Power to the People: 6 ways intelligent document processing empowers your staff

Summary

Recent headlines have some people worried that artificial intelligence (AI) will soon eliminate their jobs. But the truth is that today’s advanced AI systems are actually more likely to open up new opportunities for organisations and the workers they employ.

Intelligent document processing (IDP) solutions provide a good example of this principle. They harness the power of computer vision, natural language processing, and machine learning to help individual employees become more productive and efficient. They enable your team members to engage in creative, innovative work rather than wasting time on tedious tasks. And that, in turn, allows you to reduce the time, effort, cost, and errors involved in document processing, while empowering your people.

A recent Gallup poll found that only 21% of employees say they feel engaged at work, an indicator of the phenomenon known as “quiet quitting.” In addition, stress is at an all-time high with 44% of workers saying they experience significant daily stress.

Offloading some of their more tedious and repetitive tasks to intelligent systems can give these workers the ability to focus on the more fulfilling aspects of their work. It allows them to become more productive and efficient, while also opening up the opportunity for them to learn new skills.

One of the AI-based technologies that holds the most potential for empowering workers in this way is intelligent document processing (IDP).

Intelligent document processing (IDP)

Organisations have been using automated document processing to improve efficiency for many years. Using optical character recognition (OCR), systems can extract data from highly structured forms and integrate it into databases and applications.

Intelligent document processing takes this kind of automation to a whole new level. It harnesses the latest advances in computer vision, natural language processing, machine learning, and other branches of AI to streamline workflows, and speed the process of transforming data into insights.

Industry analysts define IDP this way: “Intelligent document processing (IDP) solutions extract data to support automation of high-volume, repetitive document processing tasks and for analysis and insight. IDP uses natural language technologies and computer vision to extract data from structured and unstructured content, especially from documents, to support automation and augmentation.”

How IDP empowers your staff

Today’s IDP solutions have several characteristics that set them apart from legacy document automation solutions that relied solely on OCR and rules engines rather than AI. These characteristics allow your team to become more productive and efficient, improving your operations and, ultimately, your bottom line.

1. Rapid Insights

The pace of business just keeps getting faster.

As the world has become more connected, expectations have shifted. Consumers are used to ordering something online and having it delivered within a day or two. And online chat means you can connect to a customer support agent day or night. That changes everyone’s assumptions about how soon companies should respond to requests.

The smartphones in our pockets mean that we’ve grown accustomed to being able to answer any question as soon as we think of it. Your business leaders expect that the information they are using is similarly up to date.

And innovation just keeps getting faster. Not too long ago, generative AI like ChatGPT seemed like the stuff of science fiction. Now it’s changing daily life, and the companies that don’t innovate will be left behind.

The biggest benefit of IDP is its ability to help businesses adapt to this fast pace. Leveraging AI, it can dramatically increase the speed of document processing while improving accuracy. PWC reports, “Even the most rudimentary AI-based extraction techniques can save businesses 30–40%.” That can be the difference between taking a week to respond to taking just days.

Consider the example of a mortgage company competing to service a new home loan. The prospective home buyer fills out pre-approval applications with several different companies. Then they wait.

Of course, the mortgage rate is important, but speed also plays a role. If the home buyer gets responses from several of your competitors 40% faster than they receive your response, they will likely choose from among those early responders. Your company won’t even have a chance to get the business.

In these situations — and others like them — humans can perform the necessary task of validating uncertain information. In essence, humans become the process for exception handling.

HITL empowers staff by allowing them to concentrate on the edge cases that the AI can’t handle on its own. Rather than wasting time on tedious data entry tasks, workers are engaged in complex decision-making tasks that require their unique experience. Some solution providers also offer HITL as a managed service, further reducing the burden on your staff.

2. Human-in-the-loop exception processing

There are some tasks that computers do far better than humans. And there are some that humans do far better than machines.

The best IDP solutions bring together the best of both worlds with human-in-the-loop (HITL).

HITL is a popular technique for improving machine learning models. In general, humans process exceptions that can be used to help refine models. For example, if you were building a machine learning model that allowed autonomous vehicles to identify stop signs, you might start with humans labeling a bunch of images of stop signs. The machine learning model would look for images similar to those that were labeled by humans and attempt to determine whether other images did or did not include a stop sign. Then humans would evaluate the computer- generated output, offering feedback on when the autonomous vehicle system got it right and when it got it wrong. That would help the system get better over time.

When it comes to IDP, human-in-the-loop is similar. Because many organisations have already trained a lot of document processing models, your team might not have to go through the early steps of labeling each document.

However, every IDP solution, no matter how sophisticated, is going to run into documents that are difficult to parse. Maybe they are handwritten documents with particularly messy handwriting. Maybe someone spilled coffee on a form before scanning it. Maybe they used an older version of a digital form that is different than the documents the system usually processes.

3. Low code

Today’s IT teams are universally over-worked and under- staffed. When your data analysts are developing or refining their IDP models, they don’t have time to wait for the developers in IT to get around to writing the code they need. They need tools that allow them to accomplish those tasks on their own.

A report titled Emerging Technologies: The Future of Low Code notes, “Digital business transformation is radically outpacing the capabilities and staffing of many traditional ‘pro code’ strategy’s capabilities to change. Both IT organisations and external service providers struggle to keep up with the agility and diversity that digital solutions demand. Low code has emerged in the last five years as one potential tool in both enabling business transformation and scaling these initiatives cost- effectively over time.”

Low-code tools rely on user-friendly interfaces to enable data scientists, analysts, and others to set up IDP models and workflows. According to one analyst firm, 41% of the employees in any organisation can be considered “business technologists.” These are the tech-savvy folks that peers turn to for advice when they have questions or problems with the software and hardware they use every day.

While these super-users may not have formal computer science or programming training, they have more than enough expertise to set up and improve the IDP models. In fact, in many cases, these people are much more familiar with the workflows involved, which can enable them to do a better job refining the models than professional developers. Low-code tools speed innovation and also help “citizen developers” learn new skills that can help them advance their careers.

Analysts predict, “By 2024, developers outside of formal IT departments will account for at least 80% of the user base for [low-code] technology/tools, up from 60% in 2021.”

Not all IDP solutions have low-code capabilities built in, but many of the best ones have these capabilities. Low-code allows organisations to use their IDP solutions for more use cases and tailor their workflows more specifically for their needs.

Customised workflows

No two organisations process documents in exactly the same way. An advanced IDP solution will allow you to use low-code tools to easily customise your models and your workflows. That makes it easy to not only set up the initial workflow, but also to refine it over time.

This capability empowers your staff to find new ways to improve your existing processes. Because your staff can make changes without having to wait for engineering to write code and update the system, you can easily test whether small changes to the model, or the workflow, brings greater efficiency. And if not, they can quickly roll those changes back.

This level of flexibility and agility empowers your team to think more creatively and find innovative ways to improve your operations. Rather than wasting time on tedious, rote tasks, your team will be actively finding ways to complete tasks faster and with fewer errors. That leads to improvements in your bottom line over time, while also keeping your human workers highly engaged in valuable work.

5. Industry standards

The best IDP solutions are more than just software — they also include valuable services from data processing experts. And when the vendor has worked with a lot of different organisations in a lot of different industries, they bring an understanding of industry standards with them, allowing you to leverage their expertise.

For example, Iron Mountain has worked with a number of government agencies to help them process documents like immigration papers and birth, death, and marriage certificates. While each country has different regulations that necessitate some customisation, this experience has helped Iron Mountain acquire a deep understanding of the best practices for governance, security, and retention for government documents. That allows them to help other organisations in the public sector get up and running with an IDP deployment very quickly.

Instead of needing to learn all this information about industry standards on their own, your staff is able to tap into the knowledge of experts. This helps them develop their own skills faster while enabling them to create models and workflows that rival those created by people with far more experience.

6. Ability to iterate and scale

When you process documents manually, your speed is limited by the number of staff members you have working on the task. And scaling up causes your costs to increase at the same rate.

Old-school document automation solves some of these problems. It allows fewer workers to process more documents and helps organisations save money through some economies of scale. But these systems generally don’t get better over time. The processing capabilities you initially purchase are the same capabilities you will have until you replace the system.

IDP not only scales very easily, it also harnesses the power of machine learning to improve over time. The more you use the solution, the faster and more accurate it will become.

And these improvements don’t cost additional money.

Deploying an IDP solution will empower your workers today. And it will empower them more and more over time as they work with the technology to help your organisation achieve its goals.