Felix Cheung of Bairong-W (06608.HK) Addresses First Seafront Fund Strategy Summit: AI Roll-up Reshapes Industries as AICC Scaling Accelerates

Abstract: In his keynote speech, Felix Cheung systematically outlined the critical path for AI scaling from foundational models to enterprise-grade AI agents. He noted that AI had evolved beyond an assistant tool to a workforce component (AI agents). Enterprises are shifting from purchasing software to buying measurable outcomes, with AI spend expanding from IT budgets into operational and workforce cost pools. He argued that commercially viable models of the future would carry vertical-domain features, creating a three-tier structure comprising general foundational models, vertical foundational models and enterprise-grade AI agents. The integrated stack of vertical models plus enterprise-grade AI agents holds the key to large-scale AI deployment, and AICC (AI Contact Centre) serves as a China-based real-world example.

The 2026 Annual Investment Strategy Summit hosted by Qianhai First Seafront Fund was held in October 2026 under the theme of Pursue Quality Through Innovation, Forge Ahead Amid Shifts. This flagship annual summit, highly influential in China’s capital market, brought together top specialists and leading institutional investors from home and abroad for in-depth discussions on investment opportunities amid macro trends, industrial transformation and AI development, drawing widespread market attention.

Felix Cheung, Founder, Chairman and CEO of Bairong-W (06608.HK, “Bairong”), delivered a keynote address via video titled From Foundational Models to Enterprise-Grade AI Agents: The Critical Path to Scaling AI Deployment – AI Roll-up Ecosystem Practices. Notably, Bairong was invited to present at Qianhai First Seafront Fund’s annual strategy summits across Beijing, Shanghai and Shenzhen alike, testament to Bairong’s deep expertise in industrial AI rollout and strong recognition from capital markets.

(Mr. Felix Cheung, Founder, Chairman and CEO of Bairong, delivered the keynote address via video at the summit.)

Core Insight: AI Is Advancing From Analytical Capability to Actionable Execution

Cheung observed that AI’s functional frontier keeps expanding: from reasoning and multimodal capabilities to sophisticated tool calling and long-sequence workflow execution. Historically, organisations deployed AI primarily for data analytics, content generation and decision support. Today, businesses and individuals are experimenting with AI to take ownership of specific tasks, interact with live systems and deliver business outcomes. “AI has transitioned from an assistant tool into a workforce component via agents.” This paradigm shift is reshaping corporate procurement: buying software is giving way to buying outcomes. Corporate AI expenditure now stretches beyond the IT budget into operations and human-resource cost buckets.

He further clarified the boundaries of key concepts: AI is much more than foundational models; generative AI and discriminative  AI together form a broader AI landscape. Nor are foundational models equivalent to agents. Enterprise-grade AI agents depend on supporting systems for perception, memory and execution. Model ownership alone does not translate into deployable enterprise-grade AI agents – “last mile” execution capability makes all the difference.

AI Roll-up: A New Organisational Model for Industrial Transformation

A key focus of Cheung’s keynote was AI Roll-up, a new paradigm for industrial organisation. He outlined its three-stage evolution: conventional roll-up strategies prioritised M&A consolidation and scale gains; AI Roll-up pairs acquisition integration with AI-redefined delivery. The broader definition of AI Roll-up is not confined to M&A. Its core lies in AI-driven delivery transformation.

He cited North American practices: acquirers refactor the technology stack of portfolio assets with AI engineering to revamp live workflows and lift productivity. The Chinese market follows a different, often organic route: clients embed AI natively, or integrate AI post-investment or acquisition. “The two approaches share one core principle: extending AI into live workflows, client relationships and service delivery,” Cheung emphasized. “AI does not replace skilled professionals. Instead, it reallocates specialists toward judgement, relationship management and high-value advisory activities.”

Drawing on the rise of vertical-focused players such as Anthropic, he set out a thesis: commercially viable models of the future would feature vertical-domain specialisation. The ecosystem would settle into three layers: general foundational models, vertical foundational models and enterprise-grade AI agents (“silicon-based workers”). Enterprises running integrated vertical-model-and-agent stacks are better positioned to build self-reinforcing loops: live business deployment generates fresh data, which feeds back into model refinement, enabling continuous optimisation.

AICC Deployment Case: Bairong’s China Example of AI Roll-up

Bairong’s AICC use cases feature broad applicability, quantifiable value and closed-loop task flows, making them a natural fit for outcome-based pricing. Next-generation AICC systems are evolving from simple outbound calls to sophisticated inbound calls. They run on a multimodal voice foundation model focused on real-time voice interaction, a specific foundation LLM focused on intent recognition and proactive guidance and enterprise-grade AI agents, moving beyond natural dialogue to completing production tasks aligned with business workflows.

Against this backdrop, Bairong centres its efforts on AICC. By deploying vertical models integrated with enterprise-grade AI agents, Bairong supplies “silicon-based workforce” to reshape conventional labour-intensive service models. It has built three proprietary domain-specific foundational models: BR-Voice – multimodal voice model, BR-LLM-Proactive – proactive conversation model , and BR-Vision-Doc – document understanding model . A flywheel built on live business data drives continuous model refinement. Validated positive user feedback gathered in production feeds into evaluation metrics and reward signals for reinforcement learning.

On the commercial side, Bairong adopts an RaaS (Results-as-a-Service) model. Pricing structures are tied to successfully completed workloads, the scale of deployed agents (silicon-based workforce), or revenue share from business conversions driven by agents. “Outcome-based pricing is more than selling an AI tool. It leverages agents to assume defined tasks and deliver business results. This is how the tech-reconfiguration path of AI Roll-up works commercially,” Cheung explained.

The same underlying speech model stack also boosts internal corporate productivity. Bairong showcased its Bairong Baixiao product, an AI multi-role collaboration platform for sales teams. It connects sales, pre-sales, product and delivery roles across the full lifecycle: requirements gathering, proposal, commercial terms, POC and delivery, ensuring frontline insights flow directly to decision-makers.

Closing: Four Key Takeaways

Cheung closed his speech with four key conclusions:

1. AI agents embed AI within production systems. Capability boundaries expand and purchasing patterns shift, bringing AI spend into workforce cost pools.

2. AI Roll-up represents a new industrial organisation paradigm. The North American model pairs capital control with AI engineering overhauls, while the Chinese model combines M&A integration with AI transformation plus organic agent deployment on the client side.

3. General foundational models will not dominate every use case. Anthropic’s success in specialised vertical models demonstrates the trend toward industrial specialisation and segmentation.

4. Integrated stacks offer a viable route for enterprises to scale AI. Bairong’s  AICC business rollouts have produced early validation for the combination of vertical models and enterprise-grade AI agents.

As a state-of-the-art (SOTA) AI player specialising in AICC, Bairong centres its offering on proprietary vertical speech foundational models and enterprise-grade AI agents delivery capabilities. It is charting a China-native path for scalable AI deployment amid the AI Roll-up wave.