The Roles of AI

There Are Fundamentally Only Two Roles for AI

Despite the rapid pace of innovation and the growing complexity of Artificial Intelligence (AI) applications, every practical use of AI reduces to one of two core roles:

These two roles provide a clear foundation for thinking about how AI should be designed, deployed, and governed. Whether the AI is generating natural language, driving a car, or automating a claims review process, it is either being used as a tool or acting as a performer.

The AI Role Matrix

To help organizations understand and plan for the appropriate use of AI, we present the AI Role Matrix. This framework classifies AI systems using two dimensions:

• Role: Whether the AI is used as a tool or functions as a performer.
• Behavior: Whether the AI acts according to fixed rules or adapts based on learning or reasoning.

This results in a simple but powerful two-by-two matrix that allows organizations to categorize any AI deployment and determine the appropriate level of oversight and integration.

Understanding the Two Dimensions

AI Role: Tool to Agent

On the horizontal axis, the role of AI ranges from tool to agent. Tools are used by a person or another system. They do not act independently. Agents, on the other hand, perform tasks themselves. They may use tools, but they own the task and carry it out.

AI Behavior: Deterministic to Autonomous

On the vertical axis, the behavior of AI ranges from deterministic to autonomous. Deterministic AI follows predefined logic or rules without learning or adaptation. Autonomous AI adapts its behavior over time based on input, context, or experience.

The Four Quadrants of AI Function

The AI Role Matrix yields four primary types of AI systems:

Preserving Human Agency

Understanding the role and behavior of AI is critical to preserving human agency. As AI systems become more autonomous and begin to act as agents, organizations must ensure that accountability remains with humans, even if the AI performs the work.

This is not achieved by limiting what AI can do. Rather, it requires the implementation of clear governance mechanisms. These include human-in-the-loop oversight, explainability, transparent decision models, and responsible orchestration.

The AI Role Matrix makes it easier to determine where such safeguards are needed, and which AI systems require higher levels of control or supervision.

The Augmented Intelligence Sweet Spot

While full autonomy may be desirable in some scenarios, many of the most successful AI applications today fall into the area where humans and AI work together. These collaborative systems:

• Allow AI to suggest, summarize, or recommend
• Enable humans to make final decisions
• Preserve context, judgment, and ethical considerations

This balanced use of AI aligns with what some call conditional autonomy or shared agency. It combines the strengths of both human reasoning and machine intelligence. In the AI Role Matrix, this sweet spot lies between adaptive tools and autonomous agents.

Swarm Agents and Ecosystem-Level AI

Some advanced AI deployments consist of multiple autonomous agents working together. These are often referred to as multi-agent systems or swarm agents. While they fall under the category of autonomous agents, they add a new layer of complexity:

• Each agent may act independently toward a shared goal
• Coordination is decentralized and dynamic
• The system exhibits emergent intelligence, not pre-scripted behavior

These systems require new forms of orchestration, such as protocol-based interaction, distributed governance, and model-based contracts that define how agents collaborate and share responsibility.

Why the AI Role Matrix Matters

The AI Role Matrix provides a clear and actionable way to:

• Identify the appropriate use of AI in a given context
• Ensure proper governance, accountability, and transparency
• Design AI deployments that align with human values and business goals
• Support modular, flexible architectures that incorporate tools, agents, or both

Whether you are integrating AI into a clinical workflow, automating a financial process, or building decision-centric business applications, understanding the role of AI is foundational to success.

Aligning with Trisotech Solutions

Trisotech enables organizations to take full advantage of this framework through:

• BYOAI (Bring Your Own AI) strategies, allowing external or internal AI to be integrated as tools or agents.
• Decision Centric Orchestration, where BPM+ (BPMN, DMN, CMMN and SDMN) models define intent and control flow.
• AI TRUST governance framework, ensuring human accountability in AI-enhanced automation.
• Model Context Protocol (MCP), enabling seamless interaction between autonomous agents and model-defined services.

Explore the Right Role for AI in Your Organization

If you are planning or scaling your use of AI, start with the AI Role Matrix. It offers a simple, structured way to classify your systems, avoid risk, and unlock the full value of AI across your organization.