With digital transformation gaining momentum along with sophisticated IT implementation, most tasks within the business process are getting computerized. While humans are being employed to feed and control these tasks with data and direction, the actual tasks are being implemented by computers.
There have been huge advancements in processing power, communication technologies, transmission bandwidths, and other such IT-related infrastructure. These enhancements in computing technologies have allowed the entire business process to be considered as being IT-enabled.
As the search for constant optimization and efficiency continues, automating the human component of a computerized task has come to the fore. Automated bots are steadily replacing human-related interactions with systems to drive more efficiency and accuracy and reduce errors.
While digital transformation and the IT enabling of infrastructure continue at a high pace, there is now a renewed interest in replacing the human component in IT. Newer technologies allow for a higher degree of simulation of the human component in the system itself.
Automation is being introduced into all possible processes within the enterprise to remove the dependence on human interaction as much as possible. To that extend, let’s understand
- What are Bots and RPA?
- Understanding AI, Machine Learning, and Intelligent Automation
- The Emergence of Hyperautomation
Bots and RPA
Robotic process automation (RPA) is a technology that simulates human interaction with software deployed on devices. RPA creates bots or automation programs that can interact with other software program interfaces in a predesigned manner to complete a particular task. This bot can then be replayed and repeat itself to complete that particular task several times without any human intervention.
No doubt, RPA is very useful when the steps of human interaction with the software to complete a specific task are repetitive. RPA tools are relatively simple to learn and do not involve a high level of coding. This ensures a rapid adoption of RPA technologies in an enterprise.
Once trained, these RPA bots can emulate the human resources required to complete those tasks on a system, freeing up resources and achieving high efficiency. This reduces costs as well. RPA can be used to automate processes across the IT enterprise which are labor-intensive yet repetitive.
All in all, automation using RPA has resulted in cost reduction, higher workload capacities, and reduced errors. Most importantly, RPA adds value to a business process, freeing human resources to complete other tasks and improving the overall performance of an enterprise.
AI, Machine Learning, and Automation
Just like in other technologies, artificial intelligence (AI) and machine learning (ML) is being introduced in the space of automation. Tools and technologies are being used to proactively inject intelligence into the system based on data analytics. This allows for an enhanced decision-making process for the future. Self-learning abilities can also be introduced into the automation system.
As elucidated above, in robotic process automation, a bot is taught to repeat human interactions on software in a repetitive manner. Intelligent automation takes that RPA bot and combines it with enhanced technologies such as AI and ML, taking business process automation to a new level.
As such, the bot begins to predict outcomes based on collected data and make decisions for future events and actions. This process continuously gets modified and finetuned as more data is collected and analyzed. Any automation process or tool that displays this capability of self-learning and making decisions based on outcomes is considered as Intelligent Automation. Intelligent automation could also include other advanced technologies such as fuzzy logic, natural language processing (NLP), and computer vision.
Essentially, intelligent automation allows for more complex but repetitive IT tasks to be digitally transformed and automatically implemented. This results in increased business process efficiency and accuracy. Moreover, costs are reduced, and IT resource allocations get optimized. Most importantly, human resources are freed from mundane, repetitive tasks and can be assigned more crucial responsibilities.
Since intelligent automation is continuously building new data based on the analysis of older data to optimize the business process, there is an automatic increase in the traceability and observability of the entire business process. Also, as human interaction gets reduced across the entire workflow, cybersecurity breaches due to human errors get minimized.
The Emergence of Hyperautomation
Tools and technologies involving RPA and Intelligent Automation are now included in the IT war chest of any enterprise. The advantages of adopting various automation methodologies in workflow management and other business processes are now understood and accepted. Companies are rushing to include these technologies as a part of their digital transformation efforts.
But, ad hoc and not-thought-through implementation of these advanced automation tools and techniques could result in reverse consequences of efficiency and productivity. Hence the need for a structured and planned approach to automation and how to scale the existing automation within the enterprise has begun to emerge.
To that end, hyperautomation is really about automating and scaling automation within an enterprise within a structured framework. It’s a framework that makes a studied approach to automation and its implementation within an enterprise.
Hyperautomation uses existing tools of intelligent automation to make strategic decisions regarding what more can be automated, what automated processes can be reused, which automation can be scaled, and so on.
With the hyperautomation framework in place, much more of the business workflow gets automated, thus further increasing efficiency, boosting productivity, enhancing customer experience, and lowering costs. More data is collected, and there is more observability – resulting in better decision-making.
With the emergence of hyperautomation, digital transformation is now being complemented by a digital workforce using a framework of intelligent automation, RPA, NLP, computer vision, and other such technologies.
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