Why Enterprise AI Adoption Is Hitting a Cost Wall in 2026

Lucas and Luna explore why the biggest barrier to enterprise AI adoption in mid-2026 isn't model capability — it's inference cost. Using fresh data from Palantir's 4.3% weekly gain, AMD's 15.2% surge, and Glean's AI budget-cutting pitch, they unpack how companies are hitting a wall with deploying large models at scale. The conversation drills into the economics of AI inference: why per-token costs still matter, how hardware shifts from training to inference are reshaping chip demand, and what the rise of specialized AI hardware like ASICs means for the market. They also touch on the broader theme of the internet being rebuilt for machines, and how that changes the calculus for enterprises. #AI #ArtificialIntelligence #InferenceCosts #EnterpriseAI #Palantir #AMD #Glean #ChipIndustry #ASICs #MachineLearning #Technology #Podcast #BusinessPodcast #FexingoBusiness #TechEconomics #AIAdoption #CostOptimization #HardwareTrends Keep every episode free: buymeacoffee.com/fexingo