Cognitive automation promises to enhance other forms of automation tooling, including RPA and low-code platforms, by infusing AI into business processes. These enhancements have the potential to open new automation use cases and enhance the performance of existing automations.
"As automation becomes even more intelligent and sophisticated, the pace and complexity of automation deployments will accelerate," predicted Prince Kohli, CTO at Automation Anywhere, a leading RPA vendor.
Many CIOs and other IT leaders are increasingly turning to cognitive automation to dramatically improve efficiency, business resiliency, employee productivity and growth to create a digital workforce that utilizes the best of bots and human ingenuity. Here are five of the benefits of cognitive automation that they can expect in the enterprise:
1. Unlocking new value
"The shift from basic RPA to cognitive automation unlocks significant value for any organization and has notable implications across a number of areas for the CIO," said James Matcher, partner in the technology consulting practice at EY.
These areas include data and systems architecture, infrastructure accessibility and operational connectivity to the business.
Data architecture and infrastructure have long been in the CIO's wheelhouse, and although the exponential growth of data volumes and the need to make the data easily accessible and dynamic is more complex today than ever before, the greatest shift for any CIO will be in how closely they need to integrate with the business and their processes.
As the digital agenda becomes more democratized in companies and cognitive automation more systemically applied, the relationship and integration of IT and the business functions will become much more complex.
"Cognitive automation by its very nature is closely intertwined with process execution, and as these processes consistently evolve and change, the IT function will have to shift from a 'build and maintain' model to a 'dynamic provisioning' model," Matcher said.
This shift of models will improve the adoption of new types of automation across rapidly evolving business functions. CIOs will derive the most transformation value by maintaining appropriate governance control with a faster pace of automation.
2. Streamlining IT
Although much of the hype around cognitive automation has focused on business processes, there are also significant benefits of cognitive automation that have to do with enhanced IT automation.
"Cognitive automation can be the differentiator and value-add CIOs need to meet and even exceed heightened expectations in today's enterprise environment," said Ali Siddiqui, chief product officer at BMC.
In this domain, cognitive automation is benefiting from improvements in AI for ITSM and in using natural language processing to automate trouble ticket resolution.
Cognitive automation could also help detect and solve problems buried deep within an enterprise that could go undetected until a problem arises and then takes up the bulk of IT's time to resolve, such as a critical system bug, site outage or a potential security threat. Instead of having to deal with back-end issues handled by RPA and intelligent automation, IT can focus on tasks that require more critical thinking, including the complexities involved with remote work or scaling their enterprises as their company grows.
Additionally, modern enterprise technology like chatbots built with cognitive automation can act as a first line of defense for IT and perform basic troubleshooting when end users run into a problem.
"With a team that is free to innovate and contribute improvements to the organization, CIOs can deliver higher employee satisfaction, improve customer retention and achieve incredible time and resource savings that directly impacts their bottom line," Siddiqui said.
3. Multiply value of automation
CIOs should consider how different flavors of AI can synergize to increase the value of different types of automation.
"Cognitive automation multiplies the value delivered by traditional automation, with little additional, and perhaps in some cases, a lower, cost," said Jerry Cuomo, IBM fellow, vice president and CTO at IBM Automation.
He observed that traditional automation has a limited scope of the types of tasks that it can automate. For example, they might only enable processing of one type of document -- i.e., an invoice or a claim -- or struggle with noisy and inconsistent data from IT applications and system logs.
Cognitive automation can use AI to reduce the cases where automation gets stuck while encountering different types of data or different processes. For example, AI can reduce the time to recover in an IT failure by recognizing anomalies across IT systems and identifying the root cause of a problem more quickly. This can lead to big time savings for employees who can spend more time considering strategic improvements rather than clarifying and verifying documents or troubleshooting IT errors across complex cloud environments.
4. Automated decision-making
Another benefit of cognitive automation lies in handling unstructured data more efficiently compared to traditional RPA, which works best with structured data sources. This enables executing higher value activities automatically. RPA is often used to deliver low-value, high-frequency automation.
"With cognitive automation, CIOs can move the needle to high-value, high-frequency automations and have a bigger impact on the bottom line," said Jon Knisley, principal of automation and process excellence at FortressIQ.
One organization he has been working with predicted nearly 35% of its workforce will retire in the next five years. They are looking at cognitive automation to help address the brain drain that they are experiencing.
"Ultimately, cognitive automation will morph into more automated decisioning as the technology is proven and tested," Knisley said.
Down the road, these kinds of improvements could lead to autonomous operations that combine process intelligence and tribal knowledge with AI to improve over time, said Nagarajan Chakravarthy, chief digital officer at IOpex, a business solutions provider. He suggested CIOs start to think about how to break up their service delivery experience into the appropriate pieces to automate using existing technology. The automation footprint could scale up with improvements in cognitive automation components.
5. Improving operations and CX
Anthony Macciola, chief innovation officer at Abbyy, said two of the biggest benefits of cognitive automation initiatives have been creating exceptional CX and driving operational excellence. In CX, cognitive automation is enabling the development of conversation-driven experiences. He expects cognitive automation to be a requirement for virtual assistants to be proactive and effective in interactions where conversation and content intersect.
Cognitive automation is also starting to enhance operational excellence by complementing RPA bots, conversational AI chatbots, virtual assistants and business intelligence dashboards.
"To achieve this level of automation, CIOs are realizing there's a big difference between automating manual data entry and digitally changing how entire processes are executed," Macciola said.
These technologies are coming together to understand how people, processes and content interact together and in order to completely reengineer how they work together.
Start simple and build up
A company's cognitive automation strategy will not be built in a vacuum. While technologies have shown strong gains in terms of productivity and efficiency, "CIO was to look way beyond this," said Tom Taulli author of The Robotic Process Automation Handbook. Cognitive automation will enable them to get more time savings and cost efficiencies from automation.
While there are clear benefits of cognitive automation, it is not easy to do right, Taulli said. CIOs need to create teams that have expertise with data, analytics and modeling. Because of this, it is a good idea to start with clear-cut use cases. And it's usually better to focus on back-office applications. Then, as the organization gets more comfortable with this type of technology, it can extend to customer-facing scenarios.
It's also important to plan for the new types of failure modes of cognitive analytics applications.
"The governance of cognitive automation systems is different, and CIOs need to consequently pay closer attention to how workflows are adapted," said Jean-François Gagné, co-founder and CEO of Element AI.
These systems require proper setup of the right data sets, training and consistent monitoring of the performance over time to adjust as needed. Cognitive systems may be more resilient than RPA in many ways.
"But this doesn't mean they don't need proper care and adjustments over time," Gagne said.