education and consistency of wound care standards (The King’s Fund, 2018; Sen, 2021; Gould and Herman, 2025).

Within healthcare, artificial intelligence (AI) has emerged as a promising solution to several of these challenges with demonstrated improvements in diagnosis and treatment efficiency and clinician education, and productivity (Chen et al, 2024; Rippon et al, 2024). AI promises to replicate aspects of clinician experience and intelligence and can prove to be a useful tool in increasing the scale and speed of appropriate care provision (Bajwa et al, 2021; Rippon et al, 2024). AI has the potential to encompass all aspects of wound care and clinician education and training, including wound and risk assessment, healing prediction (e.g. by assessing patient comorbidities and social and psychological factors) and delivery of evidence-based, tailored treatment (Rippon et al, 2024; Reifs et al, 2025).

The aim of this consensus is to highlight for wound care clinicians and allied healthcare associates the multidimensional potential of AI, especially for chronic and/or complex wounds. A central theme of this consensus is to highlight the crucial role that wound care clinicians will need to play in implementing AI. It is only natural that some clinicians may be wary of the impact of AI on their job security. In this publication, we strive to dispel this myth and highlight that clinicians’ satisfaction with AI can only improve with a better understanding of what AI is and how it can be an addition to their toolbox. The expert panel also provide examples of implementing AI in their own wound care practices and share their learnings of improved outcomes, current barriers and areas of future need.

This consensus is not intended as a reference for highly technical AI terminology. Instead, the goal is to simplify the overwhelming amount of AI information for wound care clinicians, presenting key concepts in accessible language. We aim to help clinicians of all experience levels understand the implications and unmet needs in AI-driven wound care, empowering them to navigate their role in this rapidly evolving field.

Educating and preparing clinicians for the disruptive potential of AI is the first step towards creating effective, replicable, equitable and safe wound care systems that are increasingly needed for addressing the rising global wound care burden. 

Supported by Essity and Mölnlycke Health Care.

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