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Intelligent Business Automation: A framework for combining RPA and AI

December 13, 2022

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Intelligent business automation (IBA) is one of the high points of modern-day technologies that swiftly and accurately serve contemporary business needs. However, the foremost challenge currently is the large volume of unstructured and semi-structured data requiring manual intervention in the absence of automation. This is where the role of IBA solutions becomes crucial due to its ability to segregate unstructured data from a humongous set of data information. Hence, it is always advisable to implement such tools and solutions to drive efficient practices in the workspace. Failing this will only result in wasted human work hours and sluggish progress.

The best part of IBA is that Artificial intelligence (AI) is now stretching the scope of Robotic Process Automation (RPA) with the help of IBA. This is achieved by implementing innovative algorithms that deploy predictive analytics to make better-informed decisions. Moreover, repetitive mundane tasks can be undertaken with an infusion of intuitive and actionable insights, yielding intelligent business process automation.

What is Intelligent Business Automation?

Intelligent Business Automation harnesses the combined potential of RPA, AI, and even intelligent OCR. Be it business process management workflows or handling (un)structured data, IBA relies on the unified information made available across various platforms. This ensures the combined effect of vital details and information accessible to all stakeholders. Furthermore, decision-making engines apply algorithm-based logic to extrapolate existing data and identify potential trends for improving processes.

Such enhancements also ensure sustainable development for future process flows. Consequently, this leads to quicker and more versatile operability for the masses and ergonomic interfaces, augmenting planning for streamlined commercial management. Automation in business intelligence is the future of how companies transact and operate. Gartner predicted that by 2025, 70% of organizations would incorporate structured infrastructure automation for flexible and efficient workflows, increasing by 50% from 20% in 2021.

Why do businesses need IBA?

As IBA can boost productivity with greater capacity or volume to process data, this can enable businesses to meet fluctuating and unexpected demand with a consistently stable yet dynamically capable supply. However, it also drives the main factor of operational contingency by adapting to various factors, favoring and prioritizing those that matter the most.

Significant impacting variables include the ability to drive commercially affiliated processes, including production and profitable exchanges through intelligence-based information. For instance, demand sensing comes from AI-based algorithmic computation to detect demand signals. Thus, an intelligent business automation platform offers a seamless flow of businesses by encompassing everything they need in one unified platform.

Strategies to implement IBA

IBA mainly depends on RPA and AI, which are the backbone for automating processes. Therefore, the method includes robust automatable frameworks where AI can be easily implemented. Moreover, various system formats must share common or universal compatibility and support to ensure a seamless transition.

Hence, AI is more focused on analyzing the needful with an intelligent digital outlook, whereas Robotic Process Automation capitalizes on this with an added measure of repetitive task assignability. This fulfills all monotonous yet essential tasks, such as data collation (promoting proactively reactive remedial actions). As per a survey by Gartner, only 50% of enterprises will develop skills for infrastructure automation across hybrid and multi-cloud platforms’, an increase of 40% from less than 10% in 2021.

Top 5 ways IBA combines AI and RPA to increase business efficiency

The synergistic effect of two or more factors tends to have a greater than combined overall efficacy. These streamlined and accurate plus productive results are achieved using a variety of methods, including:

  • Better productivity: Automated applications cum processes can run quicker. Such automation drives better decision-making, forecasting, and predictions (as aforesaid) using multi-sourced live (un)structured data empowers organizations. This boost in accuracy and production rates expedites planning cycles. Examples include deploying robotic process automation to generate and distribute monthly reports, producing valuable data.
  • Lower overheads: Scalable cost lowering is critical to enriching efficiency within any system.
  • Enhanced accuracy: Both unstructured data and automated repetitive processes ensures apt decision-making. Lower human intervention improves precision and curbs errors incurred via manual data entry.
  • Great customer experience: Organizations can better understand and fulfill customer needs, offer better services, and focus on qualitative communication. Optimized customer journeys, satisfaction levels, responsiveness, and seamless support are just some of the many advantages of both AI and RPA.
  • Shift to intelligent work processes: Transition manual to intelligible and developmental work for employees, thereby saving and reinvesting vital resources. This value is imperative to maintain and sustain.

What are the challenges of Intelligent Business Automation adoption?

  • Discontinuity in workers’ adoption of new systems and their respective implementation. A lack of training or inconsistent application of such solutions results in delayed uptake of automated enhancements. This causes unnecessary gaps in revolutionizing how we handle data and its implications for our operations.
  • IT unpreparedness limits how resources and data storage can be leveraged for quick implementation. Furthermore, specialized training may be required to upskill employees, and dedicated IT support teams are also needed. This only adds to the ‘burden’ of the initial investment when curating an IBA-based platform that operates on the main principle of automation-powered intelligence.
  • Employees are unwilling to adapt to such intelligence-based processes, often fearing redundancy. Still, many workforces retain and promote those who can critically think, analyze, and demonstrate similar cognitive traits. The ability to scale and troubleshoot creatively is of utmost importance to many brands. This drives versatility within any organization to promote true interconnectedness with human-in-the-loop interactions.
  • Haphazard future vision where the implementation of IBA and its effect on the workers are both unknown, uncertain, or even feared. How can companies confidently implement any new technology to improve their workforce or operations without a clear plan or outlook? The faster we can drive a unified and symbiotic system-based workflow, which is methodical, the better-prepared everyone will be for the future. Moreover, all brands would be more resilient to dealing with unfamiliar or even unprecedented future events. Situational contexts will no longer rule brand success but rather how they can adapt accordingly.

Key use cases of IBA

  • Firstly, Customer Relationship Management (CRM) warrants analyzing vast datasets. What better way than to combine the potential of both RPA and AI to drive the entire end-to-end process? Accessing or retrieving information has never been easier than with IBA. Not only does this detect and identify what type of information is required, but also seamlessly automates the process of categorizing these details for easy future reference.
  • Additionally, HR onboarding can benefit from IBA by aligning compliance adherence for regulatory approvals. By correlating such pertinent data with its various sources, such as documentation, HR professionals can consolidate all information and map it to their databases for easy future reference. Not only does this augment hiring, joining, and talent acquisition processes, but it also ensures better statutory compliance.
  • IBA can also power product lifecycle management with (un)structured data across various systems. This intersystem design provides a versatile output tool to ensure greater productivity and financial growth. In addition, the universally compatible format supports multiple operating systems and environments for a seamless approach across many projects.
  • Finally, IBA drives inventory forecasting with its intuitive abilities and predictive analytics. In addition, it offers invoice generation support, automates back-office ordering, complex analysis of passive data mapping, and even item tracking. This saves human invested time, effort, and connected office resources, only enhancing the overall customer experience.

IBA trends and future scope

More and more businesses may accept AI & RPA-based IBA within their operations. Whether healthcare or financial or banking vendors, everyone is gearing up to revolutionize and automate their vital processes to deliver better service to consumers. In addition, data-based algorithms will power low or no-code platforms, be it within the retail or wholesale industries.

When implementing a new strategy in business, companies should always be mindful of the implications on existing processes to enrich and not impede them in any way. Hence, firms need to plan what needs improvement, how this is intended, which objectives we must fulfill, by when (with set feasible timelines), where it needs to be applied, and why. Once they have clarity, they can then proceed with the implementation accordingly. Hence, these will ensure that the ideal version of IBA is constantly rolled out across any business to automate its processes.

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