From pilot to production: How scaling companies are making AI work
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Scaling companies are struggling to move AI beyond experimental pilots into production due to operational challenges including cost management, governance, and workforce adaptation. A key concrete issue is that companies embedding AI into core workflows are seeing gross margins drop from 80-90% to 50-60% due to unpredictable token costs, prompting adoption of multi-model strategies and financial operations oversight. Successfully scaling requires clear governance frameworks, transparent human-in-the-loop processes, domain expertise, and organizational commitment to AI adoption across all levels.
