SUMMARY: When we get to the end of 2026, how will enterprise companies be measuring the success of their AI projects? And how well will their teams be sharing their AI learning curves?SHOW: 1034SHOW TRANSCRIPT: The Enterprise AI Show #1034 TranscriptSHOW VIDEO: https://youtu.be/TvIFwNN-6ckSHOW SPONSORS:Nasuni - Activate your data for AI and request a demoOutShift - “Scaling Out Superintelligence”  The Internet of Cognition architectureShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!SHOW NOTES:Why AI Economics are changingHow will team collaboration evolve with Enterprise AI?Topic 1 - How do we measure AI-adoption success? Number of workloads?Financial metrics (Spend, ROI, Costs-Saved, etc.)?Speed improvements?People-level?Topic 2 Right now the AI tools are very individual-centric The machinery to share, even at the basic enterprise-level, is very difficultThe experience to share is non-deterministic, just as everyone’s working style is different.Topic 3 - The motivation to share is still unknown. How do you encourage collaboration when so many companies are laying off people, or the specter of that happening is growing?What was the motivation before (team goals?) and how does that change now? People don’t want to be monitored, so how does a manager have visibility?What happens when companies remove the managers (“the counters”)? FEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow