Anyone who hasn’t been living under a rock somewhere would have heard about Artificial Intelligence (AI) and how it is going to transform, well, everything. What few people know is just how fast the AI landscape is actually shifting, right beneath our feet.

Intelligent Document Processing, or IDP, one of the mainstays of AI applications, too has been undergoing rapid changes. Perhaps too rapid to notice! IDP reduces the need for human intervention. For businesses handling significant amounts of information, implementing an IDP solution presents an excellent opportunity to enhance process efficiencies, cut costs, and boost profits.

IDP used to combine a bouquet of techniques, including machine learning and NLP, with tools like optical character recognition (OCR) to automate data extraction, analysis, and processing. However AI has rapidly moved from there to recurrent

neural networks (RNN) to convolutional neural networks (CNN) to transformers with every detail being captured in end to end fashion.

Not so long ago, IDP relied on accurate and high-quality input data which is not the case right now.

Unstructured data found in documents may be incomplete, inconsistent, or contain errors, which can impact the accuracy of IDP solutions.

Let me give you an example.

Let’s assume that you are trying to automate the processing of invoices using IDP. The IDP solution extracts data such as the invoice number, date, supplier name, and amount from invoices and enters it into the organization’s ERP system.

If one of the invoices contains a typographical error in the supplier name—instead of “XYZ Inc.,” the supplier name is “XYY Inc.” or maybe an invoice has missing line items or inconsistent formatting. In such cases, the IDP solution would not have
been able to accurately extract all relevant data.

This would have resulted in incomplete or inaccurate data entering the ERP system So, organizations would have had to implement measures to address data quality issues such as data cleansing, normalization, and error handling.

Today, transformers with their end-to-end object detection and learning capabilities really, well, transformed AI (pun unintended!) Irrespective of the shape or form of your data, transformers can help you make sense of it.

So, what are the challenges you’re likely to face in your IDP implementation?

Challenge 1 – Integrating with existing systems

IDP solutions in isolation may not make a lot of sense for organizations. It has to be integrated with best-of-breed ERPs, CRMs, or CMS. This can be challenging, especially if these systems were not designed with IDP in mind. Take an example of integrating an IDP solution with an ERP system.

This can be challenging because the two systems may use different authentication protocols or data formats, making it difficult for them to communicate with each other.

Some differences could be:

• IDP solution may use the SAML protocol for authentication, while the ERP system may use a proprietary authentication protocol. Organizations could easily take an OpenAI route but prefer more “conventional” means such as emails, FTP, and zip files.

• The IDP solution may use a standard data format like JSON or XML to represent user identification and authorization data. In contrast, the ERP system may use a different format or data model.

This may require custom development work and close collaboration between the IDP vendor and the organization’s IT team to ensure a successful integration.

Challenge 2 – Regulatory compliance

Businesses must ensure that their IDP solutions comply with relevant data privacy laws, industry-specific regulations, and internal policies. The challenge gets magnified when your company operates in multiple jurisdictions.

Consider the different possibilities:

• If you operate in Europe, you must follow General Data Protection Regulation (GDPR) guidelines. You need to obtain user consent for data processing and allow users to access, modify, and delete their data.

• Suppose you are addressing the needs of the healthcare industry. In that case, you need to comply with the US Health Insurance Portability and
Accountability Act (HIPAA), which sets strict rules for collecting, storing, and transmitting personal health information.

• In the e-commerce or transaction industry, you must comply with PCI-DSS standards on any payment information you collect.

• Over and above these regulations, you may have to adhere to the organization's internal policies. The organization may have a policy requiring all user data to be encrypted in transit and at rest.

This requires a thorough understanding of relevant regulations and policies and close collaboration between IT, legal, and compliance teams to ensure that the solution meets all requirements.

Beyond regulatory compliance, to complicate things further, when developing proofs- of-concept (POCs) and during user acceptance testing (UAT) accessing production data is a strict no-no. So you have to resort to synthetic data, which is a huge
challenge in itself.

Challenge 3 – Security and Confidentiality

IDP solutions may process sensitive and confidential information, and thus require a high level of security and confidentiality.

Some of the security considerations you may want to look at include:

• Access controls—role-based access to ensure that only authorized users have access to sensitive information.

• Data encryption—encrypt all data in transit and at rest. For example, documents transmitted between the IDP solution and other systems should be encrypted.

• Secure storage—using secure servers and ensuring the data backups are encrypted and stored offsite.

• Audit trails—track user activity to identify any suspicious activity and respond quickly.

In addition, technicalities like extracting key-value pairs are other big challenges that you may face.

So, let’s say you’ve overcome all these challenges and are now ready to implement your IDP solution. Here are some things to keep in mind for a seamless journey:

• Communicate the benefits—organizations should communicate the benefits of the IDP solution to employees and stakeholders to gain buy-in and support. You should involve everyone affected by the change in the communication process.

• Iterate, iterate, and iterate—this is a key step in ensuring the success of the IDP implementation.

• Pilot the solution—roll this out to a small group of employees or a specific department before rolling it out to the entire organization. This would help you identify and address issues and concerns before it gets bigger.

• Monitor progress—monitor the solution's success against predefined goals and objectives. Optimize the implementation constantly to ensure that the benefits of the IDP solution are realized.

Last and certainly not the least, you have to get the buy-in of the C-suite! The challenge is the deployment is done by the IT team, the users are a different group, the influencers are different, and the final decision-makers are different! But with a good IDP solution and the benefits it offers, definitely all these challenges can be overcome!