AI success is a process, not a leap! Understand, improve, and secure AI

Last updated: 12.10.2026 07:40

AI agents work independently, provide information, and make decisions. However, companies must ensure that they operate in compliance with regulations and correctly.AI agents are taking on an increasing number of tasks and proving their worth, for example, in daily customer interactions. These autonomous software systems function as AI process agents and solve complex tasks without requiring human intervention. In doing so, they represent the brand. But what happens if something goes wrong? Unsupervised AI is not a solution—it’s a risk.

Avoid Black-Box AI Systems—Build Compliance into the Design

An AI agent without oversight is a black box that does not meet regulatory requirements. Deviations go undetected. This means there is no insight into the origin of responses, no evidence in the event of a dispute, no basis for improvements, and no transparent compliance.
That is why SMEs looking to implement an AI solution should design it to be compliant with the EU AI Act from the very beginning. The focus is always on protecting citizens and their fundamental rights. To meet this requirement, monitoring parameters must be considered, human checks must be planned, and the fundamental risks of AI must be analyzed.

An important issue here is protection against so-called prompt injection, a cyberattack method in which malicious or manipulated commands are injected into an AI’s input (prompts). Another requirement is documentation, so that the AI’s operations are transparent and traceable. Companies must be able to examine how the algorithms work, the system’s architecture, and the training data used in order to identify discrimination or sources of error. Detailed documentation therefore also includes the technical specifications necessary to demonstrate that developers have systematically addressed the potential risks of the AI system.

Human Oversight

To ensure that AI agents operate transparently and in compliance with regulations, so-called human oversight is required. In practice, this can be implemented using solutions such as VIER Human-in-the-Loop. To do this, points in the process are defined where the AI agent must seek clarification, terminate the process, or hand it over to an employee. This should occur, for example, when decisions are critical and/or data is sensitive, when legal or financial risks arise, or when exceptions occur that cannot be clearly classified.

In practice, this can mean that AI processes 80 to 90 percent of requests independently. If a process deviates from the pattern, it is automatically handed over to an employee—along with a summary of the context and a recommendation for the next action.
Human oversight, or “human-in-the-loop,” is thus a central component of modern AI architectures, combining automation with human expertise. This not only ensures greater security and compliance but also continuously improves the quality of the service provided. The collaboration between humans and AI leads to fast, precise, empathetic, and thus customer-friendly solutions.

With VIER AI Studio, a low-code platform, companies can intuitively create their own AI-powered agents for customer service and internal knowledge management and operate them in compliance with regulations. It enables the automation of dialogs across various channels such as phone, chat, WhatsApp, and email. Every conversation is fully logged in the Studio, ensuring logging and traceability in accordance with the EU AI Act. Escalation paths and manual interventions can be configured for human oversight. Real-time dashboards and anomaly detection ensure security. AI labeling and guardrails—which serve as safety measures for AI solutions—are integrated into AI Studio and provide transparency for customers. Finally, evaluation, alerts, prompt optimization, and audit logs ensure reliable risk management. VIER AI Studio is designed with data protection and GDPR compliance in mind, is hosted in Germany, and integrates seamlessly with existing systems, such as CRM or ERP software. As a result, this solution also contributes to European data sovereignty and reduces dependence on U.S. providers.

Start Small, Then Grow

A pragmatic and sufficiently secure AI approach for small and medium-sized businesses is to start with a clear, small use case, thereby laying the foundation for tomorrow’s AI strategy. At the same time, protective measures are gradually refined as AI systems grow. This also includes protection against so-called “shadow AI”—that is, the unauthorized use of AI solutions by employees.
To ensure AI is operated securely, AI expertise within the company should also be enhanced through training and the establishment of binding rules. For the platforms used, AI transparency and clear documentation are key prerequisites for compliance and trust—and, if a high-risk system is operated, also for CE marking and legal market access in the EU.

The four risk classes of AI systems according to the EU AI Act

• Unacceptable risks/Highest risk level: These include, for example, systems that use manipulative or deceptive techniques, biometrically categorize people based on sensitive characteristics such as origin, religious or political beliefs, detect emotions in the workplace or in educational institutions (except for medical or security reasons), or engage in social scoring. Such AI systems are prohibited in the EU.

• High risks: AI systems used in areas such as critical infrastructure, education, human resources, or law enforcement. They are subject to strict requirements regarding risk assessment, documentation, and human oversight.

• Limited risks: AI systems that interact directly with people or generate content such as text, audio, images, or video. A transparency requirement applies here: Users must know that they are interacting with an AI and be able to decide whether to continue. Companies should therefore enable a seamless transition between a bot and a human employee so that customers do not abandon the interaction. This includes AI process agents that operate around the clock in a service hotline, for example, and are based on Large Language Models (LLMs). Furthermore, the underlying general-purpose AI models are subject to specific obligations under the EU AI Act—such as those regarding technical documentation and copyright—which apply regardless of these four risk levels.

• Minimal Risks: These are AI systems that pose virtually no threat to users’ safety or fundamental rights. Examples include spam filters, spell checkers, photo filters, route planners, and many others. There are no specific requirements for these AI systems. However, they must comply with other requirements, such as copyright laws and anti-discrimination regulations.