Intelligent Automation is an umbrella term that refers to the use of different automation technologies to improve business processes. It includes multiple approaches, most notably Robotic Process Automation (RPA) and Agentic AI, each designed to solve different types of automation problems.
Rather than being a single technology or a combined execution model, Intelligent Automation provides organizations with options. Depending on the nature of a process, teams may implement RPA, Agentic AI, or both independently. This FAQ explains what Intelligent Automation means, how RPA and Agentic AI differ, and when each approach is used.
At Varishtha Infotech, we work with organizations at different stages of their automation journey. Some rely heavily on RPA to stabilize high-volume processes, while others are exploring Agentic AI for decision-driven workflows. Our role is to help teams assess, implement, and operate the right automation approach based on real operational requirements, not trends.
1. What is Intelligent Automation?
Intelligent Automation is a strategic framework for automating business processes using the most appropriate automation technology for each use case. It serves as an umbrella category that includes RPA, AI-driven automation, and other related technologies.
The goal of Intelligent Automation is not to force processes into a single automation model, but to improve efficiency, accuracy, and scalability by selecting the right approach for the problem at hand. Organizations may adopt one or multiple automation methods under this framework based on their operational needs.
2. What is Robotic Process Automation (RPA)?
Robotic Process Automation is a rule-based automation approach designed to execute structured, repetitive tasks across digital systems. RPA bots follow predefined workflows and interact with applications in the same way a human user would.
RPA is commonly used for processes such as Data Entry, Reconciliation, System updates and other tasks where inputs, rules, and outcomes are clearly defined. It is widely adopted in enterprise environments because it is predictable, auditable, and scalable.
3. What is Agentic AI?
Agentic AI is an automation approach that uses AI-driven agents capable of reasoning, decision-making, and adapting to changing conditions. Unlike RPA, Agentic AI does not rely solely on fixed rules or scripts.
Agentic AI is used for processes involving unstructured data, complex decision paths, or frequent variation. AI agents can evaluate context, choose actions dynamically, and learn from outcomes, making them suitable for exception handling, decision workflows, and adaptive operations.
4. What is the difference between RPA and Agentic AI?
RPA and Agentic AI address different types of automation requirements.
RPA is best suited for predictable, structured processes where rules remain stable over time. It focuses on execution and consistency.
Agentic AI is suited for processes that require judgment, flexibility, or interpretation. It focuses on decision-making and adaptability.
Both approaches fall under Intelligent Automation, but they are implemented independently based on process characteristics rather than combined by default.
5. Who should adopt Intelligent Automation?
Intelligent Automation is relevant for organizations that rely on manual processes, operate across multiple systems, or manage high volumes of transactions. This includes enterprises and mid-sized organizations across Finance, Operations, HR, IT, and Supply Chain functions.
Organizations may adopt RPA to standardize repetitive work, Agentic AI to handle complex decision-making, or both at different stages or in different areas of the business.
6. What business problems does Intelligent Automation solve?
Intelligent Automation reduces manual effort, operational cost, and process inconsistency. It helps organizations improve speed, accuracy, and scalability while reducing dependency on individual resources.
RPA addresses inefficiencies caused by repetitive manual tasks, while Agentic AI addresses challenges related to variability, exceptions, and decision complexity. Each solves a different class of business problems under the broader Intelligent Automation umbrella.
7. What does an RPA or Intelligent Automation POC look like?
A proof of concept (POC) is a focused initiative used to validate an automation approach on a specific process. An RPA or Intelligent Automation POC typically runs four to six weeks and targets one clearly defined workflow.
The objective is to assess feasibility, demonstrate measurable improvements, and confirm alignment with business requirements before broader rollout. POCs can be conducted independently for RPA or Agentic AI, depending on the use case.
Varishtha Infotech conducts RPA and Agentic AI POCs independently, depending on the process requirements, ensuring technology selection is driven by use case rather than platform bias.
8. What systems can RPA and Agentic AI integrate with?
Both RPA and Agentic AI can integrate with a wide range of enterprise systems. This includes ERP platforms such as SAP and Oracle, CRM systems like Salesforce, finance tools including NetSuite and QuickBooks, HR platforms such as Workday, legacy applications, and custom internal systems.
Varishtha Infotech has delivered automation across finance, HR, Procurement, and Supply Chain environments for organizations in industries including Insurance, Healthcare, Logistics, and Manufacturing.
9. Is Intelligent Automation only for large enterprises?
Intelligent Automation is commonly adopted by large enterprises, but it is equally applicable to mid-sized organizations with growing operational complexity. The deciding factor is process volume and variability, not organization size.
Organizations can start with a limited scope and expand automation initiatives incrementally as value is proven.
10. How should organizations get started with Intelligent Automation?
Most organizations begin by identifying processes with clear ownership, measurable outcomes, and automation potential. A structured assessment followed by a POC helps determine whether RPA or Agentic AI is the right approach for each process.
At this stage, Varishtha Infotech typically supports organizations by assessing existing processes, automation maturity, and system landscapes to recommend the most appropriate approach. Rather than forcing a single technology, the focus is on matching RPA or Agentic AI to real operational requirements.
From there, automation initiatives can scale across functions with appropriate governance, documentation, and long-term planning, ensuring stability and measurable value as automation programs grow.
Discover how RPA and Agentic AI can transform your business efficiency. Schedule a consultation with Varishtha Infotech now.
