If organizations want to get further down the road – faster – in their digital transformation journey, they’re going to need fuel. And not just any type will cut it: They need artificial intelligence.
Over the last few years, companies have made smart investments in robotic process automation (RPA) and business process management (BPM). They’ve deployed RPA to streamline discrete processes and, in doing so, freed up countless hours of their employees’ time. BPM has helped them identify workflows throughout the organization that are ripe for automation, thus extending savings and improving efficiency. But RPA and BPM on their own aren’t enough to scale automation efforts.
The need for artificial intelligence to supercharge digital workflow transformation isn’t lost on automation and AI decision-makers. In a recent Forrester survey, 61 percent ranked RPA as their top use case for automation, followed by AI/Machine Learning (43 percent) and Digital Process Automation (40 percent). They know intelligence embedded into RPA and BPM is the key to scaling their automation initiatives—especially as their competitors press the pedal to the floor.
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It’s time to enhance and connect workflows
The pressure to digitally transform operations only intensified after the start of the pandemic. Customers today have more digital interactions with businesses—and higher expectations for each one. And let's not forget another major impact of the pandemic: hybrid work models. With the workforce spread out like never before, many businesses had to scramble for the right tools and rethink processes to get their teams access to the information and systems they needed without missing a beat. Hybrid work is here to stay, and so is the demand for information management and connected workflows that empower collaboration among employees no matter where they are.
Companies understand that to thrive in the post-pandemic world, they need to deliver better customer experiences, simplify regulatory compliance, and be more agile in the face of disruption. To succeed, they’ll need to rapidly identify and automate as many business processes as possible, focusing first on high-value workflows—such as customer engagement, finance and operations.
The problem is many of these workflows are still punctuated by time-consuming, inefficient and manual sequences. A key obstacle to full automation is the difficulty in extracting and processing unstructured information—such as emails, financial documents, forms, contracts, images and digital assets. Without this capability, businesses will find it challenging to develop collaborative working relationships between human and digital workers or build connections between systems.
Further complicating matters is the relentless surge of incoming information that has been buffeting organizations in recent years. And it's likely to get worse. The Association for Intelligent Management (AIIM) reports organizations expect the volume of inbound information to grow 4.5 times in the next two years. That same report also says organizations "expect more than 57 percent of this information to be unstructured (like a contract or a conversation) or semi-structured (like an invoice or a form)." So, not only will businesses be receiving much more information, but that information is going to be of greater complexity and variety.
These are just a few reasons why the road to true digital workflow automation is paved with artificial intelligence.
An intelligent automation platform brings together capabilities like RPA and machine learning so that businesses can automate labor-intensive tasks and drive greater value. For instance, after HMI Performance Incentives added intelligent automation to its platform, its client, Polyglass, took advantage. The manufacturer used artificial intelligence to streamline its loyalty program and encourage its customers to use it more often. Once its contractors could simply snap photos of receipts, the need to rekey data was eliminated. Document intelligence-enabled Polyglass to convert this unstructured data into highly structured data, including SKU numbers, line items, dollar amounts and more. The results? Not only is customer participation in the loyalty program up, but actionable insights are helping Polyglass sharpen its competitive edge.
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How AI fuels the engine
One way to think of the intelligent automation platform is as the fueling station for all your digital workflow transformation initiatives. With AI, the platform is capable of finding, extracting, processing and transforming data into insights powering organizational decision-making. This requires three components to be tightly integrated into the intelligent automation platform: document intelligence, process orchestration and connected systems.
- Document intelligence. Much of the information businesses need to onboard new customers or comply with regulatory reporting requirements is locked within documents and images. Though RPA on its own can parse structured data with ease, it needs artificial intelligence, including cognitive capture, machine learning (ML), natural language processing (NLP) and workflow orchestration to handle unstructured information and unlock its value.
- Process orchestration plays a role similar to a traffic cop. It coordinates the many automated workflows operating in your environment, ensuring collaboration with users, systems and data.
- Connected systems make it possible for organizations to integrate their systems into a network of intelligent technologies and services via an open architecture. This capability reduces complexity and saves time while also making valuable insights available to disparate systems across the enterprise.
Consider, for example, a new home buyer applying for a mortgage. In the past, the buyer would need to visit a bank office in person, present proof of identification, and then wait as the loan officer photocopied the ID and retyped the information into the application. Now, however, the applicant can use their phone camera to take a picture of their drivers’ license and upload the image to the application. The information is then automatically ingested, classified, extracted and delivered into multiple systems, where the data becomes more accessible and valuable to managers.
To the applicant, the experience is frictionless and satisfying, especially when approvals are granted in minutes. For the organization, the automation of this high-value workflow means its employees can work smarter and drive better business outcomes.
If companies want to work like tomorrow—today, they need intelligence built into their RPA and BPM technologies. Artificial intelligence capabilities like cognitive capture and machine learning, when embedded into RPA and BPM, transform these technologies into superpowers and allow companies to achieve true digital workflow transformation.
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Omid Aslani Director, Commercial Product Management, Kofax