An AI-powered OCR That’s Intelligent and Boosts Your Use Cases? I’m In!

ECM expert Dr John Bates reflects on interesting new analysis of the rise of the successor to OCR

For decades, businesses, including healthcare and government, have depended on OCR (Optical Character Recognition) and related approaches to extract relevant information from business documents, and pipe them into other systems. 

In fact, OCR-type document processing has become such a standard part of the document management toolkit that you could be forgiven for thinking it’s no longer revolutionary. That’s an understandable view, but be prepared for some assumptions to be challenged. New data shows that OCR and its related approaches are undergoing a complete transformation.  

At the core of this revolution is the emergence of next-gen OCR, intelligent document processing (IDP). Essentially, traditional OCR has been radically extended and powered-up with AI techniques like deep learning and large language models. As a direct result, IDP can now handle much more complexity, making it possible to confidently process previously tricky document extractions, including handwritten texts, low-quality scans, and ambiguous formats.

The result is far more effective extraction of meaning from documents. This means that the integration of these advanced features marks the beginning of a new era, where document understanding is not only faster, but also significantly more accurate and context-aware.

What real customers are doing with AI

How do I know all this? Because we asked information management professional body AIIM, as part of its ongoing Market Momentum Index research program to go out to market and ask. Working in close partnership with specialist research team Deep Analysis, the result is a true snapshot of what’s really happening with OCR.

We now have a deeper understanding of how buyers and users of IDP a) approach this technology, b) the opportunities that AI (artificial intelligence) is opening up for it, and c) the challenges of implementing IDP while driving measurable ROI and business value.

The research included 600 enterprises across the United States and Europe. To participate, each company had to have revenues exceeding $10 million, employ more than 500 people, and operate in key industries—meaning this is serious work happening at serious brands.

The key findings are these:

78% of companies are operational with at least some form of AI
Just 12 months back, stalled projects and concerns about AI caused many to predict this was another hype cycle that would deliver litte actual change. But IDP is practical AI, and the data shows a dramatic shift—at least for IDP-based projects. While many existing solutions may not reflect the advanced AI-powered systems that define cutting-edge IDP, and legacy solutions based on conventional OCR and simple automation dominate, IDP adoption is now widespread and growing and most organizations are in the early to intermediate stages of AI maturity.

66% of new IDP projects are replacing existing systems
The rise of GenAI and LLMs has hugely disrupted the IDP market. Innovative startups and scale-ups are taking market share, while legacy vendors burdened by technical debt struggle to catch up. The fact that the vast majority of this new wave of IDP projects are replacing existing systems shows that this trend may not last much longer. Dissatisfaction with first-generation platforms—often limited in flexibility, scalability, or accuracy—combined with rapid technological evolution, has created strong demand for future-proof, AI-agnostic platforms that integrate evolving AI tools without constant rip-and-replace cycles.

A slew of new IDP use cases 

IDP is rapidly moving beyond traditional back-office functions like invoice and claims processing. Users report major expansion into customer-facing and compliance-heavy workflows, including licenses and permits, KYC onboarding, contracts/agreements, and HR documentation. For example, a 2025 IDP-enabled KYC flow might involve parsing ID cards with both images and text, performing fraud detection, and archiving in a compliance-ready format. You really need the power and speed of AI-powered content automation to even think about such an application, so these kinds of projects are finally taking off.

Paper is far from dead
61% of IDP processes still include paper documents, and 48% expect paper volumes to actually increase next year. The reason is very encouraging, as in sectors like healthcare, banking, and government, paper is still used, but it’s quickly being captured into secure, integrated IDP workflows—making it far more visible, valuable, and actionable than ever before.

The IDP bottomline

Though each industry AIIM looked at has its own drivers—healthcare seeks to reduce workload, governments focus on cost control, and manufacturers want speed—there is a clear IDP universal value proposition: empowerment through automation. Today’s smart version of OCR helps us focus on critical decisions while machines handle repetitive tasks, increasing throughput and responsiveness across all sectors.

We have a long way to go. Despite all the advances this study reveals, automation levels are still modest. Many organizations, even those with 56% of processes automated, still handle tens of thousands of documents manually. Yet these trendlines show that full, or near full, digitization is 100% achievable. The key lies in designing systems that can intelligently handle exceptions, escalating uncertain cases to human reviewers when needed. 

Rather than eliminating human roles, the focus should be on hybrid systems where automation handles the bulk, and humans manage the edge cases. Whatever the approach, it’s clear that IDP is no longer just about documents, but a key evolving catalyst for the convergence of content, AI understanding, and workflow automation. 

The author is CEO of SER Group, a global leader in ECM and Intelligent Content Automation