How does AI fit into process automation?

AI handles the parts of a process that rules alone cannot cover. Most automated workflows start rule-based, with clear triggers and structured data. But when a step involves reading varied document layouts, understanding email intent, or making a judgment call, AI fills that gap.

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In practice, this means targeted AI steps within a larger workflow. An invoice arrives in an unknown format: AI reads and extracts the data. A customer email needs routing: NLP classifies the intent and sends it to the right queue. An expense claim needs approval: a model trained on historical decisions flags unusual cases for review.

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Roborana uses off-the-shelf AI services (Azure AI, OpenAI) where they solve the problem, and builds custom models only when the use case demands it. We assess whether your process has enough data to train on and enough volume to justify the investment. If not, we start with RPA and layer in AI as the need grows.

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The result is automation that handles complexity without over-engineering. AI is a tool within the workflow, not a standalone solution.