by Mitul Mehta, on Mar 27, 2025 6:21:00 PM
Key takeaways from the blog
- Agentic AI is a harbinger of unimaginable productivity and efficiency gains.
- It exhibits significant autonomy and exponentially increases the processing speed.
- It intelligently automates the business landscape and establishes process orchestration.
With the onset of Agentic AI, you can ensure dynamic changes that far supersede the erstwhile Agile model. While yesteryear’s automation systems required almost 24 months to become functional for major transformations and 6 months for minor transformations, today’s conversational user interfaces (CUIs) powered by Agentic AI can run an entire development cycle within minutes and go-live within days. They enable citizen developers to conversationally orchestrate software development by using CUIs to give commands or prompts in simple English or natural language. These AI-driven technologies exhibit significant autonomy and exponentially increase the processing speed. As a result, the benefits brought in by these AI-driven technologies far supersede the challenges.
What is Agentic AI Orchestration? How does it differ from Robotic Process Automation?
Agentic AI Orchestration manages and coordinates multiple AI Agents to work in collaboration towards a complex yet common goal, thereby driving higher process autonomy. Agentic AI differentiates itself from Robotic Process Automation through its autonomous and goal-oriented approach.
Robotic Process Automation automates simple to medium complexity processes through a rule-based approach. It automates repetitive and predictable processes. It follows pre-defined rules and in case of exceptions, raises flags for human intervention. It lacks adaptiveness and the ability to autonomously decide the next best action, which is a forte of Agentic AI.
How does an AI Agent orchestrate business processes?
An AI Agent is autonomous and goal-driven and leverages the underlying critical capabilities, which include AI-models, historical data, APIs and internal triggers to fetch an assortment of automation solutions, and reflection and orchestration capability.
- AI-model: The model is the brain of the AI Agent. It supports critical decision-making, reasoning, and natural language understanding. The user interacts with the AI Agent by using conversational user interfaces (CUIs).
- Historical data: AI Agents leverage historical data and past learnings in the current context to achieve a goal. It enables the agent to tap into enterprise knowledge and orchestrate and adapt to the changing business environment.
- APIs and internal triggers: APIs, functions, and triggers enable the AI Agents to intelligently select the different automation bots and solutions and autonomously navigate a complex orchestration to achieve a business goal.
- Reflection and orchestration: It focuses on the goal, breaks it into an orchestration plan, and monitors the journey towards achieving the goal. When the environment changes, the agent reflects and reassesses the scenario and generates a new plan to achieve the original goal.
How does Agentic AI securely hyperscale business processes?
Agentic AI enables businesses to hyperscale processes by leveraging multi-agent collaboration and using AI guardrails. It involves a rapid increase in the automated processes without a corresponding increase in overhead.
- Multi-agent collaboration: It is a paradigm that enables Agentic AI to achieve complex goals at speed, where one master agent splits the complex process into multiple sub-goals for multiple specialized AI Agents to achieve a common goal. This group of AI Agents autonomously prioritizes the sub-goals, collaborates among themselves, and communicates with each other to achieve the shared goal.
- AI guardrails: They ensure robust governance, which is critical to support process autonomy. The agents are specifically trained on enterprise data sources to ensure that the output is factual. They are granted role-based access and permissions to systems and processes, like their human counterparts. The guardrails ensure maximum autonomy thresholds and similar mechanisms to pause activity in case of unexpected agent behavior.
What is the role of the human in the loop in Agentic AI?
Agentic AI elevates the status of the human from being a business users to supervisors. The elevated human role is responsible for strategic governance, setting goals, defining guardrails, and supervising the agent performance. The AI Agent escalates cases to humans only where required, thereby freeing them from routine work. Humans also use the AI Agent audit logs to understand the specific path that they took. The knowledge is useful for continuously optimizing the AI model. The role of the human thus shifts from managing tasks to managing the AI Agent intelligence to optimize process outcomes.
Advantages of Agentic AI adoption
Some of the major advantages of Agentic AI include –
- Faster workplace transformation: As stated earlier, Agentic AI brings unprecedented gains in business productivity and efficiency. The automation of repetitive tasks in an autonomous manner saves considerable time and effort such that the same number of human resources produce more meaningful outcomes at a higher speed.
- Innovation at scale: The Agentic AI platform offers different suggestions at each stage of automation, allowing the developers to unlock creativity, innovate at scale, and achieve the critical path to automation.
- Responsible AI: Agentic AI platforms are built using guard rails, focusing on ethical AI implementations. The people-process-technology integration achieved thus brings along unprecedented gains through the deployment of Responsible AI.
- Return-on-Investment (RoI): Agentic AI leverages existing automation capabilities and investments to proactively identify issues even as they occur, mitigate the issue, and achieve the targeted goals. Faster turnaround and the resulting increase in customer satisfaction ensures rapid RoI.
Important use cases for Agentic AI
- Customer Support: It helps human agents instantly retrieve data. It also provides accurate suggestions for cross-selling and up-selling.
- Workplace transformation: Agentic AI leverages enterprise automation estate to give it an autonomous fillip within the purview of Responsible AI. It hyper-scales business processes in a secure environment and augments the human agent capabilities.
- Investment ventures: Agentic AI helps FDIs, DIIs, and Fund House Investors to analyze the financial statements of prospective investment ventures at scale to find the best-of-the-breed investment options.
- Application development: Agentic AI enables citizen developers to develop applications at an exponentially accelerated pace.
- Process diagnosis and optimization: Based on the goals, Agentic AI traces the most critical path or shortest path to automation. It also identifies the bottlenecks on specific workflow paths for process optimization.
- Complex and high-speed data set analysis: It helps analyze massive data sets, such as data related to Internet-of-Things (IoT), sensors, and climatic change, to identify patterns and outliers for quick redressal.
- Instant data retrieval: It helps retrieve documents from huge repositories using inadequate or misspelled search strings.
Simply put
AI-driven technologies, such as Agentic AI, use CUIs to automate processes and intelligently orchestrate the business landscape. The automation achieved at speed and scale is the harbinger of unprecedented productivity and efficiency gains. As a result, the benefits of engaging these AI-driven automation technologies far surpass the challenges.
