Expectations for IDP are high: the global intelligent document processing market was valued at just under $8 billion last year and is projected to reach around $67 billion by 2032, reflecting a robust compound annual growth rate of 30.1%. On the surface, it certainly sounds useful — but an information management specialist might still wonder if it’s truly ready for prime time. The answer is yes: IDP is a highly promising technology, finding new ways to support organizations. Yet, perhaps surprisingly, even in 2026 its rise is occurring alongside a renewed demand for paper.

Fresh data from our new research conducted by the Association for Intelligent Information Management (AIIM) allows us to reveal how IDP is being used in practice across multiple major industries.

AIIM partnered with Deep Analysis to interview 600 enterprises across the U.S. and Europe. Each organization had over $10 million in revenue, more than 500 employees, and operated in key industries. The study examined how companies are approaching IDP technology, how they leverage AI to unlock new opportunities, and the challenges they face in implementing IDP while achieving measurable ROI.

Taken together, the research highlights a larger trend: document extraction is entering a transformative phase, driven by rapid AI adoption, expanding use cases, and evolving buyer behaviors. The findings offer a detailed look at how organizations are navigating this evolution.

Let’s take a closer look at the results.

The study found that a majority of enterprises — 65% — are actively considering or implementing new IDP initiatives, with two-thirds of these projects focused on replacing legacy OCR and document capture systems. This strong demand highlights a market ripe for innovation, driven in large part by the capabilities of GenAI and large language models (LLMs).

For the OCR industry, the message is clear: ambitious IDP startups and scale-ups are seizing this momentum, while established vendors struggle under the weight of technical debt and slower adaptation.

The research also revealed that IDP is no longer limited to back-office tasks like invoice processing. Front-office applications — such as managing HR files, contracts, licenses and permits, and KYC onboarding — have become the dominant use cases for modern document extraction and information capture, demonstrating AI’s growing ability to handle complex, unstructured content at scale.

The rise of external user involvement, reported at 62%, further underscores this shift, made possible by cloud-based DocAI tools. For CIOs, the implication is clear: IDP strategies must evolve to support these broader, customer-facing workflows and unlock the full potential of AI-driven document automation.

Data security and privacy emerged as the top concern among the 600 respondents, reflecting heightened scrutiny over AI’s access to sensitive information and the potential for LLM hallucinations. As a result, enterprises must prioritize solutions with strong compliance frameworks, including private cloud or on-premises options.

The second-largest challenge is integration, underscoring the importance of interoperable standards — such as MCP and APA — and the value of embedded IDP offerings within widely used platforms like Salesforce or Microsoft 365. Addressing these challenges is critical for organizations seeking to scale AI-driven document automation effectively.

Despite extensive digital transformation efforts and initiatives like AIIM’s “World Paper Free Day” each November 6, 61% of IDP processes still involve paper. Surprisingly, nearly half of respondents — 48% — expect their paper usage to increase.

There are notable regional differences: European participants anticipate a 50% reduction in paper over the next year, compared with just 30% among U.S. firms. Yet overall, the continued reliance on paper suggests that digitization alone isn’t sufficient. To further reduce paper in core document workflows, organizations must also address cultural and regulatory barriers, such as the ongoing use of fax in global healthcare and certain pockets of finance and government, in order to achieve truly paperless operations.

GenAI-powered research has emerged as the leading method for selecting IDP solutions, surpassing traditional references and analyst reports. To remain visible and relevant, vendors must optimize their digital presence for AI-driven search while maintaining transparency.

At the same time, the study confirms that proof-of-concept testing and industry-specific expertise remain essential for buyers. This underscores the importance for IDP solution providers to continue demonstrating tangible, real-world value in their offerings.

The research also highlights a potential barrier to IDP’s rapid adoption: many enterprises face significant shortages of technical and process redesign skills. Notably, IDP users report that the primary benefit of these initiatives is reduced processing time (50%) rather than headcount reductions (30%), reinforcing the notion that IDP is a productivity enhancer, not a tool for replacing people.

To maximize ROI, companies are advised to invest in change management and cross-functional training, ensuring that teams have the skills and processes necessary to fully leverage IDP’s capabilities.

While this new wave of IDP is highly useful, truly intelligent content automation is unlikely to arrive as a commodity service via your chosen hyperscaler. Even as major providers — particularly the leading public cloud players — offer infrastructure and native document AI services, these alone do not constitute complete solutions.

Business users ultimately need platforms that can orchestrate diverse services, integrate with internal systems, and build workflow-specific pipelines. This creates a valuable new role for specialists who can combine cloud capabilities with proprietary tools to deliver flexible, business-centric IDP solutions.

The key takeaway is clear: IDP is no longer just a back-office workhorse. It is moving into the core of critical business processes and demands serious attention. Perhaps surprisingly, it may soon become one of the most widely deployed AI applications across the enterprise.