The healthcare industry is moving past the era of speculative AI, transitioning into a phase where the technology delivers measurable impacts on efficiency and patient outcomes. According to Priscila Cruzatti, a healthcare specialist at Google, the application of artificial intelligence has moved beyond the experimental, finding utility in everything from administrative billing cycles to sophisticated clinical decision support.
However, this evolution is not unfolding uniformly. Cruzatti describes a landscape of "multiple realities," where the sophistication of AI adoption varies wildly between institutions. While some organizations are still navigating the early stages of digitization, others are already deploying predictive models to manage patient demand and integrating historical data with imaging to refine diagnostic accuracy.
The primary friction point preventing a more cohesive transformation remains the management of data. While the healthcare sector is historically data-rich, it remains information-poor; the vast volumes of accumulated records are often siloed or unstructured. The industry’s next great challenge is not the creation of more data, but the refinement of existing information into actionable intelligence that can be used at the point of care.
With reporting from MIT Tech Review Brasil.
Source · MIT Tech Review Brasil
