In this special guest feature, Tony Higgins, CTO at Blueprint Software Systems, discusses the integral role AI plays in intelligent automation and the level of growth intelligent automation (which combines AI and RPA) is likely to see in 2021. Tony is responsible for the vision and evolution of Blueprint’s Enterprise Automation Suite, a powerful digital process design and management solution that enables enterprise organizations to identify, design, and manage high-value automations with speed and precision in order to scale the scope and impact of their RPA initiatives. Tony has a broad base of software delivery skills and experience ranging from start-ups to global enterprises, and is passionate about building technology that helps teams to rapidly optimize, automate, and digitally transform their organizations.
2020 will long be remembered as the year in which COVID-19 caused worldwide upheaval, forcing businesses across all industries to deal with surges in supply and demand, remote workforces, and market fluctuations.
High on the list of workplace disruptions ushered in by the pandemic was unprecedented growth in the adaptation and use of robotic process automation (RPA) to improve both back-office operations and production activities. Recognizing that automation can ensure fast, efficient, and error-free solutions regardless of external obstacles, more companies than ever before turned to RPA in 2020 to handle everything from order processing and fulfillment to transportation management and customer support.
While many of those same businesses seem poised to shift their focus in 2021 to better design, improved planning, and greater delivery of automations that will enable RPA to function with increased stability and fewer errors, at least some companies will continue to push the boundaries of RPA in the year ahead by experimenting with artificial intelligence and its two related technologies – intelligent automation and hyperautomation.
While still not completely embracing AI, these companies increasingly will come to understand that RPA and AI are complementary technologies that can support each other and coexist in integration to form a more robust and comprehensive platform for automation. Blending the rules-based automation capabilities of RPA with the cognitive capabilities offered by AI and the trial-and-error learning capabilities of machine learning, intelligent automation will enable end-to-end automation of complete business processes and orchestration of work across teams comprised of both bots and humans.
As more businesses place greater emphasis on automation in 2021, it appears likely they will aggressively adopt intelligent automation to automate decision-based sub-processes designed to augment the rules-based processes being automated with RPA. Intelligent automation, after all, is best suited for processes that require human judgment. Where RPA is tactical, intelligent automation is strategic, leveraging learning algorithms and models that can be trained or fine-tuned to improve or self-correct on task performance over time.
All of this will trigger an increased reliance on AI and greater adoption of AI-fueled technologies such as machine learning, computer vision, and natural language processing. And while not likely to see a complete transition in 2021, RPA tools that use the cognitive capabilities offered by AI will eventually replace those that don’t. Robots are only as good as they are programmed to be. Bottom line, intelligent automation offers organizations greater value and significant advantages to business process automation at enterprise scale than RPA alone.
Given the transformational impact on business efficiency and strategy these technologies potentially hold, it is fair to expect them to receive a good bit of attention – and investment – in 2021. They also seem likely to open the door for increased adaptation and implementation of hyperautomation, often dubbed RPA’s smarter, faster, more sophisticated relative, by large-scale enterprises.
Harnessing the power of AI, RPA, and machine learning, hyperautomation is the implementation of an end-to-end automation toolchain that allows organizations to automate more complex and complete processes.
Hyperautomation won’t be limited just to the tools needed to carry out automation. It also involves establishing protocols for every step of automation, including process discovery, process optimization, design, planning, development, deployment, and monitoring. Properly implemented, hyperautomation will enable businesses to automate the integration, DevOps, monitoring, and management processes compartmentalized by traditional RPA into single, more complete automated processes, boosting efficiency and productivity on a larger scale than ever before.
While 2021 is unlikely to see these technologies reach their full potential, the hand-writing is already on the wall. AI and RPA are no longer limited to programmers. The technology is becoming readily accessible to business users in the form of more intuitive and user-friendly interfaces with the citizen developer in mind.
After a year that has magnified the importance of automation, these technologies are well-positioned to enable organizations to automate more and more of their business processes in order to drive operational efficiency, cost reduction, improved employee and customer experiences, and resiliency. Increasingly, AI and machine learning will be implemented to augment RPA-enabled digital workers, enabling employees to focus on more meaningful, high-value work.
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