RPA and AI: What’s the difference and which is best for our Organization?

Artificial intelligence (AI) and Robotic Process Automation (RPA) are two of the most successful technologies for organizations to achieve the seemingly incompatible goals of increasing customer satisfaction and employee morale while reducing operational costs.

Let’s take a closer look at what RPA and AI have to offer, and how these complementary technologies are best deployed for business process automation.

Robotic Process Automation (RPA) is the use of software “robots” (i.e., specialized computer programs) to standardize and automate repeatable business processes. RPA robots perform the same way every time. They don’t learn from one repetition to another, and they will not improvise or come up with a better way of doing their programmed task.

Instead of making people redundant, RPA robots are more like virtual assistants who let you offload repetitive tasks that aren’t complicated but consume valuable employee time. Unlike humans, robots never get bored as they complete these tasks exactly as instructed and with the utmost efficiency.

Using RPA to augment people is a proven way to benefit the organization with:

• Accuracy: minimize human error and the costs associated with it
• Compliance: create audit trails and follow regulatory rules precisely
• Speed: complete tasks 4-5 times faster, improving efficiency
• Reliability: bots are always available and work round-the-clock, minimizing delays
• Improved Employee Morale: free up employees from repetitive tasks so they can focus on productivity – not processing.

Consider a financial institution that uses RPA to automate part of their Fraud Detection process. The process starts with a fraud alert that is analyzed by an agent, who then interacts with the customer. Once the problem is resolved, the agent wraps up the incident by filling out standard forms and sending standard emails per strict SLAs. The company deployed RPA robots to automate the wrap-up phase, which was repetitive, time-consuming, and stressful. Today, agents simply hand off the wrap-up process to a bot, and are free to help the next customer. The upshot? Reduced handling time, greater accuracy, better SLA compliance, happier employees, and more satisfied customers.

RPA is great for automating straightforward tasks. When business processes have more complex tasks or require the ability to put two and two together, Artificial Intelligence can take automation to the next level.

Artificial intelligence (AI) is the simulation of human intelligence processes by computer systems, or “machines.” These processes include learning (acquiring information and contextual rules for using the information), reasoning (using context and rules to reach conclusions) and self-correction (learning from successes and failures). AI capabilities are endless, popular applications include image recognition, machine vision, speech recognition, chatbots, natural language generation, and sentiment analysis.

While RPA is used to work in conjunction with people by automating repetitive processes (attended automation), AI is viewed as a form of technology to replace human labor and automate end-to-end (unattended automation). RPA uses structured inputs and logic, while AI uses unstructured inputs and develops its own logic. Combining both RPA and artificial intelligence can create a fully autonomous intelligent process automation.

Since organizations have both structured data (e.g., form fields) and unstructured data (e.g., free text, natural speech), many processes require both RPA and AI to fully automate a process from end to end, or to improve a robotic process once it has been deployed.

End-to-end automation is key to providing the self-service options that so many customers want. Consider how opening a new bank account online can be fully automated with the help of RPA and AI or what we call Intelligence Process Automation, resulting in satisfied customers and money-saving efficiencies for the bank.

Our customer wants to open a new bank account online. The chatbot verifies the type of account the customer wants (a business account), and provides a link to the relevant form. The filled-out form is submitted, data extraction commences and is handed off to another robot who kicks off the process to open a new account. The robot does back-end tasks such as checking the customer credit score and running a “know your customer” verification process on Google and social networks.

Next, a smart OCR robot analyzes the scanned documents the customer uploaded along with the new account form. It identifies a discrepancy in the customer name as it appears on the form and on her driver’s license. This exception is sent for human adjudication. The agent confirms that Helen Green and Helen Ann Green are indeed the same person, because their Social Security Number is identical. Based on human input, the robot's machine-learning model learns how to respond to similar situations in the future.

The robot continues to validate the uploaded documents using text analytics and natural language processing to interpret and categorize key data points from within the free text.

Once all data is in order, the robot executes the set of tasks required to set up the new business account, interfacing with the bank’s various back end systems. If the customer’s data meets bank requirements, the robot automatically sends an email to the customer with a warm welcome message, account information, and access credentials.

Finally, the robot reports back to the robotic control room, mission accomplished.

Every automation project has to start somewhere. Whether the focus is on one process or several, NICE Robotics Process Automation solutions can help you pinpoint the most optimal processes to automate, and then implement at your pace. We have found the value of automation is felt almost immediately as organizations are able to:

• Increase throughput
• Ensure compliance
• Reduce costs
• Increase employee engagement

And with success comes the impetus to automate more processes. As needs change, NICE RPA scales in tandem, putting all automated processes – attended and unattended – under one management umbrella and training the organization’s employees how to build their own robots.

As organizations look to automate more complex business processes with data from unstructured sources (like scanned documents, emails, letters, and natural speech), more cognitive capabilities are needed. That’s why the open platform of NICE RPA integrates with numerous AI technologies such as OCR, speech recognition, chatbots, and machine learning. With artificial intelligence in the mix, organizations can work not only faster, but smarter toward achieving better efficiency, cost savings, and customer satisfaction goals.

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