What is agentic AI — and why companies want it
Agentic artificial intelligence (in Czech agentní AI) represents a fundamental shift from reactive AI systems to proactive ones. While a classic chatbot answers questions and an RPA robot blindly repeats a prescribed workflow, an AI agent perceives its environment, evaluates context, plans steps, and executes them autonomously — and when it encounters a problem, it can self-correct.
Happiest Minds, an Indian technology company with over 6,500 experts, offers its own Enterprise AI Productivity framework — in a nutshell, it's a maturity model for enterprise AI that describes three levels: from manual engineering through the "AI assists, human decides" phase to agentic engineering, where agents plan, execute, and self-correct their work while humans set only the guardrails. According to their data, the agentic approach can reduce time to market by 40–60% and increase developer productivity by 30–50%.
The key difference from traditional automation is the ability to adapt. An RPA robot fails as soon as a website changes its layout. Agentic AI with a large language model under the hood handles unpredictable situations — it recognizes what changed and adjusts its approach.
How agentic AI works in practice
Under the hood sit large language models (LLMs) — GPT, Claude, Gemini — complemented by planning logic, memory, tool interfaces (API calls, browser, calculator), and an orchestration layer. The agent receives a goal, breaks it down into sub-steps, decides which tools to use, performs the action, and evaluates the result.
Real-world practical examples:
- TD Bank deployed agentic AI for mortgage loan approvals — the process shrank from 15 hours to 3 minutes. The agent independently verifies documents, checks creditworthiness, and prepares decisions.
- IRS (the US tax authority) uses Salesforce Agentforce for taxpayer support — agents handle inquiries 24/7 without human intervention.
- Replit, Cursor, and Claude Code allow developers to enter a task in natural language and the agent writes the code, tests it, and deploys it on its own.
- ServiceNow deploys AI Control Tower — a central overview of all enterprise agents with the ability for immediate human intervention.
For the average business user, this means the end of routine data transfer between systems, filling out forms, or waiting for "someone from IT." Agentic AI can take over employee onboarding, travel expense management, compliance monitoring, or first-level customer support.
Key market players in 2026
Salesforce Agentforce
Currently the most comprehensive agentic platform on the market. Includes Agent Builder (low-code agent creation), Atlas Reasoning Engine for logical reasoning, and AgentExchange — a marketplace of ready-made agents. Supports MCP (Model Context Protocol) and A2A (Agent-to-Agent) protocols. G2 ranks it first in the Agentic AI category.
Google Gemini Enterprise Agent Platform
Built on Google Cloud infrastructure with access to more than 200 models including Gemini 3.5. Offers Agent Development Kit (ADK), Agent Studio for visual design, and the Antigravity desktop application. Its strong suit is scalability and integration with Google Workspace.
ServiceNow AI Agents
Primarily focused on IT service management and enterprise workflows. AI Agent Studio enables agent creation in natural language, AI Agent Orchestrator coordinates them across the company. The "Autonomous Workforce" concept treats agents as full-fledged team members.
Microsoft Copilot
Agentic capabilities are integrated directly into the Microsoft 365 and Windows 11 ecosystem. Copilot Studio enables the creation of custom agents, and Microsoft 2026 Release Wave 1 brought agentic workflows to Dynamics 365, Power Platform, and office applications. For Czech companies on the Microsoft stack, this is the most natural entry point.
Happiest Minds Enterprise AI Productivity
More of a consulting framework and implementation service than a product. Happiest Minds builds custom agentic solutions using models from OpenAI, Anthropic, and open-source. Their approach is model-agnostic and emphasizes SOC2, GDPR, and HIPAA compliance. For European companies, it can be an interesting alternative to large platforms if they are looking for tailor-made solutions.
How much agentic AI costs
Pricing models vary from platform to platform, but the common denominator is a consumption-based model — you pay for actions, conversations, or tokens, not an unlimited flat fee:
| Platform | Estimated price | Free tier |
|---|---|---|
| Salesforce Agentforce | $2/conversation, $500/100k Flex credits | Yes — Agentforce free in Salesforce Foundations |
| Google Gemini Enterprise | $0.0001/1000 characters, $0.03/pipeline run | $300 credits for new customers |
| Microsoft Copilot M365 | ~$30/user/month, Copilot Studio add-on | Limited — part of select M365 licenses |
| ServiceNow AI Agents | Enterprise licensing (on request) | No |
For a mid-sized company with 100 employees, deploying agentic AI can start at around tens of thousands of CZK per month, depending on the volume of automated tasks.
European and Czech context
Specific rules apply for Czech and European companies. The EU AI Act classifies autonomous agents based on deployment — if an agent makes decisions about loans, hiring, or healthcare, it falls into the high-risk category and is subject to strict regulation. Companies must maintain documentation, ensure human oversight, and demonstrate compliance.
GDPR further requires control over where and how data is processed. All major platforms (Salesforce, Google, Microsoft) offer European data regions, but companies should verify whether their specific configuration sends data outside the EU.
In the Czech Republic, agentic AI is still in its early stages. The CNB (Czech National Bank) is building its own AI center, several Czech startups are experimenting with AI agents for customer support, and Microsoft Copilot is available in Czech as well. However, what's missing for mass adoption are local system integrators with deep expertise in agentic technologies. Companies like Happiest Minds could theoretically serve the Czech market, but their primary scope is India and global clients — for smaller Czech businesses, it will be more practical to use platforms from Microsoft or Salesforce with local partners.
What to watch out for
Not everything labeled "agentic AI" today actually is one. Gartner warns against "agent washing" — rebranding existing chatbots and RPA tools with a new label. A true AI agent must be able to plan, decide, and adapt on its own.
Other risks include uncontrollable costs (Microsoft had to suspend Claude Code registrations, companies like Uber exhausted their AI budget in 4 months) and security — "agentjacking" attacks can exploit autonomous agents for their own purposes. Last but not least: return on investment is not yet broadly proven — as early as November 2025, the Wall Street Journal noted that few companies with deployed agents have actually achieved measurable ROI.
Can agentic AI be used in Czech?
Yes — large language models (GPT-5.5, Claude, Gemini) handle Czech at a very good level. However, practical availability depends on the specific platform. Microsoft Copilot supports Czech natively within M365. Salesforce Agentforce and ServiceNow primarily target English, but the underlying LLM models understand Czech — it is a matter of configuration whether the end agent will communicate fluently in Czech. For Czech companies, we recommend requesting a demonstration directly in Czech from the vendor before signing a contract.
Will agentic AI replace human employees?
In the coming years, it will more likely transform the nature of work rather than replace people wholesale. Agents excel at routine, repeatable tasks — sorting requests, filling out forms, initial customer support. People are shifting to activities requiring creativity, strategic thinking, and interpersonal communication. According to experience from TD Bank, agents didn't lead to layoffs — instead, employees were moved to more complex cases. Mortgage approvals accelerated, but the final decision is still made by a human.
How to get started with agentic AI in a smaller Czech company?
The simplest entry point is Microsoft Copilot (if you already use M365) — you get basic agents in a familiar environment. A second path is low-cost experimentation with tools like n8n, Make, or LangChain to build a simple internal agent. A third option is reaching out to a local integrator with Salesforce or ServiceNow experience — but expect an investment in the range of hundreds of thousands of CZK. Start with a small pilot project on a single specific process (e.g., automatic sorting of incoming emails) and evaluate the results before scaling.
