7 Challenges of AI Integration in Healthcare and Their Remedies

The integration of artificial intelligence in healthcare has been long coming, dating back to at least the 1980s, when expert systems were touted as a potential diagnostic tool.Those early efforts fell far short. But some 40 years later, the mass adoption of AI in healthcare is becoming much more realistic. The technology, especially with the arrival of generative AI (GenAI), is poised to become widely integrated into the workflows of providers, payers and life sciences companies. Use cases run the gamut from clinical documentation to revenue cycle management.Key tasks ahead include establishing an AI strategy, wrangling data, providing security, overcoming users' skepticism and managing change.

Medigy Insights

Adopting AI can potentially help healthcare organizations cut costs, improve patient care and relieve providers of manual tasks such as documenting patient visits. That's if all goes well. Poorly managed AI deployments could result in several dangerous side effects. The list includes biased data, security breaches, patient privacy violations and disrupted staff-patient communications. From a financial standpoint, ill-conceived and hastily executed projects are unlikely to generate ROI.

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Posted Apr 21, 2025