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Records Management 
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For years, digitisation meant one thing: taking paper and making it digital. Scan a document, save it as a PDF, and move on. That approach solved the storage problem but left a bigger one untouched. The information inside those files remained essentially invisible, locked inside image files that computers could not read, search or act on. For organisations managing large volumes of records and business information, that gap between “digitised” and “usable” has real consequences. AI is closing that gap, and quickly, and we’re sitting at the intersection of it: handling both physical records at scale and digitisation initiatives at scale.
Why traditional document scanning is no longer enough
A scanned document is, at its core, a photograph of text. The file exists digitally, but organisations cannot easily search for a specific clause in a contract, extract a date from an invoice, or run compliance checks across scanned HR records without opening each file manually. As The AI Journal notes, millions of businesses digitised their paper records years ago, yet employees still waste hours every week searching through folders, renaming files and manually sorting documents. We’ve talked about this many times before: discoverability might sound boring, but it costs organisations and the global economy countless billions. The files exist digitally, but the information inside them remains locked away.
The scale of the challenge is larger than many organisations expect. Doxis’ 2025 IDP Market Study found that 61% of document processes still involve paper, and 48% of enterprises expect their paper use to increase despite years of digital-first initiatives. That reliance on paper carries real costs in retrieval time, storage overheads, data entry errors and compliance risk, highlighting the need for more effective records and information management.
How AI and Intelligent Document Processing (IDP) unlock business value
Modern AI-powered document processing does something fundamentally different from traditional scanning. Rather than creating an image of a document, these systems interpret the content within it. They read, classify, and extract information automatically, turning static files into structured, searchable, and actionable data.
This is made possible by a combination of technologies: Optical Character Recognition (OCR) to convert printed or handwritten text into machine-readable formats, Natural Language Processing (NLP) to understand context and meaning, and machine learning models that improve over time. Together, they form what the industry calls Intelligent Document Processing (IDP).
The ambition behind these systems is significant. As idp-software.com reports, NVIDIA’s Nemotron Parse models represent this evolution, moving beyond “simple text scraping” to systems that interpret documents “as a human would by recognising structure, relationships and context”. That shift from pixel recognition to genuine document understanding is what separates today’s AI-powered document processing and information management solutions from the OCR technology of a decade ago.
AI document processing: The ROI and productivity benefits
The adoption figures reflect genuine results rather than hype. According to research compiled by Sci-Tech Today, IDP reduces document processing time by 60% to 70% compared to manual workflows, and companies using advanced IDP systems achieve a return on investment of between 200% and 300% within the first year of deployment. AI-driven platforms are reaching data extraction accuracy rates of up to 99% for structured and semi-structured documents.
Adoption at the enterprise level is accelerating accordingly. According to Docsumo, 63% of Fortune 250 companies have already implemented IDP solutions, with the financial services sector leading at 71% adoption. The market reflects that momentum: Fortune Business Insights valued the global IDP market at US$10.41 billion in 2025 and projects it will reach US$88.91 billion by 2034, growing at a compound annual growth rate of 26.8%.
“Crown is uniquely positioned at the intersection of physical records management, digitisation and digital transformation. The question is no longer “How many documents can we scan?” but rather “How much value can we unlock from the information we already hold?” By combining secure records management, intelligent capture, content services and AI-driven processing, we can help customers transform archives from passive storage assets into active sources of operational intelligence and compliance insight, helping them derive greater value from their business information. This shift from storage to intelligence is where the future of information management is increasingly heading.”
David Fathers, Regional Director, Crown U.K. and Ireland
How AI improves records management and compliance
For organisations in the records management and information management space, the implications are practical and immediate. Scanning a box of paper files has always been the first step, not the destination. The real value lies in what happens after: being able to retrieve, cross-reference and act on that information without manual intervention.
AI changes that calculus. A scanned invoice can be automatically classified, have its key fields extracted and be routed for approval without a person touching it. A digitised HR file can be indexed by employee, date range and document type in seconds. Legal and compliance records can be flagged against retention schedules automatically, reducing the risk of either premature destruction or unnecessary long-term storage.
The benefits compound at scale. Organisations processing hundreds of thousands of pages each year see the greatest gains, but even smaller operations benefit from the shift away from manual indexing and the errors that come with it. idp-software.com reports that intelligent automation is achieving over 99% accuracy in automatic data capture, with systems capable of delivering up to an 80% reduction in repetitive manual tasks.
What to consider when choosing an AI document processing solution
Not all AI document tools are built the same. When evaluating a solution, organisations should look beyond OCR accuracy and consider whether the system can handle the variety of documents they work with handwritten notes, mixed-format files, low-quality legacy scans and multi-language content.
Integration matters as much as extraction. A system that can identify and classify documents but cannot connect to existing records management and information management platforms, ERP systems or compliance workflows creates new silos rather than eliminating old ones. Cloud compatibility, role-based access controls, and audit trail functionality are also worth evaluating, particularly for organisations operating under regulatory requirements.
Security considerations deserve early attention. AI systems trained on document data raise questions about where that data goes, who can access it and how models are updated. Organisations handling sensitive records and business information need clear answers from any vendor before committing.
Moving beyond storage: Unlocking information intelligence with AI
Digitisation was never really about paper. It has always been about access: being able to find information when you need it, sharing it securely, and trust that it is accurate. Traditional scanning delivered the first part. AI is delivering the rest.
For organisations still measuring digitisation success by the volume of pages scanned, the next step is to ask a different question: what can we actually do with that information now? The technology to answer it is already here.
Get in touch today and discover how to unlock greater value from your records and information. We’ve been managing, storing and archiving physical and digital records for decades, and are uniquely placed to help organisations improve information discovery and make better use of their business information.