The article looks back at how predictions about artificial intelligence in healthcare played out over the course of 2025, using a “bingo card” created by readers and experts as a reference point. The exercise was meant to capture expectations around breakthroughs, setbacks, and recurring themes in health AI. As the year wrapped up, the results offered a snapshot of how closely forecasts aligned with reality.
Some anticipated developments did come to pass, particularly in areas where AI tools moved closer to real clinical use or gained broader acceptance in research and care delivery. These wins reflected steady, incremental progress rather than dramatic leaps, reinforcing the idea that healthcare AI evolves cautiously due to the need for safety, validation, and regulatory oversight.
Other predictions failed to materialize, highlighting how difficult it remains to predict the timing and impact of AI innovation in medicine. Promising technologies stalled, faced regulatory hurdles, or proved harder to implement at scale than expected. The article uses these misses to illustrate the persistent gap between hype and practical deployment in healthcare settings.
Overall, the retrospective emphasizes that health AI progress is uneven but moving forward. By comparing expectations with actual outcomes, the piece encourages more realistic forecasting and thoughtful evaluation of AI’s role in medicine, setting the stage for more grounded predictions and priorities as the field moves into 2026.
