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5 min read • Apr 23, 2025
For more than a decade, Robotic and Digital Process Automation (RPA / DPA) have helped organizations automate repetitive, rule-based tasks. However, automation is evolving — and AI agents are leading the way. As intelligent automation matures, many wonder: What’s the real difference between RPA, Gen AI, Agentic AI — and where does Agentic Process Automation come in?
To help distinguish between the different levels of automation, let’s summarize the facts:
Robotic & Digital Process Automation automates structured, repetitive, and rule-based tasks using scripts or workflows. While DPA represents an evolution of RPA—shifting from UI-based automation to API- and connector-based integration—both are well-suited for high-volume, rule-based processes such as invoice matching or form entries. These technologies operate best in environments with minimal variation and limited unstructured input.
GenaI leverages large language models (LLMs) to generate natural language, code, images, and more based on input prompts. It excels at creating content and interpreting unstructured data (e.g., summarizing documents, drafting emails). However, GenAI alone lacks process awareness, or the ability to interact with enterprise systems autonomously — it is typically a stateless content generator, not an executor.
Agentic Process Automation combines the interpretive power of GenAI with traditional automation tools (RPA, DPA, and AI services) to enable orchestration of workflows based on predefined goals. These custom-made systems can analyze unstructured inputs, invoke tools dynamically, and apply contextual logic to guide processes forward. Built on platforms like Microsoft Power Platform, Copilot Studio, or UiPath, these agent-like workflows introduce goal-oriented reasoning and intelligent decision-making into automation. They offer flexibility in handling variation and user interaction but remain bounded by the structure and scope of their underlying workflows.
The most advanced form of intelligent automation, agentic AI systems are designed to be fully autonomous and aim to manage almost any digital task. They integrate generative reasoning, multi-step planning, memory, tool/API invocation, and feedback loops to pursue and adapt to high-level goals. These agents can independently plan and execute complex workflows across systems. However, the technology is still emerging and requires careful design, governance, and alignment with business objectives to be viable in enterprise environments.
Unlike RPA bots that follow predefined scripts and rigid workflows, the agentic approach introduces a higher degree of autonomy—enabling systems to handle deviations from the “happy path” and even adapt to new or unforeseen scenarios. However, this flexibility comes with a trade-off: increased autonomy often leads to reduced determinism. Enterprises seeking solutions with consistent and reliable outcomes should carefully assess for each process their tolerance for variability and establish clear thresholds for agentic system usage.
At BE-terna, we support companies on their intelligent automation journey through strategic advisory and tailored solutions. We help organizations identify high-impact use cases, implement AI-driven tools where they create the most value, and ensure seamless integration with existing processes and systems. By thoughtfully combining various automation approaches, we deliver practical, scalable, and sustainable outcomes. Here are some examples of Agentic solutions we've implemented:
At BE-terna we don’t just deliver and implement automation tools. We connect strategy, processes, and AI to drive real business value. Our approach is holistic, combining technical expertise with a deep understanding of organizational needs.
Through our modular AI consultancy program, companies can start with focused pilot projects and gradually expand to full-scale implementations. We provide comprehensive, end-to-end services, beginning with unified data solutions suitable for organizations of all sizes and maturity levels.
Beyond implementation, we support change enablement by helping both IT and business teams adopt and integrate new technologies effectively — ensuring that automation becomes a sustainable part of your operations.
See these use cases in action and learn how to start your journey. We’ll walk you through real projects, lessons learned, and how to succeed with AI agents in your organization.
*This webinar will be held in German
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