Process-First Automation with Document AI and GenAI

With all the hype around generative AI, it can sometimes be difficult to separate genuine value from noise. On LinkedIn, I often see frustration expressed in comments like “GenAI can’t do maths,” “GenAI doesn’t understand this anatomy image,” or “GenAI is just a prediction engine.” These criticisms are not without merit, but they also miss the point. GenAI is, at its core, a predictive model. It processes input and predicts the most suitable output using a transformer neural network.

The real question is: How do we apply its strengths effectively, and should AI always be the first tool we reach for? At scale, the ability to predict meaning from unstructured input is incredibly powerful when applied to the right use case.

I’ve long argued that intelligent document processing (IDP) and now Document AI are only ever part of a bigger picture. Automating data capture is powerful, but we must also think about where that document came from, and where the captured data is going.

Without context, extracted data is just numbers and text. With process understanding, however, it becomes actionable intelligence that drives real outcomes. That’s why purpose-built Document AI and GenAI, combined with process improvement before automation, unlock the biggest benefits for organizations.

Document AI + GenAI + Process AI use case

A good example is customer inquiry management as an extension of sales order processing. Success here depends on understanding how customers communicate, categorizing those communications, and identifying the workstreams they create. With this knowledge, we can pinpoint where GenAI and Document AI add the most value.

The same principles apply across service, finance, or supply chain workflows.

In practice, GenAI can categorize incoming messages and extract key details from natural language. Business process management can then route tasks to the right people. Meanwhile, Document AI can extract structured data and meaning from attached documents. When combined within an efficient process, the outcome is faster, smoother, and far more scalable.

As part of our ongoing partnership with ABBYY, I’ve recently added a new example of this approach to the ABBYY Marketplace. This asset showcases how ABBYY Vantage IDP and AI can be combined into a single Process Skill that classifies incoming communications while simultaneously extracting data from attached sales orders. The result is downstream automation that routes quote requests, delivery chases, and new orders directly to the right teams, cutting response times, reducing manual triage, and freeing people up to focus on value-add activities.

You can access it here in the ABBYY Marketplace.