Analysts are evaluating companies' AI implementation not just on technology, but across six business functions: personalization, customer acquisition, product innovation, labor productivity, supply chain, and inventory management. The assessment also considers breadth, depth, and proprietary initiatives to differentiate leaders.
Forward-thinking companies like Shark Ninja are not waiting for AI-driven "agentic commerce" to mature. They are actively optimizing their direct-to-consumer websites for Large Language Models (LLMs) like ChatGPT, anticipating that what drives conversion today may not rank well in future AI-powered searches.
Economists forecast that the combined effect of direct investment in AI infrastructure (data centers, chips) and resulting productivity gains will add between 40 and 45 basis points to U.S. GDP growth over 2026-2027. This represents a significant contribution to the overall economic growth outlook.
To avoid being disintermediated by AI agents that could direct consumers elsewhere, retailers can leverage their physical assets. An AI agent will still prioritize retailers with extensive infrastructure and forward-positioned inventory to ensure fast and efficient delivery, creating a competitive moat against pure-play e-commerce.
Consumer goods company General Mills is leveraging AI-powered "digital twins" across its network. This has structurally increased its historical productivity savings by a full percentage point, from 4% to 5% annually, demonstrating a tangible, direct impact on the P&L from AI adoption.