AI and RPA are often mentioned in the same sentence as ML and IoT; they are touted as magical solutions that will transform the way we live and work. For companies with massive legacy tech platforms, overnight change is not that easy -- or is it? Consider this data point: A study by McKinsey & Company determined IT costs per policy for insurers with modernized IT can be 41% lower than that of players with significant legacy systems. Because legacy platforms hold tremendous amounts of proprietary data without which companies cannot function, and moving away from them is deemed too expensive. The downside: those platforms are often not only costly financially, but from a human resources perspective, they are key blockers of agility.

Artificial intelligence (AI) is of great strategic importance to the United States. We are recognized as the current leader in the space, and as such, are investing in capabilities and opportunities to ensure we are progressing AI forward across the country. AI is instrumental in providing the country with a competitive advantage. If we're not raising the bar in the United States, other countries will become more adept leaders in the space. AI is a top priority at the federal level right now.