Core Insights - The article presents predictions about the evolution of AI by 2026, emphasizing a structural transformation in production and service delivery driven by AI advancements [2][27]. Group 1: Predictions about AI's Role in Supply - By 2026, AI will transition from being a tool to becoming an essential part of supply, fundamentally altering production processes [4]. - The evolution of AI can be divided into three phases: 1. Tooling phase (2023-2024) focused on cost reduction and efficiency [5]. 2. Commoditization phase (2025) where AI becomes a standard part of business processes [5]. 3. "AI as Supply" phase (2026) where production costs drop to one-tenth of previous levels, disrupting traditional business models [5][6]. Group 2: Underlying Truths of AI Transformation - The first truth is about cost: a survival benchmark of reducing costs to one-tenth is essential for creating real barriers to entry [6]. - The second truth concerns service: AI will standardize previously non-scalable services into algorithm-driven products, allowing personalized experiences for users [7]. - The third truth relates to delivery: the shift from passive to proactive delivery, where AI anticipates user needs before they are expressed [8]. Group 3: Technological Evolution - The technological evolution leading to "AI as Supply" includes: 1. Coding Model (2024) enabling low-cost task reconstruction [10]. 2. Agentic Model (2025) allowing AI to autonomously plan and execute tasks [11]. 3. Memory Model (2026) providing AI with the ability to retain past experiences and user preferences, thus eliminating alignment costs [12][13]. Group 4: Business Model Changes - The shift from "tool-making" to "asset encapsulation" will redefine business opportunities, with a focus on deep industry knowledge as a unique asset [16]. - The business model will evolve from selling AI usage rights to selling results, as AI's marginal cost approaches zero [17]. Group 5: Trust and Community Value - In an environment where information is easily replicable, trust will become a critical asset, with brands and communities serving as long-term value anchors [25]. - The ability to foster genuine relationships and community interactions will be essential for maintaining user trust and loyalty in the AI landscape [25].