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From Chatbots to Autonomous Agents
When the first chatbots entered enterprise practice a few years ago, they primarily served as interactive FAQ — answering questions but not taking independent action. Today's agentic AI represents a qualitatively different category. These systems not only understand commands but also autonomously break down tasks, call external APIs, adjust sequences of steps based on interim results, and retain context for future interactions.
According to Trend Hunter, this shift accelerated in mid-2025 when Amazon Web Services introduced a suite of agentic AI tools at the AWS Summit focused on automating complex business processes. Agents could perform tasks across multiple applications, react to changes, and make autonomous decisions with minimal human intervention. This was a signal that the market is moving from assistive tools to full-fledged digital colleagues.
Amazon Bedrock Agents: Multi-Agent Orchestration for Enterprise
Amazon expanded its vision through the Amazon Bedrock Agents service. The platform allows developers to build agents that leverage foundation models, corporate APIs, and internal data sources to solve multi-step tasks. A key innovation is multi-agent collaboration — multiple specialized agents cooperate under the supervision of a parent agent that breaks down complex processes into smaller, more manageable steps.
Other significant features include memory retention for task continuity across interactions, Retrieval Augmented Generation (RAG) for accurate responses from internal databases, and code interpretation for automating data analysis and visualization. Amazon also introduced Bedrock AgentCore, an open-source framework for securely deploying agents in any environment.
In terms of pricing, Bedrock is built on a consumption model: organizations pay for input and output tokens according to the model used, with prices ranging roughly from 0.0008 USD to 0.02 USD per 1000 tokens. For Czech companies, it is relevant that AWS operates European regions in Frankfurt and Ireland, which facilitates GDPR compliance. However, direct Czech localization of agents remains rather the exception — primary language support is English.
Microsoft Foundry Agent Service: Agents Within the Office Ecosystem
Microsoft responded with the Foundry Agent Service, which is part of the broader Microsoft Foundry platform. Unlike competitors, it emphasizes deep integration with existing enterprise tools — particularly Microsoft 365, Teams, SharePoint, and Azure Logic Apps. Developers can create multi-agent workflows with more than 1400 ready-made connectors.
One of the most prominent advantages is Entra Agent ID — each agent receives its own identity within Active Directory, enabling control over its access rights, activity auditing, and application of security policies just like for human users. The platform supports the Model Context Protocol (MCP) for secure connection with custom APIs and offers built-in memory for preserving organizational knowledge.
Microsoft offers flexible consumption pricing based on the models and tools used. For non-programmers, Copilot Studio is available from approximately 200 USD per month per organization, while individual Copilot Pro subscriptions cost around 20 USD per month. For the Czech market, it is crucial that Microsoft provides full Czech language support within Copilot and Microsoft 365 services.
Anthropic and Financial Agents: Claude in Action in Banking
While Amazon and Microsoft build general platforms, Anthropic focuses on vertical solutions. In May 2026, it introduced ten ready-made agent templates for the financial sector, covering tasks from creating pitchbooks through KYC screening to closing monthly accounting operations. The templates are available as plugins for Claude Cowork and Claude Code, or as cookbooks for Claude Managed Agents.
Anthropic simultaneously expanded integration with Microsoft Office — Claude now works directly in Excel, PowerPoint, Word, and soon in Outlook. Thanks to this, a financial analyst can launch a model in Excel and continue seamlessly in a PowerPoint presentation without losing context. A significant competitive advantage is support for the Czech market: Claude is available in the Czech Republic, with paid plans starting at 30 USD per user per month (Team plan), while the Enterprise variant is available upon request.
On the Vals AI Finance Agent benchmark, the Claude Opus 4.7 model achieved a score of 64.37%, currently placing it at the top in the area of financial agent tasks.
Google and Other Players: Vertex AI Agent Builder
Google concentrates its response into Vertex AI Agent Builder, which allows creating agents using Gemini models. The platform primarily offers strong search and RAG capabilities built on Google Search and enterprise data sources. Pricewise, Vertex AI costs approximately 0.0018 USD per 1000 tokens for the Gemini 2.5 Flash model, and is available in EU regions including Western Europe.
Practical Impact for Czech Companies
For Czech businesses — especially medium-sized and larger ones — agentic AI platforms bring several concrete opportunities. First is the acceleration of internal processes: agents can be deployed on repetitive administrative tasks such as invoice processing, contract compliance checks, or report preparation. Second is the reduction of errors during manual data transfer between systems. Third is scalability: once created, an agent can serve multiple departments without the need to increase staff.
On the risk side stands the EU AI Act, which from August 2026 introduces stricter rules for high-risk AI systems. Companies deploying agents in areas such as creditworthiness assessment or legal analysis will need to demonstrate transparency, auditability, and human oversight. The recommendation is to start with low-risk use cases (for example, internal reporting) and gradually expand the scope.
Technological availability is not a barrier — all three mentioned platforms are available in the EU. The challenge remains language localization and the internal readiness of Czech organizations to manage autonomous systems.
Conclusion
Agentic automation platforms represent the natural continuation of the journey that generative models began. While in 2023 it was about answering questions, in 2026 AI is already fulfilling entire workflows. For Czech companies, it is crucial not to underestimate either the preparation of internal data or the regulatory framework — but also not to miss the train that is already leaving the station.
Do I need to be a programmer to use agentic AI in a business?
Not necessarily. Microsoft Copilot Studio and some Amazon Bedrock Agents templates offer low-code or no-code interfaces where you assemble agents using pre-built blocks and natural language. However, for more complex integrations, it pays to have a development team or partner.
What is the difference between agentic AI and classic RPA (robotic process automation)?
RPA robots follow rigidly defined scripts and fail when the interface or data format changes. Agentic AI uses language models that can adapt the approach based on context, work with imprecise inputs, and independently decide on the next step. It's a similar difference as between a remotely controlled car and a car with an advanced driver assistant.
How is agentic AI regulated in the context of the EU AI Act?
The EU AI Act classifies some agent systems as high-risk, especially if they influence decisions about employment, credit, or public services. Companies must ensure transparency, human oversight, and auditability of decisions. For internal administrative agents (for example, reporting), however, a milder regime usually applies.
