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. ...
Live from digitalNow 2025: Inside the Association Evolution | 108
Sidecar Sync
28 minutes
2 months ago
Live from digitalNow 2025: Inside the Association Evolution | 108
Send us a text Live from digitalNow 2025 in Chicago, this special edition of Sidecar Sync brings together voices from across the association world, sharing real-life examples of AI implementation, leadership innovation, and strategic transformation. Mallory Mejias speaks with leaders from the American Paint Horse Association, the Missouri State Teachers Association, AGRiP, and more to uncover how associations are moving from ideation to execution with AI. Whether it’s slashing support calls w...
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. ...
