For organizations looking to harness the power of their data, Intelligent Document Processing (IDP) has become the buzzword, promising torevolutionize how we handle and process vast amounts of data. But all this “revolutionizing” isn’t without some drawbacks – many of the mostcommon objections we see are related to cost and time investment.

It’s true, investing in AI-powered document processing isn’t cheap and it’s not as easy as hitting the easy button. Like all good things, it takes timeand eff ort. And because your data doesn’t exist in a vacuum, anything you do with or to it is going to have a ripple eff ect.

If you want to understand the true capabilities (and limitations) of intelligent document processing, look no further.

Lie #1: We can just do it ourselves

Now, hear me out: I’m not saying you can’t do it yourself – I am recommending that you work with an expert who can give you some guidance and that you make sure you have the infrastructure to support it. DIY document processing contains hidden expenses that will add up, primarily in terms of time
and lost productivity.

There are great software options out there for organizations that do have that infrastructure and are prepared to commit to the level of investment needed, but we always recommend that you don’t cut corners on support and guidance – you’ll spend way less than you would to clean up the mess of a poorly executed document processing project.

Lie #2: IDP is just advanced OCR

A common misunderstanding is equating IDP with Optical Character Recognition (OCR). While OCR is an integral part of IDP, used for extracting text from images and scanned documents, IDP’s capabilities extend far beyond. IDP utilizes sophisticated technologies like machine learning, natural language processing, and artificial intelligence to not just extract text but to understand and process the information in a nuanced and context- aware manner.

Lie #3: IDP eliminates the need for humans

Say it with me:

IDP requires human intelligence and intervention.

Many believe that IDP can fully automate and replace human involvement in document processing. In reality, IDP can offload manual data entry and processing so your employees can focus on higher-level work. Where deep contextual understanding or decision-making is needed human oversight remains crucial.

Lie #4: IDP is all about data extraction

IDP isn’t just about pulling data from documents. It encompasses a broader scope, including data validation, enrichment, and integration with various systems and workflows. The ultimate goal of IDP is to convert extracted data into a meaningful, structured, and actionable format that can drive business processes and decisions.

Lie #5: IDP systems automatically learn and improve

There’s a belief that IDP systems, powered by machine learning, autonomously learn and improve over time. However, these systems don’t magically self-optimize. They require initial training, continuous data input, and regular tuning to maintain accuracy and effectiveness, particularly when handling diverse document types and evolving datasets.

Lie #6: All IDP solutions are created equal

The IDP solution market is diverse, with each product offering unique strengths and capabilities. Some are tailored for specific document types or industry needs, while others provide more generalized functionality. Understanding the specific requirements and challenges of your business is key to selecting the right IDP solution.

Lie #7: IDP is only for large corporations

It’s a common belief that only large enterprises can benefit from IDP due to their high-volume
document processing needs. However, IDP can be a game-changer for businesses of all sizes, offering scalability, efficiency, and the ability to handle growing data processing demands.

Lie #8: Implementing IDP is quick and simple

Finally, there’s a notion that implementing an IDP solution is a straightforward and speedy
process. In reality, it involves careful planning, integration with existing systems, and both
system and staff training. True expertise in this field is akin to artistry, combining deep technical knowledge with the ability to navigate complex data landscapes. Professionals in
intelligent document processing don’t just make systems work; they ensure they work with precision, efficiency, and scalability tailored to specific business needs.

The complexity and time required for implementation can vary significantly based on the specific needs and existing infrastructure of a business. So turns out, there’s not easy button even where AI is involved.

Where you go from here We all know how tempting it can be to cut corners to save a buck, but please hear us, loud and clear:

Your data is not the place to make those kinds of cuts.

That pretty much sums up the words of wisdom I have today. If you’d like to learn more about how AI-powered document processing could help your business, we offer custom demos with your organization’s documents, or we’re happy to help you build a business case.