The pace of change in the digital workplace shows no signs of slowing down. One of the next waves to look out for is the rise of intelligent process automation, or IPA. In a nutshell, IPA brings together robotic process automation (RPA) and artificial intelligence (AI) technologies to take automation of business processes to the next level.
How, exactly, does IPA differ from RPA? RPA is the use of computer software ‘robots’ to handle repetitive, rule-based digital tasks, with the robots interacting with applications and information sources in much the same way as human workers do. These robots are quick, reliable and excel at doing the same repetitive tasks over and over again. But they do not continuously ‘learn’ and improve.
On its own, RPA is highly efficient at automating processes that are driven by structured data. However, many business processes are fed by or generate large amounts of unstructured data such as scanned documents, emails and letters. That's where more advanced cognitive solutions come into play – IPA makes it possible to automate these processes, too.
And by adding cognitive intelligence to the mix, IPA enables robots to learn from performing their tasks so that they can work faster, better and more accurately over time. Where basic RPA is not intelligent and cannot easily manage nuances and exceptions, IPA is smarter and more flexible. It augments and builds on the already valuable capabilities of RPA.
The technologies in Intelligent Process Automation
IPA is the product of the convergence of AI and related technologies – including computer vision, cognitive automation and machine learning – with RPA. Bringing these technologies together catalyzes richer automation possibilities, unlocking even more business value for enterprises. Some of the core technologies in IPA include:
- Unattended robots, or server-based bots that fully automate processes that do not require human judgement or intervention.
- Machine learning algorithms that find patterns in structured data through “supervised” and “unsupervised” learning.
- Smart workflow tools that help to manage, integrate and hand off processes spanning people and machines.
- Cognitive agents, virtual agents that combine machine learning and natural-language generation to carry out tasks, learn from data sets, and communicate with human users.
- Computer vision tools such as Optical Character Recognition, the technology used to convert a scanned document or photo into text.
- Natural language processing (NLP) tools, which enable a computer to understand, interpret and manipulate spoken or written language. This technology is key in chatbots and virtual assistants.
The benefits of Intelligent Process Automation
IPA has the potential to be a truly transformational technology, offering possibilities that go beyond elevated efficiency to include step change improvements in customer experience, productivity and efficiency. The good news is that as enterprises embark on the IPA journey, they will be able to unlock return on investment as they build out individual components of their IPA program.
Over the longer term, IPA will benefit an organization by enabling it to automate more complex tasks and perform more adaptable workflows. Such tasks include those that RPA cannot handle – because they involve many exceptions or draw on unstructured data – yet which are cumbersome, boring or time consuming when done by human employees.
Consider the example of a large bank using a mixture of RPA and AI technology to automate the complex process of opening a bank account. The customer could initiate the process via a chatbot, which presents them with an online application form. Once completed, the form is submitted to unattended robots for automated background checks and identity verification (using computer vision to extract data from a passport, for example).
If the machine cannot validate the applicant’s identity – for example, someone calls themselves Steve on the form when their passport says Stephen – the exception can be referred to a human operator. The machine learning algorithms will watch how the human handles the exception and learn how to handle it better in future. From there, the RPA tools may interact with NLP tools to execute the remaining tasks required to open and activate the account.
As this example shows, the benefits of a basic IPA use case are numerous. Firstly, human operators can focus on human relationships rather than process work. Secondly, automation of complex processes at scale will deliver significant cost savings and productivity gains. And perhaps most importantly of all, customer satisfaction should soar because much of the friction will disappear from processes such as querying a bill or opening an account.
How does NICE’s RPA platform support Intelligent Process Automation?
NICE is a pioneer in cognitive automation. Our open RPA platform is designed to accommodate intelligent technologies as they emerge, enabling our customers to automate increasingly complex processes and to continuously improve efficiency and productivity. Our platform integrates with leading AI technologies, such as Optical Character Recognition (OCR), chatbots and machine learning.
Our process automation robots can learn, understand and execute processes based on unstructured data – scanned documents, chats, text messages and more – while improving themselves over time. These robots can talk to other bots in your organization, from virtual agents to chat and voice bots, providing end-to-end service by performing back-end actions in real time.
As such, our platform enables organizations to automate business processes that depend heavily on unstructured data and to more easily automate processes that are less rule-bound than those at which traditional RPA excels.
Organizations can start with simple, repetitive tasks on our platform and rapidly scale their efforts as their RPA maturity grows. Part of successfully scaling process automations is to continuously identify new opportunities for automation within the organization. NICE’s Automation Finder innovation has built-in AI and is designed to rapidly identify and recommend which processes should be automated to maximize ROI. All of these cognitive capabilities are easily accessed from a single automation platform.
