By 2022, 65% of organizations that deployed Robotic Process Automation (RPA) will introduce Artificial Intelligence (AI), including Machine Learning and Natural Language Processing algorithms. Intelligent Automation (IA) is an automation solution that combines complementary automation technologies with AI-enabled intelligence to digitize business processes. IA employs AI to augment task-level automation using RPA within business processes that have been streamlined using Business Process Management (BPM). BPM is used to orchestrate users, data, tasks, systems, and RPA bots while AI is used to automate the decision-making process.  

Organizations tend to implement various automation tools, such as RPA, from multiple vendors to accelerate their digital transformation journeys. However, these solutions are often poorly integrated and delivered in silos to provide fragmented solutions. Without the oversight of an enterprise-wide strategy, these automation silos create technical debt and hinder an organization’s ability to achieve long-term agility.

“The deeper organizations get into their transformation initiatives, the more challenging it is to readjust their strategies. As a result, in hindsight, firms realize that they invested in a set of technologies that are challenging to maintain — leading to high technical debt”.

As an increasingly popular alternative to this ad-hoc automation, a single-vendor Intelligent Automation approach provides a holistic, scalable, and intelligently integrated solution for end-to-end automation. IA combines the individual benefits of RPA, BPM and AI tools with the over-arching objective of improving customer experience, organizational agility, and employee productivity.

IA helps organizations move beyond basic use-cases and low-hanging fruit towards an accelerated digital transformation. Yet many organizations fail to realize the full benefits of IA due to the challenges associated with skilled resources, security risks, legacy systems, adoption, and cultural shifts. Legacy systems can be difficult to integrate and too many legacy systems can minimize the increase in efficiency from IA. Perhaps the bigger challenges are the security threats that can arise from data leaks, unauthorized access, privilege abuse and system vulnerabilities. Improper planning and implementation will only add to the complexities through tool sprawl and weak quality assurance.

The rising trend of IA implementation within organizations can be attributed to its ability to achieve a quick ROI by transforming simple, manual, and repetitive front or back-office business processes. However, to achieve sustainable competitive advantage, organizations need to scale beyond the simple repetitive task automation and utilize the intelligent toolkits on an enterprise level. Successful organizations will follow a well-defined and structured approach to leverage IA capabilities and align it with their enterprise digital strategy.