Feature
The Gist
- Key distinctions. IPA surpasses RPA by managing unstructured data and making data-based decisions.
- Tremendous impact. IPA's predictive analysis and cognitive abilities enhance customer service and efficiency.
- Vital balance. Despite IPA's capabilities, tasks requiring empathy, creativity and intuition still need human involvement.
Intelligent process automation (IPA) blends artificial intelligence, computer vision, cognitive automation, natural language processing and machine learning with robotic process automation to enable advanced decision-making automation. IPA excels in customer service, document processing, handling unstructured data and data-driven decision-making. When used for customer service, IPA enhances the customer experience with quick response times, round-the-clock availability and virtually no human errors. It provides customers with a seamless, personalized multichannel customer experience, while also freeing up human agents to focus on more complex, customer-centric tasks.
A June 2023 Precedence Research report on IPA revealed that the global market for IPA is expected to grow to $51.35 billion US dollars by 2032. The report cited the benefits of IPA to include increasing process efficiency, improving the customer experience, optimizing back-office operations and workforce productivity, reducing costs and risks, enhancing product and service innovation as well as monitoring and fraud detection. This article will delve into IPA, exploring the ways that brands are using it to improve the customer experience, tasks it is suitable for, and processes that are better suited for human agents.
How Is IPA Different From RPA?
While robotic process automation (RPA) and intelligent process automation (IPA) both aim to automate business processes, they do so in significantly different ways. RPA is typically used for automating rule-based, repetitive tasks, whereas IPA, with the help of AI and machine learning (ML), can handle more complex data-based tasks that require decision-making abilities. It is able to learn from unstructured data, adapt to changes and make predictions.
Although RPA works well with structured data, it falters with unstructured data. IPA, on the other hand, adeptly manages both by using AI features such as natural language processing (NLP) and computer vision. This makes IPA ideal for tasks like document interpretation, sentiment analysis or data extraction from complex or unstructured sources.
Additionally, RPA lacks cognitive abilities, and can't understand or interpret the meaning behind the data it works with. Conversely, IPA can understand, interpret, and make decisions based on data. It is able to comprehend the context, extract insights, and even predict future trends based on historical data.
Cynthia Davies, founder of Cindy's New Mexico LLC, a fast LLC formations provider, told CMSWire that while RPA can help you fill out forms more quickly, IPA can actually check your information against what's on the forms to let you know of any mistakes or improved responses. "Essentially, RPA knows what to put in the bubbles — IPA knows what the recipient actually wants, thanks to computer vision and cognitive automation," said Davies.
Related Article: The Origins, Growth and Challenges of Robotic Process Automation (RPA)
What Kind of Tasks Is IPA Suitable For?
IPA is most suitable for tasks that involve complex decision-making, learning from unstructured data, adapting to new scenarios and improving over time. By using NLP, IPA excels at tasks including language translation and content summarization. These tasks require the interpretation and generation of human language, as well as an understanding of language nuances and context. By using IPA, customer service agents are able to determine the mood and sentiment of customers in real-time, which helps them to better serve the customer.
Rather than using archaic optical character recognition (OCR) technology, the integration of AI technology such as computer vision into IPA makes it well-suited for image recognition and analysis, which is especially useful for processing scanned documents, reading handwriting or identifying objects within images. Additionally, IPA is also adept at predictive analysis. Through the use of historical data, it can spot trends and forecast future occurrences, making it suitable for tasks such as sales forecasting, fraud detection and customer behavior prediction.
“'Autofill on steroids' may sound a bit mundane, but consider just how much time we all spend inputting, checking, and re-inputting information as part of our jobs,” said Davies. “IPA can essentially do the work for us and turn entire processes into mere approvals. Right now we need to weed through this kind of information looking for errors and fact-checking.” Davies firmly believes that IPA offers a future where information is assured correctly, reducing wait times for responses from the customer's perspective and streamlining processes. “Think of how powerful this can be when applied to the paperwork-heavy realms of banking and healthcare. Customers can finally get the level of service they deserve without having to pay for a personal concierge.”
Because it is able to work with complex or unstructured data, IPA can extract and interpret information from sources such as emails, social media posts or web pages. It is also useful for cognitive decision-making tasks that rely on data analysis, such as recommending actions based on customer behavior or evaluating risk levels in financial transactions.
Casey Jones, founder, director and head of marketing at CJ&CO, a global digital marketing company, told CMSWire that his company uses IPA to handle routine and repetitive inquiries from its customers via chatbots and voice assistants. “These inquiries include checking the status of a campaign, requesting a quote, or scheduling a meeting. IPA allows us to provide quick and accurate responses to our customers 24/7, without the need for human intervention,” said Jones. “This has improved customer satisfaction and loyalty, as well as reduced our operational costs and workload.”
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Additionally, Jones’ business uses IPA to analyze and segment its customer data using NLP and ML. “This helps us understand our customers’ needs, preferences and behavior better. We can then use this information to personalize our communication and offers to each customer, based on their profile and history. This also enhanced customer engagement and retention, which in turn increased our conversion and revenue,” said Jones.
Related Article: Intelligent Process Automation Pushes the Boundaries of Business Process Automation
Examples of IPA in Use
IPA is being used by more and more brands today due to its ability to speed up and automate processes while increasing accuracy, minimizing the amount of time employees spend accomplishing mundane tasks and being able to process data 24 hours a day.
American Express, for instance, uses IPA to streamline data extraction and entry from a multitude of sources including customer service communications, emails, reports and enterprise applications. The aim is to update critical aspects such as customer details, purchases, shipments, inventory status and delivery information. During the pandemic, American Express came to discover that manual processes were not working out. Aside from the physical aspects of gathering documents, the pandemic forced many smaller businesses to secure additional lines of credit. In order to streamline the commercial credit onboarding process, American Express used the power of AI and ML to automate the process of document analysis, which allowed the underwriter to return their focus to the customer.
Spotify is another brand that is using IPA to drive efficiency and greater data quality, enabling its employees to focus on more value-added tasks. One example of its use of IPA is the testing of ad formats within the Spotify application. Previously employees had to manually test each ad to ensure that the audio and visuals are up to spec for each ad, but they were able to automate the process using IPA, which ensures that the audio and visuals are appropriate for each ad.
IPA has many advantages when used across various departments in a business. Jones said that CJ&CO has used IPA to automate and optimize various aspects of its customer service process. "The results have been astounding. Our experience with IPA has been positive overall, but not without challenges,” said Jones. “We believe that IPA is a powerful tool for customer service that can create value for both customers and businesses, but it is not a replacement for human agents.” Jones said that there will always be a need to combine it with human expertise, creating a hybrid model that leverages the strengths of both.
Jim Reis, VP of technology for Capital Group, one of the world's largest investment management organizations, leads the company's Process Integration & Smart Automation practice globally. His team uses intelligent automation solutions such as intelligent document processing (IDP), which combines native AI and automation to quickly and accurately extract data from business documents to automate the company's strategic customer programs and investment operations areas with highly manual processes. As a result, Capital Group has been able to modernize its core systems to unify processes, data and client experiences. Ultimately, this enabled employees to focus on more strategic work, improving customer onboarding lifecycle experiences and diminishing costs.
The Challenges of IPA
IPA has many advantages, but there are also several challenges associated with its implementation and usage, chief among them being data privacy and security. Because IPA interacts with sensitive data across various channels, platforms and systems, it can potentially expose data to security risks. Additionally, for IPA to be truly effective, it must be integrated with other systems and applications, which can be technically complex and time-consuming and may require significant changes to legacy systems.
Finally, IPA systems cannot fully replicate the human elements of intuition, empathy, creativity and complex decision-making based on ambiguous or incomplete information. As such, there are processes that are better suited for humans. “We found that IPA is not suitable for handling complex inquiries from our customers that require human empathy and judgment,” said Jones. “These inquiries include resolving complaints, providing feedback, or offering advice. IPA may not be able to understand the context or emotions of the customer, or provide appropriate or satisfactory solutions.” Jones said that in such cases, they prefer to escalate the inquiry to a human agent who can handle it with more care and skill.
Because IPA is not capable of having human emotions, tasks that require emotional intelligence are better off being handled by a human agent. “For example, one specific task that we found IPA to be unsuitable for is creating and designing online campaigns for our clients. This task requires human creativity, intuition, and flair, which IPA cannot replicate or replace. We need human agents to understand the client’s goals, target audience, and brand identity, and to come up with original and engaging ideas and concepts for the campaign,” said Jones.
Final Thoughts on IPA
IPA represents a paradigm shift in how businesses operate and serve their customers. It offers potential solutions for increasing efficiency, reducing costs and improving customer service. That said, IPA works best as a complementary tool, supplementing human expertise rather than replacing it. By integrating IPA and human elements, brands can deliver an exceptional, personalized customer experience.
