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Hyper-efficient business model that includes intelligent automation

How many of you are aware that the global Intelligent Process Automation market is expected to reach USD 13.75 billion by 2023, with a compound annual growth rate (CAGR) of 12.9 percent between 2018 and 2023?

Intelligent Automation (IA) has heralded the start of the Fourth Industrial Revolution and is rapidly altering the fundamental dynamics of the digital world, according to industry experts. In addition to driving high-value, smooth customer experiences, reducing outcome variability, and improving business decisions, it also has the potential to drive significant amounts of innovation.

This technology-driven innovation has found its way into a wide range of industries including banking, insurance, retail, oil and gas, logistics, telecommunications, and financial services, as well as many public sector and government institutions, which have emerged as key adopters.

Given the current turmoil caused by Covid 19, businesses across all industries are demonstrating a high level of acceptance for intelligent enterprise automation in order to keep up with technological evolution and become more agile in the post-pandemic era.

Robotic process automation (RPA), machine learning (ML), artificial intelligence (AI), computer vision, and natural language processing are just a few of the disruptive technologies that are ushering in a new era of enterprise process automation in which information and process silos are broken down.

What is Intelligent Enterprise Automation and how does it differ from traditional robotic process automation?

C-suite executives who are struggling to close operational gaps that are causing their internal functional silos to crumble are now taking the disruption caused by COVID-19 into consideration as a strategic consideration. In order to improve the efficiency, speed, and consistency of operations, Robotic Process Automation (RPA) is used as a lynchpin to raise core automation capabilities to a higher level.

RPA technology penetrates deeper into an organization's existing infrastructure and replicates mundane, repetitive rules-based tasks by mimicking human actions, allowing humans to devote their time and attention to more strategic endeavors. Using cognitive technologies to accelerate digital transformation journeys is the least expensive and most straightforward approach to accelerating digital transformation journeys.

Organizations can benefit from RPA technology by leveraging core benefits such as increased speed, faster turnaround time, and unprecedented levels of quality. However, without Artificial Intelligence, they will be unable to reap the benefits of faster decision-making capabilities, better scalability, and risk reduction.

Traditional RPA deployments frequently fail to scale when the following conditions are met:

  1. Exceptional candidates for robotic process automation (RPA) technologies include business processes that are rule-based, high volume, error-prone, and reliant on multiple fragmented systems for data. When an enterprise requires decision-making on an as-needed basis, however, the concept of traditional RPA technology defeats the purpose of the technology. Higher levels of manual intervention are required for more dynamic processes, which can be replicated through the use of Artificial Intelligence and Cognitive RPA.
  2. RPA bots become incomprehensible when the target user interface (UI) changes: RPA bots are designed to follow instructions and to be used in highly consultative deployments. They are prone to going blank in unexpected situations when there is no clarity on the instructions or memo they have been given. Intelligent Automation would benefit from their ability to learn and respond, as these abilities would be more appropriate for Intelligent Automation.
  3. Relying on ineffective governance: RPA bots that are left to run autonomously without supervision are more likely to fail. They perform at their best when processes are thoroughly optimized and components are carefully chosen. Human intervention is required on a frequent basis in non-standardized, poorly designed processes, which frequently results in the RPA deployment being an utter failure. In order to avoid automation failures, a robust governance framework is required.

As a result, many forward-thinking organizations that have previously benefited from RPA solutions are now looking to expand their capabilities. Intelligent Automation (IA) is the next stage in the digital transformation journey, and it is characterized by the use of artificial intelligence, machine learning, and dynamic workflows to trigger a judgment-based response. Businesses can now leverage the power of this innovative technology to drive a holistic transformation, as well as increased business agility and decision-making capabilities, by relying on its exponential value.

What to Expect in the Future: Intelligent Automation is the New Normal

When it comes to transforming fragmented business processes and increasing accuracy through automation, Intelligent Automation is a game-changing strategy for all organizations looking to stay ahead of the curve in an increasingly fast-paced environment. Organizations can push the boundaries of automation and unleash the next level of intelligent automation capabilities by combining cognitive RPA with artificial intelligence (AI). This is accomplished through the use of natural language processing, data mining, and pattern recognition technologies.

The goal of achieving strategic coherence between people, processes, and technology has motivated many executives and decision-makers to invest significant resources in Intelligent Enterprise Automation solutions. The success rate of RPA + Intelligent Automation within an organization is influenced by a number of important factors, which are as follows:

  1. Priority one should be given to a process-centric perspective: When robotic process automation (RPA) is deployed as a core element of broader business process management and digital transformation initiatives, process-centricity is extremely important for every business process automation project, regardless of size. If an organization wants to make RPA and Intelligent Automation a huge success, it must re-imagine business processes by leveraging relevant design-thinking principles, which will result in the improvement of customer experiences while maintaining compliance and governance.
  2. Digital Enterprise Automation: As a result of the rapid Cloud Computing revolution, Enterprise Integration has been pushed towards a Hybrid Integration Model, which allows for unified output across an organization. HIPs are typically used to allow different on-premises applications to seamlessly integrate with cloud and SAAS-based applications, as well as with other third-party applications. This results in real-time development, increased process efficiency, and the lowest possible risk – all of which contribute to seamless Digital Enterprise Automation.
  3. Tight integration of RPA capabilities, enterprise software, and APIs: Enterprises are maturing toward the tight integration of RPA capabilities, enterprise software, and APIs in order to achieve high productivity while reducing the need for custom development work and improving customer experiences. They will be able to transform rule-based processes into truly intelligent automation, which will result in more significant benefits such as higher cost reductions, increased competitiveness, and new capabilities, among others.

The Concluding Remarks

Intelligent Process Automation (IPA) is quickly becoming the epitome of the next-generation operating model, according to industry experts. It ensures high productivity and efficiency while also lowering operational risks, increasing cognitive capabilities, and providing better customer experiences by simplifying interactions and speeding up processes. Gain 6x faster turnaround time across your enterprise-wide digital transformation journey, whether it's for business workflows or IT operations. 

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