Blog Post

Intelligent Process Automation

Blog Post

Will Roberts Profile

Will Roberts

Senior PMM

What Is Intelligent Process Automation?

Intelligent Process Automation is the next evolution for automation technology, where robotic process automation (RPA), natural language processing (NLP), and artificial intelligence (AI) intersect and become something better.

If robotic process automation alone is taking rote tasks and using software to handle repetitive tasks, intelligent automation gives automation flows their own metadata and design.

It can be helpful to think of IPA as an executive function that improves the workings of all your digital process automation. That means that it can become flexible and more responsive to your human-powered workplace and customer base.

Basic tasks also are pre-built and easily reusable between flows so that each automation solution isn’t designed or built from scratch. For example, intelligent automation depends on capabilities like pre-trained machine learning models which can be disposed of without further development and model training.

At its best, IPA allows companies to design their automated processes to make decisions and “learn” from experience; change with input from past automation results.

Which Technologies Are Involved in IPA?

IPA applies artificial intelligence, conversational AI, natural language processing, and a host of other “intelligent” tools to your existing automation to augment your entire process. These technologies are already being used in digital processes to improve sectors like insurance, banking, and healthcare.

What Are the Benefits of IPA?

For some time now, businesses have automated processes like payroll, invoicing, and data entry. Simple automation can save businesses hours of human labor and can also save them from inevitable human error. However, traditional automation also comes with severe limitations. Simple automation cannot easily handle workflow changes and isn’t flexible enough to respond to unexpected inputs. As a result, the automation breaks down whenever the underlying application changes or a customer interacts with it in some non-predetermined fashion. Traditional automation has also likely depended on programming languages that require expertise in a technical field.

What are some simple examples of brittle automation? Consider the automation flow that takes a document placed in a shared folder every week by staff, prepends it with the date, and then copies it to an SFTP site for the next person to review and process. That solution could be as light as a combination of bash scripting and Python to lighten the load for service staff, but is a lift for an IT team to build and maintain. Each time a person diverges from this straightforward process, IT and service teams would have to scramble to resolve the issue and add technical debt to their queue.

If your business relies on older automation designs, you've probably already experienced the unavoidable downtimes resulting from your IT team scrambling to rewrite and redesign “bots” so that your system can get up and running again.

Intelligence process automation doesn’t suffer the same limitations and consequences of brittle design.

IPA tools bring automation with a brain, and allow automation flows to learn from past mistakes, handle unstructured data, and collaborate with a human operator to keep customer experiences up and responsive. IPA can also take in new information and change course as needed, so that your automation keeps running even when circumstances change.

What Is the Difference Between IPA and RPA?

There are a number of important divergences between IPA and RPA. Inevitably, they get lumped together, which is why it’s worthwhile to tease out the differences and values.

Robotic Process Automation

RPA stands for robotic process automation. It’s an umbrella term that refers to the category of software solutions used to build and deploy robots that carry out digital back-office tasks.

Robots can make keystrokes and navigate online systems. They excel at predictable, repetitive tasks with a clear sequence of steps, which is why they are widely used in areas like data entry, invoicing, and payroll. Simple robots can be programmed to track employee hours and issue paychecks; they can also be programmed to calculate overtime pay and deductions.

Robots perform these menial tasks more quickly than most employees, and they do so without the volume of errors human intervention typically incurs. Automating menial processes can save businesses the cost of labor, while eliminating the cost of repairing errors in operations. Automation also frees up employees to focus their energy on more complex tasks. For these reasons, RPA technology is largely focused on improving operational efficiency within the enterprise, impacting the employee experience but less so the customer experience.

Intelligent Process Automation

IPA takes process automation to the next level for various industries. IPA platforms apply artificial intelligence tools to manual business processes. Of course, each solution can look quite different depending on the use case; there is a broad array of tools that key components of IPA can bring to bear. Computer vision and natural language processing are just a few of the more common tools used by IPA to create a more flexible, and interactive automation journey.

Computer Vision

Computer vision allows computer programs to “read” and “understand” complex visual inputs, so that they can collect data from video and still photos even when that information is not clearly labeled. Inputs such as photos of damaged property, personal identification, and scans of standard forms are good examples. Computer vision can be used for insurance inspection and claims settlement, among other things.

Natural Language Processing

Similarly, natural language processing tools, or NLP, allow computers to communicate in human languages; written or spoken. NLP-enabled programs can read and respond to texts that are written the way people really speak. Chatbots are powered by NLP; so are search engines.

Machine Learning

IPA can also apply machine learning tools to the automated processes themselves. Machine learning, or ML, allows the software to identify patterns in large data sets and is the product of many data scientists expertise. Eventually, ML-enabled programs can make predictions based on those patterns. This allows them to course-correct and to keep improving their own functioning by, essentially, learning from experience.

While Robotics Process Automation improves operational efficiency for employees, Intelligent Process Automation leverages Artificial Intelligence to self-service more sophisticated customer intents. To make an impact on your customer experience, you'll need an Intelligent Process Automation solution that understands the problems and jargon unique to your industry and those that it serves.

IPA and RPA: A Difference in Focus

RPA and IPA have fundamentally different focuses: RPA is focused on a process, while IPA is profoundly data-focused. You don't need to have RPA tools in order to implement IPA. But if you are already using RPA, then Intelligent Process Automation platforms can complement your existing end business processes.

For example, RPA excels at capturing and storing data. IPA can take this process a few steps further by applying NLP and mining written texts for data to drive scale. IPA can use NLP to “read” emails from business partners and customers and extract all the relevant data so that it can be stored and later studied; thereby injecting intelligence into an automated process.

What kind of data are we talking about? It could be anything from sales data and transactional data to contractual information. When you use intelligent automations in your workflows, human employees no longer have to sift through an endless email inbox looking for actionable information.

Intelligent Process Automation Use Cases

IPA can be used for digital transformations in virtually any field and certainly different industries. Here’s how a few key sectors are already using this technology.

Insurance Industry

Insurance enterprises rely heavily on communication with customers who reach out to their service centers regularly, and all with a unique language and tone. The high volume of communication and varied intent can be a problem for brittle automation flows dependent on human actions. That’s why any tool that is flexible and intelligent enough to improve communication on a high level is a game-changer for people in the field.

Claims Processing Across Industries

Ushur’s insurance claims process automation slashes the time needed to process claims regardless of whatever data format they originate in. An insurance enterprise can use Ushur’s intelligent process automation so customers can submit claim details over any channel and receive proactive status updates as they arise and are generated by backend systems. And, with fewer delays and less friction in each engagement, customers report a far greater level of engagement and satisfactory outcomes.

Banking and Financial Services Industry

The banking and financial services sector is rapidly growing its online presence, and customers expect to carry out a broad range of activities via their devices. The sector also still sees inordinate operational costs in their customer service centers despite heavy investments in other existing automation technology which leaves gaps in their overall customer experience. Intelligent automation is changing what’s possible with customer experience in banking.

Ushur is using IPA and conversational AI to facilitate smooth conversations with both existing customers and prospective customers. Conversational AI means that chatbots can understand customer queries and interact directly with backend systems to resolve their issue. 

At the same time, Ushur’s solution allows early adopters to capture data from conversations with clients, and learn steadily more from each experience. As a result, every customer interaction becomes a growth opportunity, in which the chatbot learns how to improve its services. The more data the bank can capture, the better it can serve its customers via use of analytics.


Effective communication is a vital part of the healthcare sector, and IPA solutions make it easier for healthcare facilities to listen to patients and learn from their concerns while safely and responsibly collecting and storing data in a format humans understand.

But Ushur doesn't stop at simply collecting information. The system builds on the intent captured through Conversational AI by automating routine tasks across backend and legacy systems. The result is smoother workflows and greater customer satisfaction through the use of complementary technology and use of AI.

Conversational Intelligence

Ushur is working closely with clients in the insurance industry to implement IPA solutions so that customers can be better served at all times. Ushur’s Language Intelligence Services Architecture (LISA) is a framework for services that serve Natural Language Processing, Natural Language Understanding, Sentiment Analysis, Topic Detection, and Metadata Mapping to understand and respond intelligently to customer conversations.

LISA can understand human speech and respond in kind. The system can handle a variety of customer queries and perform triage, passing customers along to a human agent whenever necessary. Using LISA means that customers get their issues resolved quickly, while agents are freed up to focus on the customer relationship and make important decisions.

Getting Started with Intelligent Process Automation

IPA has a very broad range of applications, extending well beyond what we’ve outlined in this post. At Ushur, we believe that every business -- in every field -- can transform their customer experience through automated business processes that eliminate the friction and risk from every customer engagement.

Curious about what IPA and associated new technologies can do for your business? Get in touch today and start a conversation about how Ushur can help you maximize your company’s potential.

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