Turning Documents into Decisions: Intelligent Document Processing in the Agentic Era

Organizations today are drowning in data, yet much of it remains trapped within unstructured documents, PDFs, invoices, contracts, and reports. Intelligent Document Processing (IDP) is emerging as a game-changer, allowing businesses to unlock valuable insights from their documents and turn them into actionable decisions. 

In a recent SSON webinar, "IDP in the Agentic Era: Turning Documents into Decisions", experts from Base64.ai and High IQ AI explored how automation and AI are reshaping the way businesses process information. Hosted by Bethany Brown, the discussion featured Chris Maertz, SVP of Partner Ecosystems at Base64.ai, and Norman Osumi, CEO of High IQ AI, who shared their insights on the evolution of IDP, the role of Agentic AI, and the impact on finance and operations. 

The Shift from Data Collection to Decision-Making 

For decades, organizations have relied on manual document processing or outdated optical character recognition (OCR) technology, which often fails to capture data accurately and efficiently. As Maertz pointed out, most businesses struggle with the sheer volume of unstructured data, with estimates suggesting that 80 to 90 percent of an organization’s content is in non-standardized formats. 

Historically, companies have tackled this challenge with structured automation, extracting key information from documents for later use. But today’s IDP solutions go much further, allowing businesses to instantly analyze and act on data. Instead of simply pulling information from an invoice, for example, modern AI-driven systems can verify compliance, match it against purchase orders, and even automate approvals, all in real time. 

What is Agentic AI, and Why Does It Matter? 

The conversation naturally led to the concept of Agentic AI, which has been gaining traction in recent months. Unlike traditional automation, which follows predefined rules, Agentic AI operates with a higher level of autonomy. It can take a set of inputs, evaluate different data sources, and determine the best course of action to achieve a goal. 

For document processing, this means businesses can move beyond simple data extraction. AI can now evaluate documents against company policies, verify terms and conditions, and flag discrepancies without human intervention. Instead of a finance team manually cross-referencing purchase orders, an AI system can instantly confirm whether a vendor’s invoice aligns with contractual agreements and either approve it or escalate issues that require attention. 

This shift is particularly valuable in industries that rely heavily on compliance and accuracy, such as finance, healthcare, and procurement. As Maertz explained, AI-driven document processing allows organizations to not only speed up workflows but also reduce human error, ensuring better decision-making across departments. 

How CFOs are Approaching AI Adoption 

From a financial perspective, Osumi highlighted how CFOs and finance teams are navigating the shift toward automation. While cost reduction is a primary driver, the real value of AI lies in improving efficiency, enhancing data accuracy, and ensuring compliance. 

One of the biggest concerns CFOs face is the seamless integration of AI with existing enterprise systems. Organizations often hesitate to invest in new technologies due to compatibility issues, but modern IDP solutions are designed to work alongside existing ERP, CRM, and accounting platforms. Osumi stressed that AI’s effectiveness hinges on high-quality, well-structured data, making governance frameworks essential for reliable decision-making. 

Workforce adaptation is another key factor. While AI won’t necessarily replace jobs, employees need to develop new skills to work effectively alongside intelligent automation. Training in AI literacy, such as understanding how to interact with large language models and fine-tune AI prompts, will be increasingly important in the coming years. 

For organizations considering AI adoption, Osumi advised taking a phased approach. Instead of attempting a massive overhaul, companies should start with smaller, high impact use cases, gradually expanding automation as teams gain confidence in the technology. 

Base64.ai’s Approach to Intelligent Document Processing 

As an AI-first company, Base64.ai is at the forefront of making document processing smarter and more efficient. The company offers a vast library of over 2,800 pre-built AI models capable of extracting data from identity documents, financial records, insurance forms, and supply chain documents. 

What sets Base64.ai apart is its ability to handle unstructured documents without extensive configuration. Through semantic AI, the platform can understand and structure information even from documents it has never seen before. This zero-shot extraction capability means businesses no longer have to spend months training AI models or setting up complex rules-based workflows. 

Beyond extraction, the company’s Agentic Doc AI technology enables businesses to go straight from receiving documents to making decisions. For instance, rather than simply pulling data from a vendor’s sales order, AI can instantly compare it to a corresponding purchase order, flag discrepancies, and provide justifications for approvals or rejections. This eliminates the need for manual verification, significantly reducing processing time while increasing accuracy. 

What Businesses Want from IDP Solutions 

A live poll during the webinar revealed that organizations are looking for IDP solutions that not only provide quick time-to-value but also integrate seamlessly with their existing systems. Flexibility is key, businesses don’t want rigid automation tools that only work with predefined document types. Instead, they need solutions that can adapt to various formats and requirements without extensive customization. 

Compliance and security are also top concerns. As organizations process sensitive financial and legal documents, AI-driven solutions must ensure data privacy and adhere to industry regulations. Base64.ai, for example, has heavily invested in enterprise-grade security to meet these requirements. 

Final Thoughts: The Future of Document Processing 

The webinar underscored a fundamental shift in how businesses interact with documents. No longer just static records, documents are becoming dynamic assets that drive decision-making in real time. With the emergence of Agentic AI, the potential for automation extends far beyond simple data extraction, businesses can now implement systems that actively reason, validate, and execute decisions based on document inputs. 

For companies looking to stay competitive, embracing AI-driven IDP is no longer a question of if but when. As Maertz pointed out, businesses that leverage AI to transform documents into decisions will gain a significant competitive advantage in the years ahead. 

As organizations continue to refine their automation strategies, the ability to quickly and accurately process information will be a defining factor in their success.