CloudWave’s Predictions for Healthcare IT in 2025 Part 4: Broader Adoption of Targeted Use Cases for Healthcare AI
In the first series of CloudWave’s predictions on healthcare IT developments for 2025, we discussed why hospitals must prioritize patient-centric cybersecurity approaches to better protect care delivery, shared our thoughts on how healthcare organizations will implement more proactive cybersecurity approaches that emphasize prevention in addition to detection and response, and touched on the growing threat of healthcare supply chain attacks. This edition will focus on the AI use cases we expect to see more broadly adopted this year, including tools that enhance decision-making, improve operational efficiency, and deliver better care and patient engagement.
As AI technology continues to evolve beyond early generative AI applications, we expect to see broader adoption of several targeted, healthcare industry-focused use cases for AI. Some of the innovations that are expected to gain traction include:
- Partner ecosystem applications: Healthcare organizations will increasingly adopt AI-powered solutions through partnerships with electronic health record (EHR) vendors, such as MEDITECH, Cerner, and Epic.
- Ambient listening: AI-powered ambient listening technology applications will be a focus as they aim to improve clinical documentation and reduce administrative burdens on physicians. The technology uses AI to capture and summarize conversations between patients and physicians and translates the information directly into the medical record. The ultimate goal of AI-powered ambient listening is to increase care quality and insights while decreasing provider documentation requirements.
- Point solutions: We also expect to see the adoption of additional AI-powered tools that help hospitals and healthcare systems enhance their financial performance by streamlining documentation, better preparing physicians to optimize visits, decreasing documentation time, and reducing time-to-revenue.
However, several barriers still must be addressed for broader adoption in the healthcare environment, including security and privacy concerns, as well as regulatory and ethical considerations. For example, in the case of ambient listening, a provider talking to a patient generates protected health information (PHI). These are new assets on a healthcare organization’s network and, unfortunately, create another target sector for bad actors to go after.
Working with partners that understand the complex healthcare ecosystem to secure and optimize the network can help address these challenges so healthcare organizations can focus on managing day-to-day operations, making providers happier and more productive while improving patient outcomes, enhancing operational efficiency, and reducing costs.
As hospitals increasingly adopt new AI technologies, establishing robust policies and procedures is crucial. We invite you to request our customizable AI Privacy & Security Template that provides a set of policies and procedures focused on the implementation, governance, and risk management of AI technologies within healthcare settings.
Mike Donahue, Chief Delivery Officer