gist
- Main difference. IPA goes beyond RPA by managing unstructured data and making data-driven decisions.
- A tremendous impact. IPA’s predictive analytics and cognitive capabilities improve customer service and efficiency.
- vital balance. Despite IPA’s capabilities, tasks that require empathy, creativity, and intuition still require human involvement.
Intelligent process automation (IPA) combines artificial intelligence, computer vision, cognitive automation, natural language processing, and machine learning with robotic process automation to enable advanced decision automation. IPA excels at customer service, document processing, unstructured data processing, and data-driven decision making. Using IPA for customer service improves the customer experience with fast response times, 24-hour availability, and virtually no human error. This provides customers with a seamless, personalized, multi-channel customer experience while freeing up human agents to focus on more complex customer-centric tasks.
A June 2023 preliminary research report on IPAs revealed that the global market for IPAs is expected to grow to US$51.35 billion by 2032. The report cites IPA’s benefits as increased process efficiency, improved customer experience, and optimized back-office operations. Enable employee productivity, cost and risk reduction, product and service innovation, and enhanced surveillance and fraud detection. This article explores IPA in detail and explores how brands can use it to improve customer experiences, tasks suitable for IPA, and processes suitable for human agents.
How is IPA different from RPA?
Robotic Process Automation (RPA) and Intelligent Process Automation (IPA) both aim to automate business processes, but in very different ways. While RPA is typically used to automate rule-based, repetitive tasks, IPA uses the help of AI and machine learning (ML) to automate more complex database tasks that require decision-making ability. can be processed. It can learn from unstructured data, adapt to change, and make predictions.
RPA works well with structured data, but poorly with unstructured data. IPA, on the other hand, uses AI capabilities such as natural language processing (NLP) and computer vision to manage both well. This makes IPA ideal for tasks such as document interpretation, sentiment analysis, and data extraction from complex or unstructured sources.
In addition, RPA lacks cognitive ability to understand or interpret the meaning behind the data it works with. Conversely, IPA is able to understand, interpret, and make decisions based on data. Understand context, extract insights, and even predict future trends based on historical data.
Cynthia Davis, founder of Cindy’s New Mexico LLC, a fast LLC formation provider, told CMSWire that while RPA helps fill out forms faster, IPA actually compares information against what’s on the form. and let us know of any mistakes or improvements. reaction. “Basically, RPA knows what to put in the bubble. IPA knows what the recipient actually wants, thanks to computer vision and cognitive automation,” Davis said. say.
Related Article: The Origins, Growth and Challenges of Robotic Process Automation (RPA)
What kind of business is IPA suitable for?
IPA is ideal for tasks involving complex decision making, learning from unstructured data, adapting to new scenarios, and improving over time. By utilizing NLP, IPA excels at tasks such as language translation and content summarization. These tasks require the interpretation and generation of human language, as well as an understanding of linguistic nuances and context. With IPA, customer service agents can determine a customer’s mood and emotions in real time, so they can provide better service to the customer.
Rather than using outdated Optical Character Recognition (OCR) technology, IPA integrates AI technologies such as computer vision, making it ideal for image recognition and analysis, processing scanned documents, reading handwriting, and more. , or is particularly useful for identifying objects in images. Additionally, IPA is great for predictive analytics. Using historical data allows you to identify trends and predict future occurrences, making it suitable for tasks such as sales forecasting, fraud detection, and customer behavior prediction.
“‘Powerful autofill’ may sound a little cliché, but think about how much time we all spend typing, reviewing, and re-entering information as part of our jobs. Let’s go,” says Davis. “IPA can basically do the work for us and turn the whole process into just approval. Mr. Davis strongly believes that IPA offers a future where information is guaranteed to be accurate, reducing wait times for responses from the customer’s perspective and streamlining processes. “Think how powerful this could be when applied to a paper-intensive sector like banking or healthcare. Customers finally get the level of service they deserve without having to pay for their personal concierge. I am now able.”
IPA can handle complex and unstructured data, allowing you to extract and interpret information from sources such as emails, social media posts, and 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 assessing the risk level of financial transactions.
Casey Jones, founder, director and head of marketing at CJ&CO, a global digital marketing firm, told CMSWire that his company is using IPA to reach out to customers via chatbots and voice assistants. He said he was responding to regular and recurring inquiries. “These inquiries may include checking the status of a campaign, requesting a quote, or scheduling a meeting. We can provide our customers with a better response,” said Jones. “This has increased customer satisfaction and loyalty and reduced operational costs and workload.”
Additionally, Jones’ business uses IPA to analyze and segment customer data using NLP and ML. “This will allow us to better understand our customers’ needs, preferences and behaviors. We can then use this information to personalize communications and offers based on each customer’s profile and history. This has also enhanced customer engagement and retention, resulting in increased conversions and revenue for our company,” said Jones.
Related article: Intelligent Process Automation Pushes the Boundaries of Business Process Automation
Examples of using IPA
IPA is now being used by more and more brands because it speeds up and automates processes while increasing accuracy, minimizes the amount of time employees spend performing routine tasks, and can process data around the clock. I’m here.
For example, American Express uses IPA to streamline data extraction and input from numerous sources such as customer service communications, emails, reports, and enterprise applications. The purpose is to update key aspects such as customer details, purchases, shipments, inventory status and shipping information. During the pandemic, American Express found its manual processes not working. Apart from the physical aspect of collecting documents, the pandemic has forced many small businesses to secure additional lines of credit. To streamline the onboarding process for commercial credit, American Express harnessed the power of AI and ML to automate the process of document analysis, allowing the underwriter to return its focus to its customers.
Spotify is another brand that uses IPA to drive efficiency and data quality, allowing employees to focus on more value-added tasks. An example use of IPA is testing ad formats within the Spotify application. Previously, employees had to manually test each ad to ensure that the audio and video met specifications for each ad, but with IPA, the process can be automated, We were able to confirm that the audio and video were appropriate for each ad.
IPA has many advantages when used in various departments within an enterprise. Jones said CJ&CO uses IPA to automate and optimize various aspects of its customer service process. “The results have been amazing. Our overall experience with IPA has been positive, but not without challenges,” said Jones. It is not a replacement for human agents. Jones said there is always a need to combine that with human expertise to create hybrid models that leverage the strengths of both.
Jim Reis, Vice President of Technology for Capital Group, one of the world’s largest investment management organizations, leads the company’s process integration and smart automation practices globally. His team uses Intelligent Automation his solutions such as Intelligent Document Processing (IDP). It combines native AI and automation to quickly and accurately extract data from business documents and highly manual processes to automate strategic customer programs and investment management areas of the company. As a result, Capital Group was able to modernize its core systems and unify processes, data and client experience. Ultimately, this freed up employees to focus on more strategic work, improved the customer onboarding lifecycle experience, and reduced costs.
Challenges of IPA
Although IPA has many advantages, there are also some challenges associated with its implementation and use, chief among them data privacy and security. IPA communicates sensitive data across various channels, platforms, and systems, potentially exposing your data to security risks. Additionally, to be truly effective, IPA must be integrated with other systems and applications, which can be technically complex, time consuming, and require significant changes to legacy systems. .
Finally, the IPA system cannot perfectly replicate the human elements of intuition, empathy, creativity, and complex decision-making based on ambiguous or incomplete information. So there are processes that are better suited to humans. “IPA proved unsuitable for handling complex customer inquiries that required human empathy and judgment,” says Jones. “These inquiries may include resolving complaints, providing feedback, or offering advice. IPA may not be able to understand the customer’s situation or feelings and provide an appropriate or satisfactory solution.” Jones said he prefers to escalate investigations to human agents who can respond with more care and skill in such cases.
Tasks requiring emotional intelligence are better handled by human agents because IPA cannot have human emotions. “For example, one specific task that we found the IPA to be unsuitable for was creating and designing online campaigns for clients. It cannot be replicated or replaced by IPA, we need a human agent who understands the client’s goals, target audience, brand identity and comes up with original and compelling ideas and concepts for the campaign.” said Jones.
Final thoughts on IPAs
IPA represents a paradigm shift in how companies operate and serve their customers. We offer potential solutions for increased efficiency, reduced costs and improved customer service. That said, IPA works best as a complementary tool that complements rather than replaces human expertise. By integrating IPA with the human element, brands can deliver superior, personalized customer experiences.
