Core Insights - AI models are consistent in product characterization but inconsistent in financial stability and governance assessments, which can impact procurement decisions [1][4][6] Group 1: AI and Commerce - Companies are increasingly concerned about how to ensure their products are recommended by AI agents, leading to the emergence of generative engine optimization (GEO) services [2][3] - Google has launched a shopping checkout feature in its AI Mode, with Walmart as one of the first adopters, indicating a significant shift in e-commerce [3] - Google Cloud introduced AI features to support agentic commerce, including a new product that combines shopping and customer support, which could reshape business organization [3] Group 2: AI Model Reliability - AIVO Standard found that AI models struggle with questions about cybersecurity certifications and governance standards, potentially favoring larger, publicly traded companies over smaller, privately-held ones [4][6] - AI models not only list risk factors for weight loss drugs but also make recommendations, influencing patient preferences despite disclaimers [5] - The reliability issues of AI models persist across various prompts, with models sometimes doubling down on incorrect information [6] Group 3: Challenges in Generative Engine Optimization - GEO is still evolving, and companies should be cautious about trusting marketing tech firms that claim to effectively shape AI responses [7][8] - The variability in AI responses based on brand information suggests that there is no guaranteed method for influencing chatbot outputs [8] - Companies often lack systems to track the prompts and responses that inform decision-making, which poses risks, especially in regulated industries [9]