AI and Ethics: Can We Truly Trust Artificial Intelligence?

What exactly is agent-based AI?

Agent-based AI represents a new generation of artificial intelligence that can operate autonomously to achieve specific goals with minimal human supervision.

A practical example: I asked an AI agent to “schedule a meeting with someone from Teriagen for AI support”. The agent identified our company online, visited the website, located the appointment booking page, chose an available slot, and arranged a meeting with one of my associates in seconds.

These AI agents can understand their environment, reason, plan, and execute complex, dynamic actions in real-time, interact through APIs or software/web interfaces, and sometimes even coordinate with other AI agents.

What are the benefits of integrating AI agents into a company’s processes?

The ability to operate autonomously is revolutionizing business productivity and responsiveness. AI agents can handle entire complex workflows, from anomaly detection to customer service ticket resolution, freeing up employees for higher-value tasks.

Agent-based AI also offers significant speed and adaptability: it reduces response times, learns continuously, anticipates incidents, personalizes responses, and alleviates the burden of repetitive or critical tasks.

It transforms incident management and decision-making, with a proactive responsiveness that is inherent in its operation.

Companies need to stay updated with this trend to keep up with competitors: Gartner predicts that by 2028, up to 15% of daily professional decisions will be made autonomously by agent-based AI systems.

What are the risks of allowing artificial intelligence to act autonomously?

While agent-based AI is a significant technological advancement, the role of humans and the quality of data are crucial to frame and secure its use. Its autonomy is a concern that indeed requires special attention.

The real challenge is to maximize its reliability through transparent design, clear governance, and robust audit mechanisms that ensure trust.

Fortunately, agent-based AI is gradually overcoming limitations related to biases or imperfect data through rigorous data quality practices combined with human review processes, moving towards a more resilient learning model.

The issue of opaque systems is also increasingly addressed, and there are now tangible solutions: explainability approaches (XAI), for instance, help make sense of the AI’s decisions.

What are the ethical and responsibility challenges posed by this technology?

Governance becomes imperative, and the decision to adopt AI agents must not be made impulsively but with proper support. “Human-in-the-loop” supervision processes are essential to ensure that AI agents remain aligned with the company’s goals and values.

Transparency, decision traceability, and auditability must be the pillars of any integration initiative.

On the regulatory front, companies must ensure compliance with the GDPR or the AI Act, not to mention the French legal framework (such as labor laws). To prevent misuse, an ethical strategy cannot be left to chance; it requires cross-departmental committees involving business, legal, data science, and security experts.

What about cybersecurity?

In cybersecurity, agent-based AI is primarily recognized for its ability to anticipate, detect threats, and respond immediately, stopping attacks before they spread.

However, while it serves as a defense tool, agent-based AI can also become an offensive weapon if misused, for example by automating phishing or identity theft on a large scale.

This is why establishing isolated environments (sandbox), human validations, and monitoring interactions between agents is essential.

Can we truly trust agent-based AI, in your opinion?

When discussing AI in general, which perfectly applies to agent-based AI, I often refer to the analogy of a screwdriver: in the hands of a skilled mechanic, it’s an extremely effective and reassuring tool, but in the hands of a criminal, it’s a lot more worrisome!

So, my answer is both “yes” and “no.”

Yes, because agent-based AI offers unique power and responsiveness. No, if human governance lacks rigor: trust cannot be separated from protective measures, strong supervision, and constant monitoring.

What protections need to be implemented to safely integrate agent-based AI?

The approach should be gradual and strategic: assess the stakes and risks (regulatory, social, environmental, etc.), start with targeted pilots, measure the effects, and refine the system based on feedback. All automation must remain under control, with traceability, robust security (encryption, granular access, learning audits), and continuous human supervision.

Your final word?

Agent-based AI heralds an era where technological autonomy must be matched with human rigor—this is its true potential. By combining ethics, explainability, and security, we can foster a form of intelligence that acts, reasons, and creates value… while remaining under control!