The promise of artificial intelligence in healthcare has never been greater. From diagnostic support and treatment planning to payer claims automation and patient-intake optimisation, AI holds the potential to transform care delivery, reduce cost and unlock entirely new workflows.Yet, this promise comes with paradoxes. On one hand, clinician adoption is accelerating, reflecting demand for smarter tools. On the other, significant gaps remain in validation, governance and operational safety.

Selenium has been a bridge between how developers build and how users experience the web. Since its origin in 2004 as a lightweight JavaScript test runner, Selenium’s steady climb to becoming a W3C-standardized automation layer mirrors the broader evolution of web applications themselves: from static pages to dynamic, API-rich, real-time experiences.

Every vendor now claims to be “AI-powered.” For CTOs and CIOs, the challenge isn’t whether AI has potential, it’s how to separate marketing gloss from partners who’ve operationalized it across the software delivery lifecycle.

Most health systems can point to AI pilots that looked promising in early demos: a chatbot triaging patient queries, an NLP model parsing radiology notes, or an agent automating claim denials. On paper, the pilot works. In practice, it stalls at rollout.

Last week, BrowserStack and Ideas2IT came together to host a QA Meetup in Dallas. With 15 attendees, including several external participants, the room buzzed with curiosity, sharp questions, and genuine excitement about where AI fits into software testing.

The hard truth: Fewer than 2% of health system leaders say their EHR's AI tools are fully developed, leaving 98% of providers waiting on vendor roadmaps that prioritize generic solutions over your competitive advantage.