Even if you’re not a tech geek, automated processing and robotic automation were likely to appear in your feed at some point. In this article, we will explain what these terms mean, how they apply to document processing, and what are the future trends we may see on the rise in regard to those AI technologies.
If you are a little bit of a film buff, you probably recall how sci-fi movies from the past millennium depicted the future. Flying cars, highly-advanced androids used as everyday helpers. Monumental city designs, with skyscrapers and neon-soaked streets.
Full-on cyberpunk galore, with skyline railways and dooms protecting the modern cities!
Welcome to 2022, where almost none of these wild creations turned out to be true.
Curiously enough, past generations imagined automation long before they had the Internet. And while many of their visions were not correct, modern designers visibly draw inspiration from decades ago.
Take Roomba, the cleaning robot, as an example. The idea for a house chores helper was conceived almost 100 years ago.
Today we know that most of those visions, sometimes based on books by Stanisław Lem, Jules Verne, or Aldous Huxley, were more like fairytales.
Well, almost, if you consider the fact that Verne’s novel Twenty Thousand Leagues Under the Sea influenced the development of large-scale submarines.
So, civilisation achieved a stupendous progress, but not in the direction that seemed so appealing to the imagination of the past generations.
How did we develop then?
When you think about the single most important driver of change, it is the need to save time.
Business-wise, as well as personal life-wise. A vast majority of improvements happened because people wanted to spend more time on things that matter to them. That could be family gatherings, hanging out with friends, or taking pets for long strolls in the forest. Whatever the reason, time has become the universal currency.
Here’s an example. As a person who started a professional career in public relations, I had to draw essential information from all coverage regarding the customer’s publications after a certain campaign was conducted.
So, I would spend hours scouting the Internet in search of online mentions, building excel files, going through all clippings, and assessing the tone of voice. Now I’d consider this a manual nightmare.
Today, the same job is mostly automated – there are tools that gather data concerning all media mentions across all platforms – from search engines to social media – and assess the type of message.
In practice, that means that PR specialists focus on better quality of work, rather than quantity.
Many more examples, from many more industries, could be mentioned here. From robotization being implemented in production facilities to AI assisting surgeries, we’ve seen all kinds of boosts, upgrades, and improvements that help us deliver more in a shorter time.
No steampunk cities sadly, but maybe it’s for the best?
How common is automation among businesses?
Despite its rising popularity, automation solutions remain somewhat of a tech gimmick for most companies.
According to McKinsey, only 31% of global businesses have successfully automated at least one process as of 2020.
Any process, to be precise.
That means that the vast majority struggles with manual processes, letting their employees drown in tedious work instead of unleashing their full potential. These processes vary from sales funnel optimization to marketing automation and accounting practices. Many of them also require lots of paperwork – the one aspect of work that we can all unanimously agree on is just life-draining.
If you’re as ecstatic about manual paperwork as Sheriff Woody, then Intelligent Document Processing (IDP) should really pick your interest.
Hundreds of documents – from invoices, receipts, and contracts to passports, IDs, financial analyses, etc. – are received, categorized, analyzed, and distributed every second around the world.
Judging only by the astonishing number of emails sent every day – that is 361 billion by 2024 – handling paper and online documents is, whether you care about it or not, a fundamental part of conducting business.
That’s where IDP comes in handy.
While Intelligent Document Processing doesn’t actually reduce paperwork by limiting the need to generate documents, it digitalizes them and helps immensely with processing them too. Furthermore, IDP helps turn various documents into structured sets of data, and streamline them into other integrated tools your company might be using already.
If numbers speak to you better, consider the size of the market that reflects the possibilities created by IDP tools.
Intelligent Document Processing as a market is predicted to achieve US$ 6.78 billion by 2027. The global e-invoicing market reached US$ 8.74 Billion in 2021 and is estimated by IMARC Group to be valued at US$ 29.68 billion by 2027. Note that both these markets are expected to achieve CAGR – compound annual growth rate – at over 20%.
Last but not least, the same McKinsey report concerning automation indicated that the trend of leaning toward automation is on the rise, with 66% of businesses piloting solutions to implement (as of 2020).
Hence in this article, we’ll try to take a closer look at the technologies that significantly improve document processing, in particular:
- What is Intelligent Document Processing (IDP)
- Benefits of implementing IDP software
- What is Automated Data Processing
- The upcoming trends in Documents Processing
Let’s deep-dive into a bit of the educational part of the article then. We start with the basics – the definition of Intelligent Document Processing.
What is IDP?
IDP, which stands for Intelligent Document Processing, refers to a process of transforming unstructured data extracted from documents into structured and relevant information. This process of transforming data can be called intelligent due to the technology that exists at the core of IDP – artificial intelligence, machine learning, NLP (Natural Language Processing), and computer vision. In even simpler terms, IDP helps businesses in the automation of finding, categorizing, and processing data from documents.
Here’s an example: even a small SaaS business that is only beginning to get traction, generates a certain – not too big though – amount of invoices and documents. Surely, employees of the company can process most of these documents manually. That means inserting data such as contractor name, address, amount to be paid, and so on into any software used for processing invoices.
In fact, a report from Billentis Market indicates that over 70% of global invoices processing is still conducted in a paper-based manner. Hence, if our SaaS business uses only digital invoicing, then they’re already in the more advanced minority.
Assuming that no error was made at any stage of the process, the same company will grow and therefore struggle with a rising number of business documents. More people hired, new contract amendments, more invoices from clients – more documents of all kinds to be processed.
An error-free business doesn’t exist though.
Even a single mistake in an invoice – a missing part of a delivery address – can be costly.
A delayed payment means a disruption in the cash flow, potentially an angry customer who receives a product later than expected. That’s mostly the case for production-based businesses. A SaaS business, particularly in an early stage of growth, plans the cash inflows carefully, thus the certainty of payment at particular dates is of utmost importance.
Automated document processing helps with mitigating those risks.
A well-trained, AI-based software can draw data from invoices in seconds, as well as indicate any potential errors or faulty parts. The automation can also help achieve cost reduction, and shift the team’s focus to more complex and valuable challenges business-wise. We’ll cover the benefits of Intelligent Document processing in a separate part of this article – before that, let’s clarify one more thing.
Difference between OCR and IDP
You might have also heard about OCR, which stands for Optical Character Recognition.
How does it refer to Intelligent Document Processing?
Is it the same thing?
From the technological point of view, OCR converts specific templates of images or scans of documents into machine-encoded text.
OCR systems are rule-based though, which means that the extraction happens within particular fields in a document template. Fields, defined by the user, need to be common for all documents that the OCR tool processes.
As an example, take a look at the invoice below.
When formatting of such a template changes, the OCR-based tool needs to be trained in order to extract data properly. For businesses that generate or process varying types of documents, OCR can seem too limited, since every deviation from a set of used templates needs to be separately processed by the tool.
What it also means, in reality, is that your company would need to receive and create documents within very strict formatting boundaries, and that’s seldom a case if you work with various contractors or branch out to different countries.
What IDP solutions, such as Alphamoon, can do, is take an invoice and extract data that can be streamlined into other integrated tools. Intelligent Document Processing is designed to help establish more efficient process and provide you with a better grip over the content of your documents. Like this:
IDP solves such matters by the application of Artificial Intelligence and Machine Learning. The bigger the set of documents used to train the tool, the more capable the IDP technology becomes. At the same time, IDP is template-free, which means there’s no need to define each new type of invoice or document as a separate template.
Hence, while traditional OCRs can help process a fraction of documents in the whole workflow, they can’t be applied to automate any further processes, and, therefore, generate additional value from documents.
If you’re looking for a tool to help you save time and money on document processing, get in touch with us.
What are the benefits of the implementation of Intelligent Document Processing?
The above gives you a bit of an overview of what can you expect after implementing Intelligent Document Processing in your company.
However, let’s dig deeper into the benefits of IDP implementation.
- First and foremost, IDP saves time for you and your employees.
A study by SnapLogic indicated that 90% of employees are burdened with repetitive tasks that could be automated. What’s more, that causes the losses equal to 19 working days per employee in a year.
90% of employees.
Instead of time-consuming paperwork and document classification, your Accounting or Finance Team should focus on tasks that generate more value for the whole business, while the document workflows are automated.
In other words, the same amount of employees can significantly improve their efficiency thanks to documents automation.
While we’re at it, let’s break down the popular myth that the by-product of automation translates to potential lay-offs of blue-collar workers.
The main fear concerning automation refers to the fact that automating processes removes people from the equation. When IDP decreases costs, it doesn’t necessarily refer to the reduction of people on board though. The savings can be found in a smaller amount of errors made in the document-related processes, as well as the shift in the team’s focus. The existing team’s given a better shot at wiser time management and generating crucial value thanks to the better allocation of resources. Instead of repetitive tasks, your teams can deliver leaner solutions to existing processes, as well as support other departments with more knowledge sharing.
Let’s consider an example of a company where finalizing a deal takes months – from the first negotiations to the implementation phase.
In order to process the necessary documentation, the company needs to dedicate the working hours of its employees who will analyze each page and prepare a thorough examination before the deal is concluded. With no automation set up, that task takes weeks.
However, if the analysis was automated, then the company benefits from two things:
- faster turnover of documents which maximizes the potential number of deals to be processed at a given time
- increased revenue thanks to the simple relation (ceteris paribus stands) more offers sent = more deals closed
More time and more revenue along with an automated process that saves people from frustration.
Moving on with the benefits of IDP, consider the following.
- Having the support of AI means fewer human-made errors, because the tool learns with time.
People are prone to noticing ups and downs in terms of their ability to focus. No employee’s productive at all times. A bad night’s sleep, harsh weather conditions, mood swings – you name it. The canvass of factors that have a direct impact on productivity is a large one.
Obviously, automation solutions aren’t affected by such factors.
Each AI model learns on the input from your documents, which therefore increases its accuracy. Since the main economic principle for any business owner or process owner is to maximize output by minimizing input, documents automation provides you with more structured data and support for your decision-making process in the long-term perspective. It’s easier for your employees to make the right call when they’re not tired by dull routine.
- From the investment perspective, your ROI increases after the AI teaches itself the specifics of documents your company processes. Also, your offer generation speeds up.
You no longer need to grow the team responsible for processing documents, while the existing employees can take on new challenges. Even when the company’s operation expands, automated document workflows reduce the need to hire more headcount, thus allowing you to maintain a more efficient, less costly hiring strategy too.
When assessing IDP from the business investment perspective, there’s also the benefit of faster offer generation thanks to quicker document turnaround. With automation in place, your team can quickly process emails from prospects and source data to create ready-to-send offers.
- Another key benefit: simplified internal document communication.
The above may sound like a headache for the biggest fish in the pond. However, even mid-market businesses employ various ERP and CRM systems that generate documents. IDP does the heavy lifting of transforming data from a plethora of various documents and streamlining that data into a common format.
- Increasing customer satisfaction.
While we’ve been focusing mostly on invoices so far, there are other types of documents that can largely improve other processes, i.e. complaints processing. By establishing certain templates for your complaints, IDP can help quickly extract key data from complaint forms and boost the performance of your Customer Success team.
And hey, quicker responses and better quality of service will likely end with higher eNPS.
What is Automated Data Processing?
While intelligent document processing aims at extracting data from documents, AI-based technologies can also automatically process this extracted data, thus supporting many key processes where accurate data plays a pivotal role.
Automated data processing encapsulates all technologies that utilize machine learning and artificial intelligence to extract, store, process, analyze and streamline data.
Take an SEO marketer as an example.
In order to know whether content works well, an SEO specialist needs to process lots of data – from organic traffic to average keywords position, search potential measured by impressions, and many more metrics combined. The goal of automated data processing is to organize available data in such a way that the SEO marketer knows what’s the distribution of impressions among search queries or which average positions potentially decrease the overall traffic.
Automated Data processing can happen in several ways, depending on the specific use case or business need – from batch processing to real-time processing, automation of data management is another big trend in the near future.
IDP and ADP are tightly linked together. By implementing both of these automations, your company benefits from documents on the highest possible level. Your data extraction achieves top-quality accuracy, can be transferred to other integrated tools, and then processed and put together as reports that support your decisions.
Now that we have sorted out the essential terms that give you a better grip over AI-based technologies in document processing, let’s see what – according to experts designing such a tool – is in store for the future.
The 5 upcoming trends of AI in Documents Processing predicted by Alphamoon experts
1. Growth of more advanced AI engines supporting document processing
Intelligent Document Processing remains ahead of its full-fledged form. While already advanced and beneficial, IDP is still in its rapid growth stage. The market’s hungry for top-notch algorithms that use machine learning, computer vision, and NLP (natural language processing), all techniques guaranteeing a better fit for the markets. A few key aspects to be mentioned here:
- Since IDP’s fuelled by Artificial Intelligence, new models will advance in terms of more complicated examples of documents – handwritten notes for example – or larger files where data extraction will need to be supported by a better understanding of the text context too.
- Lots of improvements will also happen in the area of non-written content – graphs, images, signatures, QR codes, etc. Many documents cannot be fully processed by conventional OCR when they include more complex visual content, such as nested tables, graphs, etc. – IDP is going to solve that problem too.
- Intelligent automation will also deploy various techniques to detect the high-risk, prone-to-error cases and pass them to be verified by humans. Those methods will include novelty and out-of-distribution detection, AI model calibration, and uncertainty estimation. That way, IDP tools will become more trustworthy.
- IDP developers will deploy multimodal deep learning models for recognizing document types and extracting relevant information. Multimodal means that they utilize different types of information – also called modalities – which are textual, positional, and visual contexts. In other words, that’s the reflection of the perception of humans, who look at both the textual and visual aspects to fully understand documents.
2. Implementation of SaaS features for the maximized ease of use
Despite the complexity of IDP, companies will likely follow the steps of most SaaS tools in terms of self-service and quick implementation. If we wind the clocks back a few years, Intelligent Document Processing technology was mostly offered to enterprises where the document processing was the most complex.
However, you don’t need to employ thousands of employees to experience a bottleneck in your paperwork speed.
Democratizing the access to IDP also requires a systematic shift from on-premises implementation to SaaS services with self-onboarding. Moreover, we’re used to adding extensions and integrations to existing tools, and rightfully so, many business owners refuse to wade through complicated implementations. After all, introducing new tools usually happens in order to achieve a certain improvement. Hence there are several benefits stemming from that change:
- SaaS deployments are easier to maintain and keep up to date. Any major update can be deployed for all clients instead of single deployments that are more time-consuming.
- Seamless scalability and easier dealing with demand peaks. Deployment of any tool should be easy – as easy as a few clicks. Along with your company’s scale, each integrated tool needs to be easily adaptable too.
- Existence and leveraging of the highest standards of security for data governance, protection, and privacy. One question that we often receive from prospects at Alphamoon is how secure is the data stored in the system. After all, our customers upload their financial documents, contracts, and many other types of docs. To achieve necessary trust, many major cloud providers employ the latest security standards for in-transit and at-rest data protection, data segmentation, and other security best practices, constantly monitoring for potential new threats.
- Supporting business continuity plans with various cloud regions and geographies. Geo-redundancy is a great way to achieve a high level of protection against unexpected and potentially damaging events that can happen to the physical servers. It can also help with business continuity plans especially when access to infrastructure becomes limited a situation that we’ve experienced during COVID pandemic.
- Faster onboarding for a wider audience like mid-sized companies. The undeniable benefit stemming from private cloud deployment is the easy extension of potential use cases. Instead of designing a very complex tool for one specific need, the platform-based solutions are quick to master and further adapt.
Easier and global access for users. Another widely popular trend nowadays is making access to the product as easy as possible. Social sign-ups among SaaS businesses, guest purchases in e-commerce, supporting web apps with mobile apps.
- Cost-effectiveness for clients without the need of maintaining internal infrastructure and a supporting team. The best tools are easy to master so that you immediately begin to notice their positive impact. You don’t want to hire a new position just to introduce and maintain a tool that’s supposed to simplify things.
3. New use cases emerging thanks to the growing capabilities of IDP tools
Do you recall the fact that most IDP technologies get better as they learn? Like humans, AI needs a bit of time to master a process. But learning one capability often means that with a bit of work and the right set of documents to learn on, a new one can emerge soon enough.
Therefore, the growing trend in AI technologies within document processing will be the increase of ready-to-use workflows, i.e. skip tracing that’s been successfully implemented in KRUK S.A., a leading debt collection company in Poland.
Let’s not halt your imagination there, because IDP will soon be powerful enough to deal with more complex and harder-to-read documents and files.
ML experts from Alphamoon expect that in the near future, IDP will be growing to cover more out-of-the-box use cases, with more structured complexity. While the tools are already used to transform documents such as invoices into sources of data, IDP will be used to provide an end-to-end perspective, potentially extracting data from several types of documents and combining it within one closed process.
We should also see IDP used in e-mail processing (remember those billions of emails sent every day worldwide), official letters, medical documentation, and so on.
Adam Gonczarek from Alphamoon adds:
“New use cases will not only empower IDP to help more companies with very specific parts of the processes to tackle but optimize them end-to-end. The goal for such products will be to automate each step of the document lifecycle, from acquiring through data extraction, understanding content, and finally decision making or response generation. Once that happens, companies will have it much easier to send, receive and process documents between various parties without the need to integrate new tools. Intelligent Document Processing should be able to adjust the extracted data from any form of document and make it useful for further, streamlined processes.”
4. Shift to no-code and low-code solutions
When Wix made it happen – by it I mean creating a website with zero dev skills – the life of an early start-up founder became much simpler. Instead of paying thousands for a brand new website for an idea that might perish after a week, there’s a tool that lets anyone create a website in a matter of a day.
Why should it be different for other products then?
Implementing technologies of document automation will be systematically shifting to low-code/no-code solutions.
What does it entail from the user’s perspective?
Well, creating document workflows will be an easy-peasy job – even for someone who never fiddled with coding at all. Training AI models for data classification and extraction will not require a separate team of IT experts either, hence business users will have control over how the tool supports their needs. That’s how Alphamoon experts indicate the democratization of documents automation in general – access to technology for business users without the necessary tech-savvy background.
That’ll create new opportunities for companies that implement IDP at an early stage too. Process owners will easily add new workflows (document processes) to meet the new needs associated with the changes in the organization. Combine this with cloud-based deployment, and then any business will benefit from the full flexibility of IDP.
Finally, this trend also opens the gates of Intelligent Automation for smaller companies that wouldn’t otherwise afford such expensive implementations.
5. The world beyond IDP
All of the above leads to the full transformation of IDP into a platform for fully autonomous document workflows with intelligent document processing, knowledge extraction, decision making, and response/outcome generation. What started with reading documents and simplifying one fraction of the process as traditional OCR needs to grow into a complex business growth support tool.
Norbert Raus, CPO of Alphamoon adds:
“In addition to automation, IDP will lean towards building structured knowledge bases from groups of various documents. Users often need to find relevant information quickly and we see that across many use cases we’re working with today. Such structured knowledge bases can enable users to get the answers, even to the most complex queries, thanks to AI-based search engines within these sets.”
Intelligent Document Processing in a nutshell: a quick recap
Let’s recap the whole topic of Intelligent Document Processing and the trends that will shape the technology’s future.
- IDP, which stands for Intelligent Document Processing, refers to a process of transforming unstructured data extracted from documents into structured and relevant information. This process incorporates machine learning, NLP (Natural Language Processing), and computer vision.
- Contrary to traditional OCR tools, which simply “read” text from documents, IDP empowers companies to optimize their existing workflows, and gain knowledge from document workflows.
- The next step in the automation chain after IDP is ADP, which stands for Automated Data Processing – a term encapsulating all technologies aimed at processing structured data.
- According to Alphamoon experts, the first big trend in document automation is the growth of more advanced AI engines supporting document processing.
- Alphamoon experts also predict that IDP platforms will lean towards SaaS models, with self-onboarding and maximized accessibility.
- Along with the new capabilities and growing competencies of IDP platforms, machine learning experts see that the trend will be to adapt to new business needs faster. At the same time, these business needs will be more complex, encapsulating an entire end-to-end capability of IDP solutions.
- As it happened in other industries – web development for example – document automation will also lean heavily towards low-code/no-code solutions. Business users with no tech background will benefit from easy access to IDP. That also means that smaller companies should soon be given a shot at more affordable automation solutions.
- IDP is likely to grow beyond OCR and data extraction, joining forces with ADP and providing businesses with full-scale decision-making support.
Document Automation with Alphamoon
Well, that’s about that. After that long read, you (hopefully) feel encouraged to learn more about the implementation of IDP.
Alphamoon works with dozens of clients with very specific needs, and we’re eager to tackle new challenges and implement the state-of-art AI our developers designed in your company too. Click below and tell us about your needs.