Is the OCR caterpillar becoming a very useful IDP butterfly?

This is a guest blog post by John Bates, CEO, SER, in which he reviews important new findings about what’s really happening with text extraction.

OCR, which is now is being replaced by IDP, Intelligent Document Processing, is moving beyond back-office tasks like invoice processing into front-office use cases like KYC (Know Your Customer) checks to contracts and HR applications.

The advent of deep learning and large language models has opened the door to the handling of handwriting, low-quality scans, and ambiguous formats, making document understanding faster, more accurate, and context aware.

Too much legacy OCR struggled with flexibility, scalability, or accuracy, fuelling demand for future-proof, AI-agnostic systems that let CIOs integrate evolving AI tools into their document workflows without constant rip-and-replace cycles.

IDP adoption is growing

As a result, the promises of yesterday’s OCR are being brought to reality by IDP in places OCR was never used before. Research on IDP adoption across 600 enterprises in the US and Europe reveals 78% of companies are already using AI via IDP solutions across a wide range of new use cases including licenses, claims, onboarding, and medical records. With 66% of these initiatives replacing legacy OCR, there’s clearly strong demand for a modern approach to business document extraction and processing.

While invoice processing remains a high-value, repetitive task ideal for automation, organisations are increasingly moving it into customer-facing and compliance-heavy workflows, where success depends on understanding complex documents, combining structured and unstructured data, and maintaining strong audit trails for regulatory compliance.

For example, a KYC (Know-Your-Customer) workflow might require parsing ID cards containing both images and text, performing fraud detection, and archiving documents in a compliance-ready format. While yesterday’s OCR could handle parts of this process, AI-powered content automation delivers the speed and intelligence required to make applications like this fully feasible today.

Pent-up eagerness for new IDP functionality?

Going even further, the evolution of IDP demonstrates its shift from niche applications to a core component of enterprise operations, tightly integrated with ERP, CRM, Enterprise Document Management and other service platforms. In our view, this integration heralds a new category: Intelligent Content Automation, where AI-powered document understanding meets enterprise workflow automation.

Another telling figure from the study is that two-thirds of surveyed organisations report they are actively planning to replace their IDP platforms. This reflects widespread disappointment with OCR accuracy claims and limited adaptability. As IDP techniques evolve even further, organisations are increasingly seeking composable, flexible platforms that support hybrid approaches, combining rules-based tools with modern machine learning and deep learning models.

At the same time, claims of 99.5% accuracy through use of AI should be viewed with caution. While such figures may be attainable on narrow, well-structured datasets like standardised invoices, real-world variability, including scribbled notes or mixed formats, makes that level of consistency extremely challenging.

Ultimately, the focus should be on matching the right technology to each document type or workflow, based on complexity and business context, rather than simply relying on marketing claims.

We’re not doing this to get rid of people

Interestingly, only 167 of the 600 organisations surveyed identified headcount reduction as a primary benefit of IDP. Far more emphasise faster processing, improved ROI, and greater business agility. The goal isn’t to eliminate jobs, but to amplify the productivity of knowledge workers, freeing them from mundane tasks so they can focus on higher-order decision-making.

Some junior-level roles, particularly those focused on routine document handling, may be at risk. This shift is driving demand for more skilled positions centered on exception handling, process optimisation, and oversight. Implementing AI and IDP also requires significant guidance, as many organisations report that gaps in technical skills, process design knowledge, and change management capabilities are major obstacles.

To overcome these barriers, organisations need user-friendly tools that enable non-technical staff to configure, customise, and manage document workflows without coding or deep AI expertise. Features like drag-and-drop interfaces, visual workflow builders, and integration with familiar platforms such as Microsoft Teams or Office make this possible. Making IDP accessible to business users, not just IT, will be critical for broader adoption.

Not just a renaissance but a transformation

Different industries have distinct drivers—healthcare seeks to reduce workloads, governments focus on cost control, and manufacturers prioritise speed—but the universal value of IDP is clear: it empowers people through automation, allowing humans to concentrate on higher-value decisions while increasing throughput and responsiveness across sectors.

IDP success hinges on designing systems that handle exceptions intelligently, escalating uncertain cases to human reviewers. The emphasis should be on hybrid approaches, where automation manages the bulk of work and humans address edge cases.

In summary, today’s IDP is no longer just about documents, it represents the convergence of content, AI-driven understanding, and workflow automation—an evolution I think we can all welcome.

The full AIIM Intelligent Document Processing (IDP) Survey 2025 can be accessed here.