Send us a text In this episode of Sidecar Sync, Amith Nagarajan and Mallory Mejias dig into the startling findings of a recent MIT study: 95% of enterprise AI initiatives are failing to deliver measurable impact. Why are so many organizations investing in AI only to watch their efforts fizzle? Mallory and Amith unpack 10 core reasons for these failures—ranging from building chat-first features instead of end-to-end workflows, to skipping the unglamorous data cleanup that powers real results. ...
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Send us a text In this episode of Sidecar Sync, Amith Nagarajan and Mallory Mejias dig into the startling findings of a recent MIT study: 95% of enterprise AI initiatives are failing to deliver measurable impact. Why are so many organizations investing in AI only to watch their efforts fizzle? Mallory and Amith unpack 10 core reasons for these failures—ranging from building chat-first features instead of end-to-end workflows, to skipping the unglamorous data cleanup that powers real results. ...
Semantic Health & the Future of Medical Coding with Dr. Nicola Sahar | 94
Sidecar Sync
43 minutes
5 months ago
Semantic Health & the Future of Medical Coding with Dr. Nicola Sahar | 94
Send us a text In this episode of Sidecar Sync, co-hosts Mallory Mejias sits down with Dr. Nicola Sahar to explore how a University of Toronto med student dove head-first into clinical AI research and went on to found Semantic Health, an AI-powered medical coding platform later acquired by the American Academy of Professional Coders in 2023. They unpack the art and science of medical coding, discuss why AI will augment rather than replace coders, dive into the critical role of data privacy an...
Sidecar Sync
Send us a text In this episode of Sidecar Sync, Amith Nagarajan and Mallory Mejias dig into the startling findings of a recent MIT study: 95% of enterprise AI initiatives are failing to deliver measurable impact. Why are so many organizations investing in AI only to watch their efforts fizzle? Mallory and Amith unpack 10 core reasons for these failures—ranging from building chat-first features instead of end-to-end workflows, to skipping the unglamorous data cleanup that powers real results. ...
