Automation has undergone significant evolution, transitioning from basic tools that execute instructions to sophisticated systems capable of reasoning, learning, and acting autonomously. Robotic Process Automation (RPA) has been a pivotal development, allowing businesses to efficiently streamline structured and repetitive tasks. This technology remains fundamental, particularly effective for high-volume, rules-based processes, delivering speed and accuracy.
Building on the success of RPA, the integration of Artificial Intelligence (AI) has opened new avenues for automation. Often referred to as AI-powered automation, this next phase incorporates cognitive capabilities such as machine learning, natural language processing (NLP), optical character recognition (OCR), and Generative AI (GenAI). These advancements extend automation’s reach to understanding documents, data extraction, and sentiment analysis—tasks that surpass the structured domain of traditional automation.
Currently, a notable advancement known as agentic automation is emerging. This concept introduces autonomous AI agents that not only process information but also plan, reason, and act independently. By analyzing unstructured data and recognizing patterns, agentic automation can execute decisions with minimal human intervention, effectively addressing complex workflows that previously required continuous human oversight.
Is agentic automation replacing traditional and intelligent automation?
RPA and AI-powered automation are adept at managing repetitive, rule-based tasks, but they often struggle with complex, unpredictable workflows. Agentic automation bridges this gap by automating intricate, end-to-end business processes that were once deemed too dynamic for automation.
Nevertheless, agentic automation should not be perceived as a substitute for RPA and AI-powered automation; both retain distinct advantages. For lower complexity and predictable rules-based tasks, RPA operates with greater efficiency, reliability, and accuracy than agentic automation. Similarly, intelligent automation achieves higher computational efficiency and improved reliability in areas such as document processing, analysis, and communications mining. For example, Shriram Properties, a prominent real estate developer in India, streamlined core workflows across finance, HR, and supply chain using AI-powered automation. This led to a 70% reduction in manual effort, a 99% accuracy rate, and the recovery of over 1,000 days annually, allowing teams to concentrate on strategic initiatives. Additionally, the company achieved an 80% success rate in invoice automation, enhancing financial accuracy.
When synergized, RPA, AI-powered automation, and agentic automation facilitate comprehensive automation across enterprises. This synergy resembles a mosaic of agents and specialized robots collaborating within an orchestrated process, each executing their tasks most effectively. For example, RPA can gather data across systems, enabling AI agents to analyze and act upon it. In turn, agentic systems can leverage AI-powered automation for tasks such as document processing and customer support, significantly improving speed and accuracy throughout workflows.
What distinguishes agentic automation?
Agentic automation introduces enhanced speed, flexibility, and autonomy to enterprise operations. By managing routine and data-intensive tasks, AI agents liberate human teams to focus on strategic and creative endeavors. This transition not only boosts productivity but also enhances job satisfaction by allowing employees to engage in more meaningful contributions to organizational objectives.
The advent of low-code tools and natural language interfaces enables teams across various departments—not just IT—to deploy and manage AI agents independently. This democratization of automation alleviates pressure on technical teams and accelerates innovation throughout the organization.
However, as these technologies become increasingly autonomous and integrated into essential business operations, the need for effective governance becomes paramount. Establishing ethical frameworks and human-in-the-loop processes remains critical to ensuring responsible and safe automation practices. Moving forward, automation will not only execute tasks but will also learn, adapt, and collaborate with humans to spearhead the next wave of digital transformation.
As the landscape of automation continues to change, organizations should avoid rushing to adopt the latest technologies for the sake of novelty. The focus should be on how emerging technologies can foster true augmentation, empowering individuals to concentrate on their core strengths: strategic thinking, creative problem-solving, and innovation. With well-orchestrated collaboration between humans, AI agents, and robots, organizations can achieve improved efficiency, scalability, innovation, and enhanced decision-making capabilities.
The author is DebDeep Sengupta, Area Vice President for South Asia at UiPath.
Disclaimer: The views expressed are those of the author and do not necessarily reflect those of ETCIO. ETCIO is not responsible for any damage caused to any individual or organization, directly or indirectly.
