Intelligent Document Processing Statistics 2024 By Extraction Technology

Introduction

Intelligent Document Processing Statistics: Intelligent Document Processing (IDP) is a technology-driven approach that uses Optical Character Recognition (OCR), Natural Language Processing (NLP), Machine Learning (ML), and Artificial Intelligence (AI) to automate data extraction from documents, enhancing efficiency and reducing errors.

IDP finds application in diverse sectors, including banking, healthcare, legal, retail, and manufacturing. Benefits encompass improved efficiency, error reduction, cost savings, and enhanced compliance.

However, IDP faces challenges related to data quality, integration, scalability, and data security, with an increasing role expected in streamlining document-centric processes.

Editor’s Choice

• The Intelligent Document Processing (IDP) market is experiencing robust growth. Its revenue is projected to witness a substantial increase over the next decade at a CAGR of 28.9%.
• In 2022, the IDP market generated USD 1,500.0 million in revenue and is expected to rise to USD 17,826.4 million in 2032.
• Solutions dominate the components landscape with a substantial majority, accounting for an impressive 64.8% of the market.
• Studies suggest that unstructured data makes up 80-90% of newly generated data in enterprises.
• Concerning the advantages of document processing during COVID-19, the most crucial advantages include the acceleration of document processing. Which garnered 55% of the votes, closely followed by the enhancement of employee collaboration at 54%.
• IDP can potentially cut processing time by 50% or even more, eliminating errors and profoundly boosting productivity and efficiency.
• Implementing IDP can significantly lower the chance of errors by more than half, reducing the risk by 52% or greater.
• IDP has the potential to attain an impressive accuracy rate of 99%.

Intelligent Document Processing Market Statistics

Global Intelligent Document Processing Market Size Statistics

• The Intelligent Document Processing (IDP) market is experiencing robust growth. Its revenue is projected to witness a substantial increase over the next decade at a CAGR of 28.9%.
• In 2022, the IDP market generated USD 1,500.0 million in revenue, expected to rise to USD 1,933.5 million in 2023.
• The growth trajectory continues to be impressive, with projected revenues of USD 2,420.0 million in 2024 and USD 3,301.1 million in 2025.
• By 2026, the market is set to reach USD 4,382.4 million, and this momentum is expected to persist. With revenues forecasted to reach USD 5,485.0 million in 2027 and USD 6,460.9 million in 2028.
• As we move into the late 2020s, the IDP market is poised for exponential growth. With projected revenues of USD 8,328.2 million in 2029, USD 10,423.6 million in 2030, and USD 13,436.0 million in 2031.
• By 2032, the market is anticipated to reach an impressive USD 17,826.4 million in revenue. Highlighting the increasing adoption of intelligent document-processing solutions across various industries.

(Source: Market.us)

Intelligent Document Processing Market Size – By Deployment Mode Statistics

• The global market for Intelligent Document Processing is projected to experience substantial growth from 2022 to 2032.
• In 2022, the total market revenue is estimated at USD 1,500 million. With cloud-based deployment accounting for USD 876 million and on-premise solutions for USD 624 million.
• A steady rise is expected in the following years, with 2023 increasing to USD 1,933.5 million overall, of which USD 1,129.2 million would be cloud-based and USD 804.3 million on-premise.
• By 2024, the total market is predicted to reach USD 2,420 million. With cloud-based solutions growing to USD 1,413.3 million and on-premise to USD 1,006.7 million.
• This upward trend continues throughout the decade. The market size will expand to USD 3,301.1 million in 2025, with USD 1,929 million from cloud deployments.
• The year 2026 anticipates a market size of USD 4,382.4 million, with cloud-based revenue at approximately USD 2,559.3 million.
• Advancing to 2027, the total market revenue is forecasted to be USD 5,485 million. A significant portion of USD 3,203.3 million is attributed to cloud-based models.
• By 2028, the market is expected to grow to USD 6,460.9 million, with cloud-based solutions contributing USD 3,773.2 million.
• An even larger expansion is projected for 2029, with the market reaching USD 8,328.2 million. Cloud-based revenues hitting USD 4,863.6 million, and on-premise revenues are at USD 3,464.5 million.
• The subsequent years will see a continuation of this growth, with the total market expected to reach USD 10,423.6 million in 2030, USD 13,436 million in 2031, and an impressive USD 17,826.4 million by 2032. With cloud-based deployment modes driving the majority of the revenue, forecasted at USD 10,410.6 million in the final year.

(Source: Market.us)

Global Intelligent Document Processing Market Share – By Component Statistics

• In the global Intelligent Document Processing (IDP) market, market share distribution by component is quite distinctive.
• Solutions dominate the landscape with a substantial majority, accounting for an impressive 64.8% of the market.
• This highlights IDP software’s and technology’s significance in automating document processing tasks.
• On the other hand, services also play a substantial role, capturing 35.2% of the market share. This category likely includes consulting, implementation, training, and support services. Which are vital in ensuring the effective deployment and maintenance of IDP solutions.
• Together, these figures illustrate the balanced ecosystem of IDP. Where both software solutions and the associated services are integral components of the industry’s success.

(Source: Market.us)

Documents with Structured vs. Unstructured Data

• Well-organized and structured documents demand less advanced technology for processing. In contrast, documents that lack structure or are less organized require more advanced and sophisticated methods. Which may include the assistance of human experts to decipher and work with them.
• These less structured documents can fall into two categories: semi-structured. Which has some organization, or is completely unstructured, lacking any discernible structure.
• In either scenario, dealing with documents lacking clear structure can be complex and challenging.
• According to Gartner, unstructured data refers to machine-printed or handwritten content that doesn’t follow predetermined rules or guidelines that computers usually rely on for classification and recognition.
• Unstructured data can take various forms, including text and non-text data, like photos with handwritten notes. It can also be found in databases that don’t follow traditional relational structures, such as NoSQL.
• Studies suggest that unstructured data makes up 80-90% of newly generated data in enterprises.
• Surprisingly, only a small fraction, specifically 18% of organizations, are harnessing the potential of this resource.
• This means that the majority, about 82%, are not fully leveraging their most valuable asset.

(Source: Gartner)

Intelligent Document Processing and Optical Character Recognition (OCR) Statistics

• While intelligent document processing (IDP) is centered around AI, optical character recognition (OCR) is crucial in enabling end-to-end document processing within IDP.
• OCR is just one component in the architecture of intelligent document processing, and it’s important to note that not all OCR solutions available in the market are equal.
• Various companies have emerged, offering technology recognizing machine-printed characters and handwritten text.
• Legacy vendors started addressing Optical Character Recognition as early as the 1980s.
• Despite decades of research, many off-the-shelf OCR technologies still struggle to decipher handwriting today accurately.
• Even with high-quality scanners and well-prepared documents, OCR typically achieves only a 60% accuracy rate before encountering limitations.
• It’s worth emphasizing that intelligent document processing surpasses standalone OCR technology. IDP offers a comprehensive suite of AI models designed to process and manage entire collections of documents, encompassing machine-printed and handwritten texts.

(Source: Automation Hero, Inc.)

IDP vs. RPA vs OCR

• Intelligent document processing (IDP) significantly departs from older automated data processing systems. Unlike its predecessors, IDP captures information from documents and comprehends the context in which the data is presented.
• This expanded capability enables organizations to automate more document-related tasks than possible.
• In contrast, the primary tool for automation until now has been robotic process automation (RPA), which relies on recording basic mouse movements to automate repetitive tasks via the user interface.
• RPA typically follows predefined steps, termed a “template,” to execute more complex screen-based tasks.
• In the early 2000s, screen scraping software was an early application of RPA. Acting as a temporary solution to bridge the gap between newer and older, incompatible legacy systems.
• Today, RPA proves effective in streamlining routine, non-document-centric tasks conducted on computer screens.
• However, both RPA and OCR have limitations regarding tasks demanding higher-level decision-making.
• The key differences between RPA, OCR, and IDP lie in the inherent intelligence of AI and IDP’s capability to grasp documents with a high-level understanding of context.
• IDP stands as the next generation of automation technology, emerging from the need to surpass the constraints of RPA.

(Source: Automation Hero, Inc.)

Benefits of Digital Document Processes During Pandemic

• In the context of the COVID-19 pandemic, digital document processes have brought significant benefits to organizations.
• According to survey responses, the most crucial advantages include accelerating document processing, which garnered 55% of the votes, closely followed by enhancing employee collaboration at 54%.
• These digital processes have also increased customer satisfaction (47%) and improved employee productivity, resulting in time savings (45%).
• Additionally, they’ve facilitated document access, editing, and sharing while enabling remote work (44%).
• Other notable benefits include reductions in printing and storage costs (37%), ensuring document tracking and data security and compliance (both at 36%), and maintaining or even increasing revenue (35%).
• Furthermore, digital document processes have enhanced document workflow flexibility (33%), increased employee engagement (32%), and provided opportunities to leverage data analytics and gain valuable insights (32%).

(Source: Statista)

Benefits of IDP Implementation

• Companies that have embraced IDP solutions to automate their workflows have experienced significant benefits, including a remarkable reduction in processing time and a substantial decrease in labor costs, often reaching up to 30%.
• IDP can potentially cut processing time by 50% or even more, eliminating errors and profoundly boosting productivity and efficiency.
• The introduction of automation into the workplace typically results in a return on investment (ROI) ranging from 30% to 200% within the first year, primarily driven by savings in labor costs.
• Employees can allocate more creative energy to the company’s core activities by eliminating time-consuming tasks.
• For example, an IDP implementation saved a financial services company approximately $2.9 million annually by halving its manual extraction workforce.
• Similarly, an engineering firm reduced its RFP response time from three weeks to just one week with the help of IDP, enabling it to process 400% more RFPs compared to the previous scenario, where 80 employees had to manually interpret complex diagrams in documents.
• Implementing IDP can significantly lower the chance of errors by more than half, reducing the risk by 52% or greater.
• IDP has the potential to attain an impressive accuracy rate of 99%.
• A native IDP solution built around AI can greatly speed up data extraction, increasing the rate by as much as tenfold, all while maintaining data extraction accuracy of nearly 99.9% across various document formats.
• Besides enhancing individuals’ efficiency and job satisfaction, it’s not unusual to observe cost reductions of as high as 70%.

(Source: Nuummite, Roboyo, Parseur, Infrrd, Datasemantics, Turbotic)

Recent Developments

Acquisitions and Mergers:

• IBM acquires Databand.ai: In 2023, IBM acquired Databand.ai, a data observability platform, for $140 million. This acquisition strengthens IBM’s Intelligent Document Processing (IDP) capabilities by improving the ability to monitor, analyze, and optimize document processing workflows through better data visibility and machine learning.
• UiPath acquires Re:infer: UiPath, a leader in automation and IDP, acquired Re, a London-based NLP company, for $125 million in mid-2023. This acquisition enhances UiPath’s automation platform by improving its natural language processing (NLP) capabilities, allowing for more sophisticated document understanding and extraction in business processes.

New Product Launches:

• Kofax launches TotalAgility Cloud: In early 2024, Kofax launched TotalAgility Cloud, an enhanced cloud-based IDP platform that integrates AI and machine learning for faster, more accurate document processing. This product aims to provide better automation for enterprises handling large volumes of unstructured data, such as invoices and contracts.
• ABBYY’s Vantage 2.5: In 2023, ABBYY introduced Vantage 2.5, an AI-powered IDP platform that offers enhanced cognitive skills for document understanding. It includes pre-trained models to handle complex document workflows, enabling businesses to automate document classification and data extraction with greater accuracy.

Funding:

• Hyperscience secures $100 million in Series D funding: Hyperscience, a company specializing in intelligent document processing, raised $100 million in 2023 to expand its platform’s capabilities and invest in AI-driven document automation. The funding will support R&D to improve unstructured data processing in industries like insurance, finance, and healthcare.
• Automation Anywhere raises $200 million: Automation Anywhere, a leading robotic process automation (RPA) company with strong IDP capabilities, secured $200 million in early 2024 to develop more advanced AI features for its document automation platform. The focus is on scaling intelligent automation across industries that deal with large volumes of documents.

Technological Advancements:

• AI and NLP Integration in IDP: The integration of AI and natural language processing (NLP) has transformed IDP, enabling systems to extract and process unstructured data more effectively. By 2024, it is expected that over 50% of IDP solutions will incorporate advanced AI and NLP features, enhancing their ability to understand complex documents like contracts, legal filings, and insurance claims.
• Cloud-Based IDP Solutions: Cloud-based IDP platforms are growing in popularity, offering businesses scalability, flexibility, and real-time processing capabilities. The adoption of cloud technologies in IDP solutions is expected to grow by 12% annually, as more enterprises shift to cloud infrastructures to handle document-intensive processes.

Market Dynamics:

• Growth in IDP Market: This rapid growth is driven by the increasing adoption of automation, AI, and machine learning technologies across industries like banking, healthcare, and insurance, where high volumes of unstructured documents are processed.
• Rising Demand in BFSI Sector: The Banking, Financial Services, and Insurance (BFSI) sector is a key driver of the IDP market, with companies increasingly automating document-heavy workflows like loan processing, underwriting, and claims management. By 2025, BFSI is expected to account for over 30% of the total IDP market, reflecting the sector’s heavy reliance on document automation.

Conclusion

Intelligent Document Processing Statistics – In summary, Intelligent Document Processing (IDP) represents a groundbreaking approach to document management, utilizing advanced technologies to simplify the extraction and handling of data.

It brings advantages such as heightened efficiency, fewer errors, cost reductions, and enhanced adherence to regulations.

What sets IDP apart from traditional automation techniques is its proficiency in grasping the context of the information it manages, which proves invaluable for intricate document tasks.

With the potential for wider adoption across various sectors, IDP is poised to take on a central role in streamlining document processes and improving productivity in today’s digital era.

Nevertheless, successfully addressing data quality, integration, scalability, and security challenges is pivotal.

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