Data silos prevent healthcare organisations from capitalising on the AI opportunity

Healthcare organisations believe AI will be vital to their operations, but lack the data processes and systems to capitalise on the opportunity, global research released by SS&C Blue Prism has revealed.

Surveying 297 senior professionals in the healthcare sector, the research found that 94% of organisations believe that AI is core to their entire operations. Executives believe improving care quality (42%), minimising repetitive and manual processes (36%) and enhancing patient experiences (34%) are the key areas in which AI can help in healthcare.

With burnout still prevalent in healthcare systems globally, 37% of executives said staff believe that AI will help improve work/life balance for healthcare practitioners.

Agentic AI, the emerging technology where AI can make decisions and conduct activities autonomously, is a priority for the healthcare sector. Two thirds (67%) of organisations plan to implement agentic AI within 12 months.

But the research shows that healthcare organisations need to get their data in order before making AI a reality. Only 54% of healthcare leaders said they have robust systems for moving data internally and only 56% say they have accurate and consistent data within their organisation. With data playing such an important role in delivering AI and personalising healthcare, the sector has work to do.

Importantly, the healthcare sector topped all industries surveyed when it comes to data governance, with 72% saying they have strong governance systems in place to ensure data is secure, private and managed with the appropriate consents.

Emily Bristow, SVP, Global Head of Professional Services & Customer Success at SS&C Blue Prism, comments:

“The promise for AI in the healthcare sector is significant. For patients it can transform the experience, leading to truly personalised healthcare, delivered at speed. For practitioners, it can help alleviate administrative burdens and stress – so they can spend more quality time with patients. But AI will not be able to live up to this promise without the right approach to data.

“The process of breaking down data silos, creating clean and consist for AI models to accurately learn from is significant. But it can be assisted by technology such as robotic process automation, machine learning, natural language processing as well as practices such as task mining and process orchestration. This enterprise AI approach helps organisations make the most of the AI opportunity. But it also helps provide guardrails, ensuring that the right processes are followed to ensure data, particularly sensitive patient information, remains protected and the results an AI model provides can be authenticated.”