The End of the Era of Fixed Scripts: The Difference Between Automation and Agentic AI

Most of us are already used to RPA (Robotic Process Automation). These are tools that can automate routine office tasks, such as transcribing data from PDF to Excel. However, it is still "automation" – the process is rigid. If the invoice format changes, the automated script will fail.

Agentic AI (agentic artificial intelligence) works on a completely different principle. Instead of a precise list of steps, the agent receives a goal. For example: "Find the cheapest flight to London, book it if it's under 3000 CZK, and send the confirmation to my calendar." The agent must plan the steps itself: open a browser, compare prices, perform the transaction, and communicate with other software. If it encounters an error, it doesn't stop, but tries to find an alternative path.

This shift, discussed by The Cryptonomist for example, changes the definition of software. Software will no longer be just a tool that we control, but a partner that collaborates with us.

How Does an Agent's "Brain" Work? Key Components

For a model like GPT-4o, Claude 3.5 Sonnet, or newer models in 2026 to function as an agent, it must possess three basic capabilities:

• Planning: The ability to break down a complex task into smaller, manageable subtasks. Modern models use techniques like Chain-of-Thought to first "think through" the process.
• Tool Use: The agent must have access to external APIs, a browser, or a calculator. Without the ability to "step out" of the text window, the model is merely a clever encyclopedist, not an agent.
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• Memory: Short-term memory allows the agent to maintain the context of the current task, while long-term memory (often implemented via vector databases) enables the agent to learn from previous experiences within your company.

Performance Comparison: From Chatbot to Agent

When evaluating the capabilities of agentic AI, not only historical knowledge tests are used, but specific agentic benchmarks, such as SWE-bench (solving software bugs) or GAIA (general real-world tasks).

Practical Impact: What Does This Mean for You?

For Individuals and Freelancers

Imagine a personal assistant to whom you don't say "write an email," but "handle all my invoices for last month." The agent will download PDFs, check them against your accounting system, and notify you if there's a discrepancy. This frees up dozens of hours per month.

For Czech and European Companies

For the Czech technology sector and small and medium-sized enterprises (SMEs), Agentic AI represents a huge opportunity. Companies that don't have budgets for hundreds of administrative employees can scale their operations thanks to inexpensive agentic workflows. However, it is necessary to consider the EU AI Act. Agentic systems that can autonomously decide on user data will be subject to strict regulation in terms of transparency and security.

Availability in Czech: Most large models (OpenAI, Anthropic, Google) will already handle Czech at a level in 2026 that allows not only understanding but also generating natural text. For developers in the Czech Republic, it is crucial to build agents that can work with Czech grammar and local data formats.

Risks and Challenges

Autonomy brings risks. Hallucinations in agents are more dangerous than in chatbots. If a chatbot invents a fact, it's enough to correct it. If an agent invents a step in a purchasing process, a real financial loss can occur. Therefore, the development of so-called "Human-in-the-loop" mechanisms – systems where the agent must have key steps (like payment) approved by a human – is a critical topic.