Overview

Agentic process automation leverages autonomous agents to manage and execute complex workflows in an intelligent manner, reducing the need for human intervention.

These agents are typically powered by advanced machine learning models such as large language models (LLMs) and can integrate with enterprise systems through APIs, enabling seamless communication between different software tools and platforms.

Key aspects

By 2026, agentic process automation is expected to become a cornerstone of modern business operations, facilitating not only routine task management but also decision-making processes that require nuanced understanding and contextual awareness.

In this timeframe, companies like S4B will likely offer solutions built on frameworks such as Dapr (Distributed Application Runtime) or Microsoft’s Azure Digital Twins to create intelligent agents capable of handling sophisticated enterprise workflows across various industries.