The Convergence of AI and BI and Preparing for the Future of Decision Engineering
Market discussions on ChatGPT and the potential of generative AI have proliferated this year. Yet separating fact from fiction and translating hype into action is not easy.
Health systems now face an overwhelming decision about how to shape their AI strategies and make progress against challenges—like workforce shortages and burnout, financial pressures, and patient acquisition retention and experience, quality of care and growth. Over half of provider organizations have begun planning and early implementation of AI strategies, but less than 10% have a system-wide, coordinated program in place to optimize the immense upside that AI presents.
AI capabilities are predicted to be 1 million times more powerful than ChatGPT within 10 years. While many have not yet adopted AI at scale, recent breakthroughs make the opportunity cost too high to ignore—and the linkage with health system’s current business intelligence and analytics programs is more important than ever.
It requires establishing the building blocks of a coordinated and coherent AI and data and analytics strategy and harnessing existing intelligence and these emerging innovations in a deliberate and strategic way.
Hear from peers in a panel discussion about their approach with AI and analytics to create actionable outputs that could be used to address some of the biggest challenges facing health systems—such as workforce shortages and burnout, margin compression, and patient acquisition, retention, and experience, quality of care and growth. Discuss how they’re evolving Data and Analytics programs and teams for the decision engineering capabilities and roles that will be required.
Speaker: Carl Dolezal, Principal, The Chartis Group
Start Date: 12/06/2023
Event Type: Archived , CHIME LIVE Webinar