A discerning investor, upon seeing a short-term negative for a listed company, feels excitement rather than anxiety. This reveals they are investing, not speculating, as they anticipate acquiring shares at a cheaper price. Different investors see different things in the same announcement, because what we perceive in others often reflects our own perspective. The value of the capital market is measured by different rulers; short-term traders use a ruler marked "quarterly," while seasoned market players use one marked "cycle." When seasoned players read an announcement, their favorite action is to first glance at the current month, then look at the "long-dated contract." Why? Because the long-dated column holds the script for the next round of the game.
In the same game, when we examine Bairong Inc (06608)'s H1 performance forecast, alongside the H1 net loss of [3.2-3.6] billion, there is a key line: "The revenue of the business not subject to the aforementioned regulatory effects, based on AICC (Intelligent Contact) technology and operations ('AICC Business'[1]), recorded relatively substantial growth. Among which, the new business serving customers in new scenarios shows significant growth, demonstrating the Group's capability in deploying AICC technology in new scenarios." This line is Bairong's "long-dated contract" in the AI arena.
What chapter of the cycle does this H1 performance forecast represent?
The announcement is clear: Bairong's H1 focus was on investing heavily in AICC new scenarios and new customer acquisition. Why is Bairong concentrating on this? Because the window of opportunity in the AI battlefield is narrowing.
Looking at the AI battlefield from 2024 to 2026, what has happened?
First, the general AI large model track has entered a "commoditization" phase. Price wars have begun, and gross margins are declining. The general large model business is shifting from "high-tech" to "infrastructure"—much like cloud computing, servers, and new energy batteries in the past. Once it becomes infrastructure, gross margins converge, and supernormal profits are no longer attainable. Second, the window for vertical AI applications is still 2-3 years open. AI, in the end, cannot remain just a tool in a dialogue box; it must ultimately become a "silicon-based employee" capable of solving B-end problems. Therefore, while general large models will become commodities, "vertical models + industrial-grade deployment + customer success" will not—this is the final window for differentiation. Whoever establishes "industrialized delivery" capability first within this window secures the future customer relationship. Missing this window means entering as a "follower" later. Third, capital is concentrating on companies with "commercialization capabilities." Top-tier capital has recognized that the company capable of creating "industrialized delivery" within 2-3 years will be the next target for investment. From 2025 to 2026, B-end customers will vote with their actual spending: AI that works stays, and AI that doesn't work gets replaced. Customers will not wait five years to see if a company can achieve commercialization; they will only use 12 months to judge whether a company can solve their problem now.
Competition in the AI battlefield is a three-layer structure: "base + middle platform + application."
Missing one layer means falling behind; focusing on only one layer means a low ceiling. Bairong happens to possess all three layers: Agentic AI infrastructure (the base layer—the "water, electricity, and coal" of the AI era, the foundation for all upper-layer applications); a self-developed model matrix (the middle platform layer—a key step from "general ammunition" to "specialized ammunition"); and enterprise-level AI Voice + AICC application scenarios (the application and trial layer—directly selling AI products to customers, along with a RaaS (Results as a service) outcome-oriented business model).
Short-term traders might choose to exit upon seeing the net loss, believing it to be the endgame. Insiders, especially AI practitioners, see the H1 investment in the base + middle platform + application as an opening move. To evaluate Bairong's AI company in H1, three things should be examined. First, the direction of investment. AI talent, AI models, and AI infrastructure are all about strengthening the foundation. Second, the footing on the ground. The footing is stable, as the announcement discloses: "Subsequent to the reporting period, the Group's cross-scenario customer expansion has continued to gain momentum, and recently, substantive progress has been made in landing benchmark customers in new scenarios such as the logistics industry." This ensures that the earlier investments and accumulation are not wasted. Third, the cash on the books. The books are sufficient, as the announcement discloses: "The Group currently maintains relatively robust cash reserves and has no interest-bearing liabilities. Bairong's existing cash reserves are sufficient to support ongoing operations and business expansion needs."
Looking back at Bairong's 2026 H1 performance forecast three to five years from now, what will be seen?
The base layer will see Agentic AI infrastructure become the "water, electricity, and coal" of the AI era—the foundation on which all upper-layer applications, all enterprise-level Agents, all silicon-based employees, and all vertical models run. The middle platform layer will see the self-developed model matrix become a "specialized ammunition depot"—a SOTA model for vertical domains. The application layer will see enterprise-level AI VoiceGPT + AICC become an "enterprise-level silicon-based labor platform"—focusing on carbon-based customer service scenarios that can be AI-transformed over 3-5 years. Together, these correspond to Bairong's chosen trillion-yuan AICC track—the intelligent contact, enterprise-level silicon-based labor market.
[1] The Group will reclassify by business nature in the 2026 interim results report. The aforementioned "AICC Business" primarily refers to operations assisted by self-developed AI VoiceGPT: (1) intelligent marketing and intelligent customer service for customers in new scenarios such as brokerages, banks, telecom operators, and logistics; (2) part of the operations for intelligent marketing and intelligent operations of credit products for some financial institutions (the products served by this part of the business are not affected by recent regulatory policies).
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