Agentic AI: How companies can now benefit from autonomous AI agents

Artificial intelligence is no longer a topic for the future, but is already influencing how companies work, optimize processes and interact with customers. The development of agentic AI, i.e. autonomous, intelligent AI agents that not only provide information, but can also make active decisions and execute business processes independently, is particularly exciting.

In the CorpInSight podcast, we spoke to Luka Bekavac about precisely this topic. Luka is an expert in AI-supported systems and recommender technologies and explains how Agentic AI works, what challenges there are and why companies should act now in order to remain competitive in the long term.

If you want to delve deeper into the topic, you can listen to the first episode of our podcast "CorpInSight" with Luka Bekavac now! 🎙️ Listen now‍

From chatbots to autonomous agents: A paradigm shift

Until now, companies have often been frustrated by traditional chatbots, which only provide ready-made answers and quickly reach their limits when dealing with more complex queries. Anyone who has ever tried to change a simple order or get technical help via a poorly programmed chatbot knows the problem: the systems are inflexible, provide incorrect or incomplete information and ultimately lead back to a human customer advisor.

But with agentic AI, this picture is changing fundamentally. Instead of just providing passive answers, these systems act like a digital employee that not only processes information, but can also directly access databases, control processes and make decisions.

Luka explains in the podcast that the new large language models now have much larger context windows. This means that they can process more data at once, which makes them much more precise and intelligent. Previous AI models, for example, could only search a limited number of documents or text sources before generating an answer. Now, however, it is possible to analyze hundreds of documents in real time and provide accurate answers based on this.

Concrete use cases: Where Agentic AI is already changing companies

The most exciting question for decision-makers is of course: Where can my company benefit from Agentic AI in concrete terms?

In the podcast, Luka mentions some exciting use cases that are already being used in practice today:

1️⃣ Automation of customer service: Companies can use Agentic AI to automatically process recurring customer inquiries about delivery status, returns or product information. Instead of an employee manually checking each inquiry, an intelligent agent can access the ERP or CRM system directly and provide the right answer.

2️⃣ Internal knowledge management systems: Many companies have a large amount of unstructured data spread across various documents, emails or internal wiki pages. With Agentic AI, this knowledge can be centralized and made efficiently searchable so that employees can quickly access the information they need.

3️⃣ Process automation in logistics: In complex supply chains, Agentic AI can automatically check the status of orders, manage stock levels in real time and even optimize delivery dates.

4️⃣ Data analysis and decision-making: Agentic AI can not only analyze existing data, but also make suggestions for business decisions by recognizing patterns and making predictions based on historical data.

An example that Luka mentions in the podcast shows how powerful these systems already are: He used an AI to extract a complete list of books from a bookshelf in a matter of seconds - just by watching a short video. This shows that AI no longer only understands text, but can also analyze images, videos and even audio files.

Challenges: Why companies should act now

Despite all the advantages, there are also challenges when introducing Agentic AI. Security and data protection play a crucial role here. After all, if an AI agent accesses databases independently and makes changes, it must be precisely defined what powers it has and where human intervention is required.

Luka explains that companies should define clear rules for this - similar to the access rights of employees:

🔒 Which data can the AI only read and which can it change?

🔒 Which decisions can the AI make independently and which need to be checked by a human?

🔒 How can AI-generated results be checked for accuracy and traceability?

In particular, the risk of AI hallucinations - i.e. the invention of false information - should not be underestimated. The best companies therefore use a combination of AI-supported agents and human control (human-in-the-loop) to avoid errors.

What does the future of Agentic AI look like?

It is clear to Luka Bekavac that Agentic AI has the potential to change entire industries. Large technology companies such as Google and OpenAI are already relying heavily on agent-based systems.

"The age of agents has arrived" - this is how Google describes the current development. And indeed, more and more companies are beginning to integrate agentic AI into their processes.

In the future, the technology will be even more closely integrated with existing company systems. This means that AI agents will not only answer queries, but will also be directly embedded in ERP, CRM and accounting systems.

Conclusion: Why companies should not wait any longer

The introduction of Agentic AI is no longer a future scenario - it is already happening now. Companies that embrace this technology early on will benefit in the long term. They can reduce costs, speed up processes and increase customer satisfaction.

But it's not just about efficiency. It's also about staying competitive. Companies that ignore Agentic AI run the risk of being overtaken by more agile competitors.

Now is therefore the right time for decision-makers to get to grips with Agentic AI and launch their first pilot projects. After all, those who invest in automation today will have a clear market advantage in the coming years.

📢 Want to find out more? Then listen to the full podcast episode with Luka Bekavac!

Listen now

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