AI Native - The Mandate to Transform Your Company
In this book, Dr. Kai-Fu Lee offers a clear roadmap for how to re-structure enterprises with powerful agentic AI at the center of the enterprise, and reveals the power and potential of using AI to tap into the hidden trove of knowledge inside companies - led by a strong CEO mandate. English copies will be released in fall 2026.
Establish the CAIO role and make AI transformation accountable to the P&L
The No. 1 leader must lead personally
CEO, CAIO, and CIO relationship architecture
CAIO
Chief AI Officer (Strategist)Advise strategy · Drive implementation · Report recommendations
CEO
First accountable owner of AI transformationSet strategy · Make final decisions · Own outcomes
CIO
Chief Information OfficerEnsure IT stability · Support the business · Monitor progress
CAIO (Brain · Intelligence Orchestration)
Chief architect of intelligence
- Resource Sensing
- Intelligent Scheduling
- Load Optimization
- Model Selection
- Cost Management
- Strategy Planning
The compute grid for intelligence
Unified scheduling · Elastic supply · Efficient utilization
CIO (Utilities · Foundation Assurance)
Responsible for infrastructure, compute, and the grid
- Hardware Management
- GPU Compute Management
- Storage Management
- Network Control
- Availability Assurance
- Cost Reduction and Efficiency Gains
CAIO: build the intelligence system
(System of Intelligence)
The essence of process reconstruction: turning workflows into skills (Skillification)
The CAIO does not rewrite software, but uses multi-agent networks to work across existing systems and take over processes
- Cross-system orchestration replaces manual cross-system handoffs
- Codify reusable skills
- Continuously learn and optimize to build a competitive moat.
- Respond faster to business changes and reduce process costs
CIO: protect the systems of record (System of Record)
Access data through APIs
Core objective: stable, reliable, and robust IT systemsBuild an AI decision hub so models truly understand the business
The four building blocks of an enterprise AI decision hub
Brain + map + GPS + operating system form a complete enterprise-grade decision system.
Business Knowledge Support
Support reasoning and judgment
Ensure secure business implementation
1 Brain: Model
- Core Reasoning Engine
- Responsible for understanding, inference, and forming judgment
- Like a CPU
- Capabilities keep improving and costs decline rapidly
- Coordinate other systems
2 Map: Ontology
- Use semantics to define the business world
- Define core objects such as customers, contracts, and approval nodes
- Describe relationships between objects
- Let AI truly understand the company
- Align judgment with business logic
Decision Hub Business Knowledge Support
3 GPS: Enterprise Real-time Context
- Ontology is the static map; GPS provides real-time state
- Track transactions, status changes, and approval progress
- Preserve event streams in chronological order
- Answer what is actually happening now
- Provide real-time evidence for grounded judgment
4 Operating System
Cut through layers of reporting so the No. 1 leader sees operating truth
It is hard for the CEO to see the company's true state
- Performance Trends
- Key Metrics
Active Filtering
Only selected priorities are reported
Information Cocoon
Limited perspective and lack of dissent
Lossy Compression
Information is simplified and details are lost
Rewrite organizational accountability so DRIs own operating outcomes
DRI, the micro-CEO in the AI era
The strongest individual contributor is not merely an executor
Drive to the End
Own outcomes all the way through
No excuses and no easy surrender
Self-driven
Think proactively and act proactively
Set goals independently and keep moving
Directly Responsible Individual
Outcome-orientedValue Loop
Horizontal Coordination
Coordinate resources across departments
Drive collaboration and secure support
Coordinate AI Employees
Understand the business, ask good questions, and verify
Drive AI to complete tasks
Start by Rewriting the P&L
The CEO leads personally to reshape the decision hub and execution path
Many AI projects, unchanged financials
Bottom-up pilots often create demos, not business impact.
The CEO must lead personally, appoint a CAIO reporting directly to the CEO, and define AI success by revenue, margin, cash flow, retention, productivity, and cycle time.
Lots of data, but models do not understand the business
Pushing enterprise data directly into a foundation model often leads to garbage in, garbage out.
01.AI builds the AI decision hub with four core components: the model as the brain, Ontology 2.0 as the business map, real-time context as GPS, and the operating system as the execution layer.
Many reports, distant truth
In traditional hierarchies, truth is filtered layer by layer.
Boss AI brings the CEO closer to operating reality through full-domain sensing, execution closure, strategic simulation, and organizational culture engines — making commitments traceable, risks visible, and talent observable.
More headcount, scattered accountability
Legacy organizations add people and layers, but accountability remains fragmented.
01.AI empowers DRIs with goals, boundaries, compute budgets, and multi-agent capabilities — turning them into micro-CEOs who can set direction, coordinate resources, and own outcomes.
Top-down Project Cases: Enter the Deep Waters of Transformation and Keep Delivering Value
Co-creating the Future of Sovereign AI
Partnering with Kazakhstan to build national-level sovereign AI
Key Outcomes
- Jointly developed AlemLLM, a Kazakh-language large language model
- Established the joint venture Q.AI, with a former Vice Minister of Artificial Intelligence and Digital Development of Kazakhstan appointed as CEO
- Dr. Kai-Fu Lee was invited to join the AI Development Council chaired by the President of the Republic of Kazakhstan
- Kazakhstan issued a Presidential Decree adopting Dr. Kai-Fu Lee’s recommendation to advance pilot programs for AI-enabled education
- Explored AI implementation across multiple government sectors, including with the Ministry of Energy of the Republic of Kazakhstan and the Ministry of Tourism and Sports of the Republic of Kazakhstan
Dr. Kai-Fu Lee Holds In-Depth Exchanges on AI Development with Leaders from Countries Participating in the Belt and Road Initiative
Key Outcomes
- Vietnam Party General Secretary and State President To Lam met with 01.AI CEO Dr. Kai-Fu Lee
- Serbian President Aleksandar Vučić met with 01.AI CEO Dr. Kai-Fu Lee
Government AI Drives Regional Development
Partnering with Sichuan Neijiang High-tech Zone to build an AI new quality productivity highland
Key Outcomes
The project represents an overall scale of more than RMB 150 million. Leveraging the industrial base, it will focus on the deep integration of large models and AI agents with local competitive industries, creating a new industrial hub.
Partnering with Wuhan Qiaokou District to co-build Hanjiangwan Digital Intelligence City
Key Outcomes
Leveraging its full-stack AI capabilities, the company will closely align with Qiaokou’s industrial layout and digital transformation needs, jointly building a strategic AI industry hub that extends across Central China and serves the nation.
Industrial AI Transformation and Growth
Partnering with Global 500 company Charoen Pokphand Group to build the Future Farm
Key Outcomes
The CEOs of both parties jointly launched the joint venture “Wanfeng Intelligence” to advance a five-layer integrated smart agriculture system, increasing automation from 20% to 40%, reducing mortality and culling rates by 5%, and enabling flexible production-sales coordination.
