At the end of 2020, Forrester Research analysts predicted that more than a third of companies would look to AI in 2021 to help with workplace disruption caused by the pandemic that is, the shift to remote and hybrid work. This includes things like intelligent document processing (IDP) and customer service agent augmentation, among other functions.
In other words, now is the time for AI to shine and for organizations looking to launch new AI projects, the good news is that its not an all-at-once proposition. Smaller applications, like those mentioned above, can be the essential first steps. IDP, in particular, can be a great entry point for organizations looking to start the artificial intelligence (AI) journey.
Dipping your toes in the AI water
With some technologies, theres no real way to take baby steps; you have to go from zero to 100. But with AI and machine learning (ML) adoption, it really is a journey. You can try it out first with small, isolated projects, applying AI to one function at a time to see the results. Its very much a crawl, walk, run approach. Unlike many transactional systems like ERP or CRM, AI/ML application deployment in the enterprise world is not a sudden, life-changing event. In fact, AI/ML should be adopted in a gradual manner to achieve the greatest success.
When you think about document processing, it may seem low on the priority list one small problem in the scheme of things. But the reality is that its an important but often overlooked component of so many functions across the enterprise. And in that respect, yes, its a small piece of the bigger picture, but a key one.
And when it comes to adopting automation and AI, IDP can be a comparatively easy place to start. For a business leader who wants to start applying automation and AI within their enterprise, it represents a relatively low-risk steppingstone.
Understanding IDP
Todays enterprises generate and receive a mountain of documents, both digital and physical. These are often manually processed by humans, who enter the relevant data into application systems for storage and future retrieval purposes. This approach is time-consuming and error-prone. It relies entirely on human efforts to process documents, which can lead to long cycle times, reduced productivity, unwanted errors and increased costs.
IDP promises to make it easier to automate these workflows through document capture, optical character recognition (OCR) and natural language processing (NLP). The premise behind IDP is to digitize the entire document processing workflow across business processes by eliminating the touchpoints that requires manual intervention. Doing away with this manual intervention not only reduces costs, but it also reduces errors and ultimately helps achieve new levels of productivity.
More specifically, IDP intelligently classifies, captures and extracts all data from documents entering the workflow. It then organizes the information based on business need. Once the data has been validated and verified, the system automatically exports it to downstream business applications. In todays advanced IDP solutions, the entire process is powered by AI/ML algorithms to make business processes more resilient to disruptions and help mitigate risks.
This is unlike robotic process automation (RPA), which doesnt really use AI and is mostly rule-based and driven by templates approach. It eliminates repetitive tasks but cant provide the other benefits that IDP brings to the table.
A gateway to more business and process automation
Documents underpin so many different functions and applications, be it Accounts Payable, CRM, ERM or business process management. Being able to apply understanding and insight to integrated documents can be a huge differentiator for many other enterprise applications.
A key to the success of AI in enterprise applications is whether you believe your AI is trustworthy. Trust can be built by verification and validation. IDP provides the opportunity to easily verify and validate whether AI is doing what it is supposed to be doing. This makes it easy for enterprises to adapt AI for other key business applications once trust has been established.
All of this fits into the bigger picture of meeting the aforementioned goals cutting costs, reducing time spent on manual tasks, reducing risk of human error and increasing productivity throughout the enterprise.
The journey begins
To paraphrase Ralph Waldo Emerson, when it comes to AI/ML adoption, its a journey, not a destination. AI can be invaluable in helping resolve real business issues and recommend new products or services, for instance, but if they are improperly set up, they can quickly become expensive failures. It makes sense, then, to start with smaller applications of AI and then slowly expand.
IDP can be an important and key first step in that journey an opportunity to start with automating of document processing before expanding to other functions and implementations across the enterprise. AI-powered intelligent document processing quickly demonstrates business value and instills faith in the power of AI across stakeholder groups. They will then be more willing to expand into other AI initiatives that will benefit your organization in additional ways.
