What's an AI Worker in ARPIA?

An AI Worker runs a defined workflow on your data and produces an output, such as transformed data, an operational update, an insight, or decision support. Where an AI Agent answers questions in conversation, an AI Worker carries out a sequence of steps.

Use an AI Worker when you need to run a repeatable process. If people need to ask questions about data, use an AI Agent. If you need answers grounded in documents, use a RAG AI.

What it does

• Runs a predefined sequence of steps across data processing, from ingestion to analysis
• Uses ARPIA's AI and machine learning models to analyze data, predict outcomes, and generate insights
• Produces outputs other people or processes can act on

How it works

1. Input. The Worker receives data from authorized ARPIA sources. Input can be retrieved automatically or passed in by another process in the platform.
2. Execute. The Worker runs its workflow, for example cleaning data, running an analysis, or applying a machine learning model.
3. Output. The Worker produces the result the workflow defines: transformed data, operational updates, insights, or decision support.

[VERIFY: how is a Worker triggered — on a schedule, manually, by an event, or by another process?]

Data sources

AI Workers read from authorized ARPIA components, including:

• Databases
• Data Models (Nodes)
• Neural Networks
• AI Apps

Workflow design

Each AI Worker runs a workflow you configure for a specific business need. The workflow defines which steps run, in what order, and what the Worker produces. The same Worker runs the same steps each time, which makes results consistent and easier to review.

Access and governance

• Role-based access. A Worker only reaches data that its configured permissions allow.
• Write access. [VERIFY: are Workers read-only by default like Agents and RAG AI, or can they write data, since outputs include "transformed data" and "operational updates"?]
• Scoped by workflow. A Worker can only do what its workflow defines.
• Human review. [VERIFY: can a Worker pause for approval before it writes or acts?]

For governance that applies to all AI implementations (human review, logging, change management), see AI-Driven Implementations.

Limits

• A Worker follows its workflow exactly. If the input data or business rules change, update the workflow.
• Outputs depend on the quality of the input data and the models used.
• Review outputs before acting on them in high-stakes processes, especially when the Worker runs without someone watching.

Related

• How to create an AI Worker
• What's an AI Agent in ARPIA?
• What's a RAG AI in ARPIA?