AI Agents Much More Than A Digital Tool

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While apps follow a fixed pattern and AI apps continuously learn, AI agents take a decisive step further: they act completely autonomously, constantly adapt to new situations, and make strategic decisions without human intervention.

What sounded like science fiction just a few years ago is already a reality in German companies today: 93 percent are already using AI agents or preparing for their implementation (Source: Cloudera study). These intelligent systems can independently pursue objectives, learn from mistakes, and make autonomous decisions. So the question is no longer whether AI agents will change our working world. Instead, it's about how quickly this transformation will progress—and what companies need to prepare for.

From Rigid Apps to Learning Systems

To understand the scope of this development, it is worth looking back at conventional smartphone apps. These digital tools follow rigid programming structures and can only execute what developers have predetermined. Every new feature requires manual updates via app stores, every action waits for explicit user input. The weather app shows the weather, the calculator calculates, the notes app saves text—nothing more. Adapting to individual needs or workflows is practically impossible.

The first breakthrough was marked by AI apps that can continuously learn and adapt to new data. Instead of just reacting, they automate processes, provide recommendations, and understand natural language through sophisticated machine learning algorithms. In medicine, they assist with diagnoses through image analysis, in education, they create tailored learning plans, and in the automotive industry, they enable predictive maintenance. However, AI apps typically focus on clearly defined areas of tasks.

The Leap to Autonomous Agents

AI agents take it a step further: they act largely autonomously in many areas, pursue defined goals, and make decisions independently—without constant human intervention.

These systems think strategically: they assess situations, plan ahead, and adjust their tactics as needed. Like humans, they iteratively refine their decision-making abilities, making them particularly effective in unpredictable environments.

Potentials of AI Agents for Industrial Companies

AI agents open up significant potential for industrial companies in areas such as service and support. For instance, KUKA already uses AI agents combined with knowledge management systems to independently identify solutions. These agents work purposefully and leverage various tools to find the appropriate response. While it is not yet a fully comprehensive agentic AI, it demonstrates how such systems can be productively utilized. Agent-based systems, in particular, offer a significant lever for efficiency improvements for medium-sized companies.

The integration of AI agents into existing systems therefore requires careful planning and specific technical prerequisites. Crucial is their ability to collect, analyze, and act on data from the environment. At the same time, these systems must operate securely and transparently to build trust.

Humans Remain Indispensable

A key balancing act lies between autonomy and control. Mechanisms such as so-called guardrails prevent agents from acting uncontrollably, while ensuring their decisions remain transparent and verifiable. Methods like combining generative AI with symbolic approaches contribute to achieving reliable and trustworthy results.

For safety-critical or business-critical decisions, AI agents must rely on human expertise. Responsibility should always rest with humans, ensuring that agents act appropriately in sensitive areas. While AI agents can independently manage many processes, they must always operate within a controlled framework.

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