Today's battlefield environment is complex, dynamic and uncertain, and requires efficient support to ensure mission success. This relies on a proper support strategy to provide supported equipment able to fulfill the mission. In the context of defense where both systems and organization are complex, having a holistic approach is challenging by nature, forces and support agencies need to rely on an efficient decision support system. Logistics, readiness and sustainability are critical factors for asset management, which can benefit from AI to reach "Smart In Service" level relying especially on predictive and prescriptive approaches and on effective management of operational re-sources. Smart Support capacities can be then monitored by appropriate metrics and improved by multi-criteria decision support and knowledge management system.

Today's battlefield environment is complex, dynamic and uncertain, and requires efficient support to ensure mission success. This relies on a proper support strategy to provide supported equipment able to fulfill the mission. In the context of defense where both systems and organization are complex, having a holistic approach is challenging by nature, forces and support agencies need to rely on an efficient decision support system. Logistics, readiness and sustainability are critical factors for asset management, which can benefit from AI to reach "Smart In Service" level relying especially on predictive and prescriptive approaches and on effective management of operational re-sources. Smart Support capacities can be then monitored by appropriate metrics and improved by multi-criteria decision support and knowledge management system. Depending on the operational context in terms of information and the objective, different AI paradigms (data-driven AI, knowledge-based AI) are suitable even a combination through hybrid AI.

Artificial intelligence (AI)–assisted electrophysiology (EP) shows promise, but even its most ardent advocates aren't ready for full-fledged endorsement--yet. A robot revolution is coming, predicted the Huffington Post in November. Citing Bureau of Labor Statistics data and an analysis by Ball State University's Center for Business and Economic Research (CBER, online June 19, 2017), the article warned that nearly half of American jobs are "vulnerable to automation." Many came couched among counsel to prepare for a changing job market, while others have joined the debate about what machines should and shouldn't be tasked with doing. Medicine hasn't been immune to the debate, leading some clinicians to worry that AI--the same brain behind automation, robotics and deep learning--might someday replace them just as it's predicted to do to workers in many manufacturing jobs.