Data Silos Are Holding Back AI Progress in Healthcare
The potential for AI to transform healthcare is clear. From improving patient care to easing the workload of healthcare staff, AI offers many benefits. Yet, healthcare organisations struggle to fully tap into AI’s promise because their data systems and processes aren’t ready.
A recent global survey by SS&C Blue Prism of 297 senior healthcare professionals found that 94% view AI as central to their operations. The top areas where AI is expected to help include:
- Improving care quality (42%)
- Reducing repetitive manual tasks (36%)
- Enhancing patient experience (34%)
With burnout still a major challenge, 37% of executives also see AI as a way to improve work-life balance for healthcare workers.
Agentic AI Is on the Horizon
Two-thirds (67%) of healthcare organisations plan to adopt agentic AI within the next year. This form of AI can make decisions and act independently, offering new operational possibilities. However, there’s a catch: healthcare providers need solid data foundations first.
Only about half of healthcare leaders say they have reliable systems to move data internally (54%) and consistent, accurate data (56%). For AI to deliver personalised care and meaningful insights, organisations must break down data silos and ensure clean, consistent data.
Data Governance Is a Strength
On the bright side, healthcare ranks highest among industries for data governance, with 72% confirming strong systems to keep data secure, private, and properly consented. This focus on protecting sensitive patient information is crucial as AI use expands.
Getting Data Ready for AI
Turning AI’s potential into reality means tackling data challenges head-on. Breaking down silos and standardising data takes effort, but technology can help. Tools like robotic process automation, machine learning, and natural language processing assist in streamlining data flows and improving accuracy.
Additionally, practices such as task mining and process orchestration guide organisations in creating a reliable data environment. These approaches not only enable AI but also establish safeguards to protect patient data and verify AI outcomes.
Healthcare professionals looking to deepen their understanding of AI and automation can explore targeted training options. Resources like Complete AI Training’s healthcare courses offer relevant skills to bridge the gap between technology and clinical practice.
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