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Intelligent Automation Examples: 5 Ways to Grow Enterprise Efficiency

Elizabeth Bell, Appian
April 9, 2024

Intelligent automation is a term for the combination of process automation and artificial intelligence (AI). And it’s creating efficiency gains for enterprises across industries. In this article, discover intelligent automation examples that will illuminate common use cases that enterprises should consider adopting to improve efficiency and make space for innovation.

Customer onboarding.

Intelligent automation technology allows organizations to move away from manual customer onboarding processes, making onboarding more seamless for everyone involved. For example, if customers need to submit forms as part of onboarding, organizations can classify and extract form data using AI-powered content processing. And AI-enhanced data fabric technology allows enterprises to connect disparate solutions so that data is easily accessible wherever it’s needed throughout the customer onboarding process. No more sorting through piles of onboarding paperwork and entering data into systems every time you have a new hire.

Example #1: Labor union uses intelligent process automation to improve contractor onboarding.

A national labor union needed to verify data for multiple contractors as part of an onboarding process. They used AI document processing technology to classify incoming documents from contractors and extract data from those documents. Then, they used robotic process automation (RPA) to pull contractor onboarding information from their application, plug it into a government website research tool for verification, and route the confirmation back to the application. Finally, they stored onboarding information in an analytics solution to give decision makers easier access to critical data. The project was wildly successful at eliminating mundane tasks for the workforce and improving data integrity overall by reducing data entry errors.

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Invoice processing.

Invoice management can be tedious and complex. But more importantly, if payments aren’t processed effectively, it can cause process snafus with serious consequences. Intelligent automation can reduce manual work in invoice processing, improve accuracy, connect data, and consolidate processes into one unified front door for employees.

Example #2: NBN processes invoices 97% faster.

NBN is responsible for providing broadband to all of Australia. They do so through retail service providers. They used to rely on legacy technology to pay service providers, but delays in paying them made this increasingly unworkable over time. NBN created an application on an AI process automation platform that uses business rules to validate invoices and calculate statements. Audits and approvals are easy now and allow NBN to pay service providers in a timely, accurate manner with less incidence of human error and  manual work. NBN’s new application was able to reduce invoice processing time by 97%. 

Inventory management.

To build more resilient supply chains, organizations need to use intelligent automation across their processes from end to end. Supply chain automation proves critical for businesses to operate at scale. For example, intelligent automation enables organizations to:

  • Automate complex tasks in manufacturing production to produce faster with consistent quality.

  • Speed up the delivery process so manufacturers can compete.

  • Improve agility via automated alerts to monitor demand signals.

  • Automate notifications when suppliers may run behind schedule or lack capacity.

Example #3: Leroy Merlin achieves 90% customer delight around refund processing.

Leroy Merlin, the third largest home improvement retailer in the world, saw a surge in both eCommerce and physical store orders, which resulted in a rise in refund and return requests. The shifting dynamics of the market further escalated these refunds, returns, and exchanges, presenting a considerable challenge for the business. 

They used intelligent process automation to address these challenges and increase efficiencies. For example, they completely automated refund payment transactions with the help of intelligent automation and robotic process automation. Initially, their finance team had to manually comb through multiple payment portals to identify if there were any transactions that had not been captured or acted on. Now RPA does that background work, streamlining the process and eradicating errors in financial transactions. 

They also integrated AI-powered document processing to accelerate refunds. Here’s how it works: The system now extracts the necessary information required for initiating refunds and fills in the relevant details automatically, speeding up the entire refund process. This, in turn, has boosted customer satisfaction. 

Ultimately, Leroy Merlin increased refund processing efficiency by 55% and achieved 90% customer delight around the returns process. 

Change-risk management.

Complex processes like change-risk management can take months without the help of intelligent automation. But when AI and automation are added to the mix, enterprises can automate manual tasks like data entry or repetitive tasks, make data accessible to the organization, and ensure every change remains compliant. All of this optimizes the workflow—sometimes to a huge degree. See how NatWest used intelligent automation below. 

Example #4: Process time goes from months to minutes.

NatWest, the UK’s largest business bank and second-largest retail mortgage provider, faced a problem implementing change. Before departments could start a change project or launch a product or application, they had to submit their request through multiple layers of policy checks and approvals, which could take up to 73 days. 

They turned to intelligent automation to reduce this process time. The bank built a new change-risk governance solution on an AI process automation platform, which allowed them to underpin the application with a data fabric. This enabled the team to leverage enterprise data seamlessly in ongoing change-risk governance cases and significantly reduced front-end triage for change colleagues. Building on that, they optimized the workflow so things move fast, and thanks to business rules, they can also ensure every change aligns to regulations and protocols. 

NatWest was able to consolidate 14 separate processes into one workflow, and cut the process down from 73 days to minutes.

Customer experience.

Modern technology has propelled customer expectations to new heights. How can you keep up? Intelligent automation allows you to execute workflows quickly as customer needs change. Removing manual work for employees means they can focus their time on improving customer service.  Beyond that, an AI process automation platform with a built-in data fabric technology gives employees faster access to data, providing the insights they need to make customer-centric decisions. And when data is combined with end-to-end process automation, employees can offer better service faster than ever.

Example #6: Aviva accelerates customer service response times by 9x.

Aviva, the UK’s largest insurer with 33 million customers across 16 countries, has a simple internal mission: delight their customers so they stay longer, recommend Aviva to their friends, and buy more Aviva products. But over the company’s history, Aviva has inherited 750 different insurance companies via acquisitions—along with all their systems, data, and processes—which led to a poor employee and customer experience. While trying to resolve issues with customers, employees would have to jump between anywhere from 12 to 22 distinct systems, making it impossible to resolve customer problems quickly and effectively. 

Using an AI process automation platform, Aviva unified these 22 different systems with a data fabric, then built one interface that gave employees all the process actions and data they needed to perform all call center operations in one place. The workflow assigns repetitive tasks to RPA bots, freeing the call center team to engage with customers. 

All of their optimizations via intelligent automation led to a 9x acceleration in customer service response times.


Intelligent automation’s impact.

It’s the right time to be researching intelligent process automation. With the fast pace of change across industries, engaging with enterprise AI and automation is a fundamental requirement for survival and success. In the short term, incorporating these technologies into your business process management discipline will increase overall productivity. And in the long-term, the right mix of artificial intelligence and intelligent automation will be pivotal for any enterprise that wants to maintain a competitive edge. 

8 experts weighed in on the big questions surrounding enterprise AI. Download their insights in the 2024 AI Outlook.