Generative AI is Transforming IDP: Here’s How to Unlock New Value
Generative AI has quickly become a transformative force across many industries, and one of the most significant advancements is its integration with Intelligent Document Processing (IDP) software, pushing the boundaries of what IDP solutions can achieve and expanding its use cases for business of all kinds. AI and its related capabilities can be intimidating, and many business leaders are unsure how to use it to maximize value and stay competitive.
The Evolution of Document Automation
IDP solutions have long been a cornerstone of digital transformation efforts, particularly in sectors like finance and banking, insurance, transportation and logistics, and healthcare, where massive volumes of unstructured data must be processed efficiently. Most IDP systems leverage OCR, ICR, machine learning (ML) models, and natural language processing (NLP) to automatically extract and process information from documents such as invoices, contracts, and forms. These AI technologies and services are the cornerstone of document process automation to onboard critical data into CRM, ERP, BPM, EHR, and other key business systems.
"It’s like having a tireless genius of an analyst by your side, dedicated full time to getting the most out of your data."
By adding generative AI capabilities into the mix, IDP is taking another significant leap forward. Powered by Large Language Models (LLMS) such as Microsoft’s Azure OpenAI Service, IDP systems can extract information from long unstructured documents and deliver deeper insights into the data as part of a decision-making process. By going beyond deterministic machine learning that’s dependent on pre-trained models or custom models, generative AI brings creative synthesis and dynamic adaptability into the fold, enabling businesses to prompt for answers pertaining to data in complex documents, or to summarize long, unstructured documents so that stakeholders can better understand and convey what the data means for their business.
Mainstream Gateways to AI
Microsoft’s Copilot is an example of how generative AI is being democratized, making it accessible for everyday business users. By embedding AI into familiar tools such as Microsoft Word, Excel, and PowerPoint, Copilot enables users to quickly produce email or campaign copy, analyze code, create original graphics, and perform other tasks using simple text prompts. While Copilot has been hailed as a game-changer for productivity, its current applications focus on time-saving benefits for individuals rather than delivering measurable business outcomes.
For instance, CFOs and other executives are often skeptical of tools that offer “soft” ROI metrics, such as time saved. When companies are investing millions in AI solutions, they are more likely to prioritize applications that drive mission-critical business outcomes–such as revenue growth, operational efficiency, or customer experience—over those that merely increase convenience for individuals and teams.
In the context of IDP, generative AI is evolving beyond mere productivity enhancements and is playing a pivotal role in automating key business tasks, especially in critical processes that rely heavily on unstructured data from documents.
Unlock Hard ROI with Generative AI
The ability of generative AI to understand and synthesize complex tasks and automate document-intensive workflows is opening new possibilities for companies to derive “hard” ROI from their AI investments. For instance, businesses can now use generative AI to automatically draft legal documents, summarize contracts, or process insurance claims—all while maintaining a high degree of accuracy and compliance.
In the financial sector, generative AI can analyze balance sheets, produce financial reports, and create projections based on historical data. The ability to automate these critical business processes, which traditionally involve hours of manual work, translates into tangible cost savings and improved operational efficiency.
"With generative AI in the mix, practically anything is possible."
Our IDP platform, KODAK Info Input Solution, integrates with the services of leading AI hyperscalers like Microsoft, Amazon, and Google, including their generative AI services. By leveraging these cloud AI services through Info Input Solution, businesses can effortlessly coordinate multiple AI techniques—such as NLP, handwriting recognition, and an understanding of data via generative AI, thus enabling a wider range of automation capabilities to support any document-centric process, from customer onboarding to contract management and beyond. With generative AI in the mix, practically anything is possible.
Expanding Business Use Cases for IDP
Powered by AI, IDP is rapidly expanding the possibilities for new business use cases. For example, in the healthcare sector, generative AI can assist in summarizing patient records or synthesizing medical research, significantly reducing the time doctors and healthcare professionals spend on administrative tasks. In the legal field, the contract review process is accelerated as a result of faster and more accurate analysis and summaries of legal contracts.
Generative AI also enables businesses to quickly analyze unstructured documents that were previously cost prohibitive to implement using traditional IDP systems. For example, customer correspondence letters, emails, meeting transcripts, and financial reports can now be converted into structured data and then analyzed for business insights. This opens new avenues for industries that rely heavily on unstructured data, and where customer engagement is critical to satisfaction and loyalty.
Challenges Ahead: Gartner’s Prediction and the Path Forward
Despite its potential, the journey of generative AI in IDP is not without challenges. According to Gartner’s recent predictions , 30% of generative AI projects are likely to be abandoned by 2025. This high abandonment rate can be attributed to several factors, including the complexity of AI implementation, the steep upfront investment required, and the high cost of licensing generative AI solutions.
The efficacy of generative AI is still being evaluated across many business contexts. While it can automate repetitive tasks, its true value will only be realized when combined with other approaches—such as supervised machine learning models and rules-based systems—to form a cohesive, scalable IDP solution. For instance, KODAK Info Input Solution integrates generative AI along with pre-trained models for specific workflows and tasks (e.g., invoice processing) to deliver a much higher level of accuracy and more comprehensive automation capabilities than generative AI alone.
Driving Business Forward with Intelligent Automation
As businesses continue to explore the potential of generative AI, its role in IDP will continue to expand, enabling companies to further automate document-centric workflows and unlock new business use cases. The ability to handle unstructured data, respond productively to complex prompts, and work in conjunction with other AI models makes generative AI a powerful tool for business transformation.
However, the rapid expansion of this technology is also leading to confusion around when, where, and how to best leverage it to realize its tremendous benefits.
Looking ahead, the companies that succeed with generative AI will likely be those that recognize its strengths and limitations. Generative AI excels when used in combination with other software processes and when applied to business-critical workflows based on tailored rules. The key for businesses is to invest in scalable platforms that can orchestrate these technologies, ensuring that generative AI can deliver measurable value in the form of cost savings, increased efficiency, and improved decision-making.
