Introducing an L0-L5 framework to help define, evaluate, and advance AI capabilities in laser cutting

Jinan, China - Bodor Laser has released the AI Laser Cutting Machine Classification White Paper, presenting a structured framework for defining and evaluating AI capabilities in laser cutting equipment.

As “AI cutting” becomes an increasingly common term across the laser cutting industry, customers are often faced with unclear claims and inconsistent definitions. While many manufacturers refer to intelligent or AI-enabled cutting functions, the industry has lacked a clear and practical framework for evaluating how intelligent a machine truly is.

Bodor Laser’s white paper aims to address this gap by defining what an AI laser cutting machine is and introducing a six-level classification system, from L0 to L5, based on the degree of decision-making performed by the machine.

According to the white paper, an AI laser cutting machine is not simply a machine with automated functions. It is laser cutting equipment that integrates artificial intelligence technologies into the cutting process and forms an intelligent closed loop across five core capabilities: perception, analysis, decision-making, execution, and optimization.

Together, these five capabilities create a complete intelligence chain. Perception allows the machine to collect information from the cutting environment. Analysis helps the system understand working conditions. Decision-making determines the optimal cutting strategy. Execution turns decisions into action. Optimization enables the system to improve continuously based on data and feedback.

Defining AI Cutting by Decision-Making Capability

The white paper introduces an L0-L5 classification system for AI laser cutting machines. The core question behind the framework is straightforward: who makes the cutting decisions, the operator or the system?

• L0: No Cutting Intelligence The operator makes all decisions, and the machine provides only basic cutting functions.

• L1: Cutting Assistance The operator remains the decision-maker, while the system assists with one or more tasks.

• L2: Partial Cutting Intelligence The operator still makes the final decision, but the system begins to provide intelligent decision-making recommendations.

• L3: Conditional Cutting Intelligence The system becomes the main decision-maker in specific scenarios and can autonomously complete part of the decision-making process.

• L4: High Cutting Intelligence The system independently completes all cutting decisions in specific scenarios.

• L5: Full Cutting Intelligence The system independently completes all cutting decisions across all scenarios.

This classification highlights the essential difference between automation and AI. Automation focuses on how a task is executed. AI focuses on whether the system can make decisions on its own.

Under this framework, L2 is identified as the entry point for an AI laser cutting machine. To be considered a true AI laser cutting machine, a system must meet two conditions: it must include the five core capabilities of perception, analysis, decision-making, execution, and optimization, and it must reach L2 or above in intelligent capability.

A Common Language for the Future of AI Cutting

The white paper provides value beyond product definition. It offers the laser cutting industry a clearer way to describe, compare, and advance AI cutting technologies.

First, it establishes a common technical language. Instead of treating “AI cutting” as a broad marketing term, the framework breaks it down into specific capabilities that can be discussed and evaluated.

Second, it provides a more measurable evaluation system. Customers can better understand what level of AI capability a machine provides and select equipment based on actual production needs rather than general claims.

Third, it creates a technical roadmap for future development. Machine manufacturers can use the framework to guide R&D priorities, while customers can use it to understand the potential upgrade path of their equipment.

Bodor Laser’s AI Development Roadmap

Bodor Laser began accelerating its AI strategy in 2025, when its self-developed enterprise AI assistant, Xiao Bang Agent, was introduced across key business areas including R&D, production, and service.

With the release of the AI Laser Cutting Machine Classification White Paper in 2026, Bodor Laser is extending its AI exploration from internal application to industry-facing methodology.

Bodor Laser has also outlined a long-term AI development roadmap, targeting L3 capability by 2027, L4 capability by 2029, and L5 capability by 2031.

For Bodor Laser, the ultimate goal of AI laser cutting is to reduce repetitive and labor-intensive work, allowing operators to shift from manual intervention to higher-value decision-making, process planning, and creative manufacturing.

By defining what an AI laser cutting machine is and how its capabilities can be classified, Bodor Laser aims to support a more transparent, measurable, and technology-driven future for intelligent laser cutting.