Business process automation has been transforming operations in many industries for decades, but the concept has taken on new meaning with the emergence of artificial intelligence and the many AI services that are now available. Companies all over the world are racing to incorporate AI into as many areas of their business as possible, with the hope of achieving unprecedented productivity and efficiency that can propel their business forward with sustainable growth.
AI has brought about rapid change, faster even than the internet did in the 1990s or cloud computing a decade later, and yet we’re still in the early days of its evolution and practical applications for business. The race to automate with AI is just getting started, and business leaders are grappling to determine how best to position their organizations to compete and succeed over the long term.
The role of IDP in the expanding scope of automation
The term intelligent document processing (IDP) can mean different things depending on the industry, but at a high level, end-to-end automation is the comprehensive automation of business processes from start to finish, eliminating human intervention wherever possible. This concept spans across various domains including manufacturing, supply chain management, customer service, finance, and more. The goal is to create a self-sustaining system where individual processes are automated and interconnected, enabling seamless data flow and operational coherence.
As cold as it might sound to seek to eliminate the manual handling of data, this level of automation is often considered the elusive “holy grail” that promises extraordinary cost savings and impenetrable competitive advantages. Human resources can then be focused where people excel—things like relationship building, customer service, and strategic decision-making.
Every industry has its own challenges with automation, but one facet of daily operations that practically all businesses share is the need to onboard information, process it, and get it where it needs to be. This is the domain of IDP, and it plays a critical role in the changing nature of automation.
IDP leverages many technologies, including optical character recognition (OCR), intelligent character recognition (ICR) for understanding handwriting, natural language processing (NLP), and machine learning (ML) to automatically classify, extract, and process data from any document, such as invoices, bills of lading, insurance policies, IDs, bank statements, and so on. This capability is essential for handling large volumes of unstructured data that traditional automation tools struggle with.
By training document models with these advanced tools and algorithms, IDP transforms unstructured data into structured formats, enabling seamless integration with other automated systems that rely on structured data—while improving data accuracy and consistency. By automating document-related tasks, businesses can significantly reduce the time and resources spent on manual data entry and verification.
For example, in banking, the right IDP automation solution can dramatically impact new client revenue by reducing the alarmingly high abandonment rate of 50%; clients opening new accounts spend far less time waiting on paperwork approvals and instead can get personal guidance almost immediately.
Integrating IDP with AI hyperscalers
With so many AI startups emerging and a constantly changing technology landscape, the winning strategy for most businesses is to step off the racetrack and instead rely on the trusted AI services of the biggest companies in the space: the “hyperscalers” that possess the resources and technology to stay ahead in the race toward optimal efficiency and productivity.
The ability to integrate an IDP solution with AI hyperscalers like Microsoft, Google, and Amazon has become key to success, as these tech giants offer robust AI services to enhance and future-proof data automation processes from start to finish.
Microsoft Azure offers support for IDP software through services like Document Intelligence, which uses machine learning to identify and extract key-value pairs and tables from documents to facilitate automated data processing. Microsoft’s Power Automate platform also integrates seamlessly with some IDP solutions, enabling businesses to create automated workflows that connect various applications and services.
Google Cloud’s Document AI is another powerful tool for IDP integration. It uses Google’s advanced machine learning models to extract key data from a wide range of document types and formats. By integrating Document AI with the right IDP tools, businesses can build end-to-end automation solutions that handle everything from data ingestion, processing, and routing, all the way to generating insights, analysis, and reports.
Amazon Web Services (AWS) offers IDP services through Amazon Textract, which uses machine learning to extract text, forms, and tables from digital documents. Integrating with Textract makes it possible to build sophisticated document automation solutions that leverage the scalable infrastructure and extensive toolset of AWS for processing and analyzing large volumes of document data.
Generative AI is also playing an increasingly important role in enhancing IDP solutions. For example, these tools can quickly generate concise summaries of key information from large volumes of text, making it easier for users to gain insights from the data. Generative AI models also excel at processing natural language and unstructured data, enabling IDP solutions to better interpret the context and meaning of text within previously difficult-to-process sources.
To get the most out of an investment in IDP software, business leaders who are looking to transform their data onboarding and processing operations should choose a solution that’s able to connect to the trusted services of these AI hyperscalers. Doing so gives businesses the best chance to maintain a competitive advantage in the race toward peak automation and efficiency.
Get on the document automation wave while it’s still cresting
As business and technology leaders look to modernize operations and introduce new productivity solutions, “end-to-end automation” will continue to be heard in boardrooms and conference calls across the world. Different businesses and the various functions within them all have their own automation requirements, but intelligent document processing is a common thread that connects them all.
Every business needs to take in documents of diverse types from various sources, analyze and process them, and get the data into downstream systems. IDP software is changing the nature of document automation, and the companies acting now are putting their organizations in a position to win.
By automating document-related tasks and integrating IDP software with advanced AI platforms, businesses can achieve unprecedented efficiency, accuracy, and scalability.
The journey toward end-to-end automation is an ongoing process, requiring continuous innovation and adaptation. As technology continues to evolve, businesses that embrace and invest in these technologies will be well-positioned to lead in their respective industries, achieving greater productivity, cost savings, and strategic insights.
Bill Galusha is a veteran Product Marketing and Product Management professional with over 20 years of experience in enterprise software. As the Global Portfolio Solution Leader at Kodak Alaris, Bill leads the intelligent document processing(IDP) solutions team with go-to-market strategies that create business value for enterprise organizations. He is a trusted advisor and thought leader in his field, guiding market awareness for Kodak Alaris technologies and services.