What is agentic AI and why is it different from ChatGPT

ChatGPT, Claude, or Gemini are fantastic at answering questions, writing texts, or generating code. But they still need a human to give them a specific prompt and decide what to do with the output. Agentic AI — in English agentic AI — turns this model upside down.

Agentic systems can set their own goals, plan steps, evaluate available options, and take action with minimal human oversight. A classic example: while standard AI needs the instruction "order 500 kg of cocoa at the best price," agentic AI itself analyzes market prices, supplier availability, logistics costs, and risks associated with delivery — and places the order.

Put simply: agentic AI has its own initiative. And that is what makes it so interesting for large companies, where every second and every percentage of efficiency counts.

Nestlé: Over 100,000 employees using AI in their daily routine

The world's largest food company, the Swiss conglomerate Nestlé, is betting big on agentic AI. According to information published by FoodNavigator, more than 100,000 employees worldwide regularly use AI tools. And agentic elements are gradually being woven into everyday processes.

Personalized productivity and HR support

Nestlé is testing agentic AI for employee self-service in the human resources area. An employee can thus interactively resolve common administrative matters — from vacation requests through benefits to internal regulations — without waiting for a response from a colleague. In more complex cases, a human naturally steps in, but routine queries are handled autonomously by AI. The pilot project is running in several countries and the company is gradually expanding it.

Finance: Better capital and risk decisions

Nestlé's agentic systems are not limited to HR. In the finance department, they help managers improve decision-making related to working capital, risk analysis, and investment allocation. AI gathers data from various sources, creates consistent reports, and offers a unified view of the situation that would take a human analyst hours or days to compile. Another advantage is easy scalability — the same model can be deployed across different divisions and markets.

Sales teams without routine

Nestlé sales representatives spend a significant part of their time on administration: filling out reports, updating CRM systems, preparing presentations. Agentic AI can automate repetitive tasks and free up time for what matters most — communication with customers and business development. That is the goal: technology does not sideline people, but gives them space to do work that has real impact.

Danone: Less waste, lower energy consumption

French dairy giant Danone, in turn, has bet on agentic AI in production and sustainability. According to FoodNavigator, the company is piloting autonomous systems across several operations with the aim of increasing productivity while reducing its environmental footprint.

Real-time production data analysis

Danone deploys agentic AI to analyze production data, simulate different scenarios, and identify areas where operations can be improved. The system can, for example, detect inefficient machine usage, suggest optimization of production lines, or alert to deviations that could lead to waste. All under human oversight and with set governance rules — Danone emphasizes that decisions on final changes remain in human hands.

Sustainability as a business goal

For Danone, agentic AI is not just about speed. The company has committed to ambitious sustainability goals and the technology is helping it fulfill them through concrete actions: reducing waste, optimizing energy consumption, and improving overall efficiency. In the context of rising energy prices and stricter European regulations, this is not just an ethical gesture but a business necessity.

What does this mean for the Czech Republic and Europe?

Both mentioned companies also operate in the Czech Republic. Nestlé runs factories here — for example in Znojmo and Holešov — and Danone has its representation and distribution network. It is therefore likely that agentic AI pilot projects will in some form reach Czech operations as well, albeit gradually and within global transformation strategies.

The European context adds another layer of complexity: the EU AI Act, which entered into force in 2024 and is being gradually implemented, classifies some AI uses in the food industry as high-risk. This concerns especially systems affecting food safety or consumer health. Agentic AI in finance, HR, or logistics falls more into the medium-risk category, but companies must comply with rules on transparency, human oversight, and accountability. Czech branches of multinational corporations will therefore have to align global AI strategies with local regulatory requirements.

For smaller Czech food companies, the news about Nestlé and Danone is primarily a signal of where the industry is heading. Technologies that giants are testing today will become available within a few years in the form of cloud solutions from providers like Microsoft, Google, or specialized suppliers. Companies that start with data and process digitization now will later have an advantage in faster adoption of agentic systems.

Where are the limits?

Agentic AI is not a cure-all. Both conglomerates emphasize that systems operate with human oversight and governance — especially in areas involving finance, food safety, or personnel decisions. AI can suggest, analyze, and automate, but final responsibility remains with humans.

Technical limits are also evident: agentic systems need quality data, clearly defined rules, and a secure IT environment. Without that, there is a risk that "autonomous" decisions will lead to errors that a human would spot immediately. That is precisely why both Nestlé and Danone are talking about pilot projects, not full-scale deployment across the entire corporation.

The future is autonomous — but cautious

Agentic AI represents a logical evolutionary step from chatbots and generative models to systems that truly "work" for you. Nestlé and Danone show that the food industry — traditionally conservative and cautious about innovations — is beginning to actively exploit this potential. For now, it is more about productivity, sustainability, and better decision-making than full automation, but the direction is clear.

For Czech readers and companies, it is crucial to monitor how these technologies evolve, what tools will be available in Czech, and how they will be affected by European regulation. And above all — that AI is no longer just about writing emails, but about a real change in how entire industries function.