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IA: Welcome to the Next Level of Automation

Today’s businesses have to boost efficiency while delivering ever-higher quality. And that’s why a growing number are embracing automation. But while robotic process automation (RPA) has transformed many industries, it can handle only relatively simple tasks. Enter intelligent automation (IA) – a combination of RPA and AI geared specifically to complex processes. IA takes automation to the next level, significantly lowering costs, hiking productivity, and enhancing customer experience.


Automation: Transforming a Wide Variety of Sectors


To remain competitive, businesses must constantly increase their efficiency and quality. So, it’s small wonder that many are implementing automation solutions – in the form not only of traditional nuts-and-bolts industrial robots, but also robotic software applications.


Leveraging the speed of quantum computing, robotic process automation (RPA) is already driving improvements in a host of sectors ranging from finance and IT, right through to customer service. In fact, the tech has proven so effective that the worldwide RPA market is expected to total USD 13.74 billion by 2028.


When Conventional RPA Reaches its Limits


But while RPA can rapidly and reliably handle many repetitive manual jobs, the tech does have its limitations. Because it uses rigid rule sets built on basic conditional (if-then) logic, RPA is unable to process complex tasks involving heterogeneous and unstructured data.


These more challenging processes can be automated using RPA, but only if employees first convert unstructured data into structured formats – a time-consuming, low-value chore. Another shortcoming of RPA is its inability to tackle cognitive tasks, for which rules can’t be modeled and which require human expertise and experience.


RPA + AI = IA


This is where intelligent automation (IA) comes in. Created by marrying RPA with cutting-edge artificial intelligence (AI), IA delivers considerable value by automatically processing and converting unstructured data into structured formats that RPA can work with.


For companies that have already embarked on their digital transformation, IA is the logical next step. And its vast potential is evident from recent growth forecasts: By next year, the global market for the underlying tech is forecast to be worth a whopping USD 595.6 billion.


For companies that have already embarked on their digital transformation, IA is the logical next step. And its vast potential is evident from recent growth forecasts: By next year, the global market for the underlying tech is forecast to be worth a whopping USD 595.6 billion.


Self-Learning – for Robots


With IA, people and technology work together in a new way. Employees no longer handle the upstream chore of converting unstructured into structured data. Now, they deploy machine learning (ML) so that the automation tools can learn to make their own AI-enabled decisions. This is what sets IA apart from traditional automation: Once the ML foundation is in place, the computers effectively train themselves.


Whenever two technologies come together, the value generated is exponential. And IA is no exception. RPA plus AI is a transformative solution that goes beyond isolated tasks, streamlining entire processes and simplifying end-to-end workflows.


Potential Hazards?


However, before we zoom in on IA, a word of warning is perhaps in order. Because this tech revolves around computers training themselves, we need to proceed with caution. For example: If we humans don’t formulate tasks carefully, it’s conceivable that IA entrusted with, say, eradicating a particular disease could do so by taking the perfectly logical step of killing everyone suffering from it.


This is an admittedly extreme example. But while IA may not currently have such devastating potential, we should be wary of how we develop and deploy the technology, carefully consider unintended outcomes from the outset, and develop effective governance and controls.


The Case for Deploying IA


IA can be implemented in almost any industry and is ideally suited for recurring tasks that have high error rates when processed manually. For example, automakers can deploy IA to accelerate production while reducing the risk of error.


Other prime candidates for the tech include companies that already deploy RPA but have issues with its limitations – for example, because of its inability to adapt to constantly changing processes. Organizations looking to automate end-to-end business processes are also an excellent fit for IA.


Planning for Maximum Benefits


As with any new technology, if you want to succeed with IA, you must have a clear vision of what you’re aiming to achieve. Consequently, a robust and realistic strategy is a must. Your plan should include clarification of central questions such as: “Why do we want to integrate IA?” and “Which areas do we need to prioritize?”


If your processes are IA-ready, and if you’ve drawn up your strategy, you can expect to reap significant benefits in terms of cost, productivity, and customer satisfaction. It almost goes without saying that automation cuts costs. And while it is difficult to put an exact figure on what IA can deliver here, savings are likely to be extremely high.


Exponential Productivity Increases


When it comes to productivity, IA delivers by mimicking routine human tasks and learning to do them better. But that’s not the only way IA can hike productivity. By taking on these tasks, the tech frees up employees for value-adding work requiring unique human qualities – like emotional intelligence, reasoning, and judgment.


Here, too, we see the exponential increases that melding two technologies can bring. RPA is known to increase productivity by up to 14%; AI goes even further, taking the figure as high as 30%. And based on my professional experience, I’d say that IA has the potential to increase productivity by as much as 50%.


Greater Speed, More Satisfied Customers


IA not only reads documents, extracts information, and decides what to do next: It does all this at very high speeds. In addition, the tech ensures service continuity. Because software robots never sleep, they can deliver the round-the-clock global service today’s customers crave.


Finally, by enhancing customer experience, IA gives companies a vital competitive edge by enabling them to get higher-quality, more reliable products to market sooner – and by answering customer queries faster or even in real time.


Want to Find Out More?


If you’re interested in learning more about IA, real-world use cases, and the potential benefits for your business, feel free to get in touch with me for an initial discussion.

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