A question of trust in AI

Imagine you're running a big company. You make decisions every day — from inventory management to customer service to strategic decisions. Suddenly, you have access to technology that can make decisions faster and more precisely than an entire team of experts: Generative Artificial Intelligence (Gen AI).

Sounds tempting, doesn't it?

An example: AI analyses complex amounts of data and suggests drastically increasing the production volume of a specific product. As a manager, you are now asking yourself a few important questions: Can I trust this recommendation? What is it based on? Would I have made the same decision?

Gen AI brings enormous potential, but also significant challenges. Unlike traditional systems, its decisions are often the result of complex, multi-layered calculations, which are not always easy for humans to understand. This creates uncertainty: AI decisions can feel like they come “out of nowhere.” It’s hard to fully grasp its recommendations—a leap into the unknown.

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Trust in AI: A key issue

The introduction of Gen AI means more than just a technological shift. It entails profound cultural and organizational changes. A practical example illustrates this: A large retail company implemented AI that optimized inventory levels in real time. Everything went smoothly at first, but then the AI suddenly recommended massively reducing stocks of certain products. For human planners, this seemed illogical.

Her gut instinct said “no.”

However, after intensive analysis, it turned out that the AI had identified seasonal trends and upcoming marketing campaigns that had eluded human planners. The recommendation was therefore correct. What would you have done?

The balance between trust and control

In order to build trust in AI systems, a step-by-step approach is crucial. Start with small, well-defined projects where AI performs simple tasks. In this way, employees can gradually understand the way they work and develop trust without being overwhelmed by the full complexity. The gradual integration leads to visible successes and reduces resistance.

5 success factors for trustworthy and accurate AI decisions

1. Understanding data sources and algorithms

Make sure that data sources are reliable and up to date. Regular audits of data quality and algorithms help to avoid distortions and errors.

2nd Transparency and traceability

Encourage transparent communication about how AI works Use Explainable AI (XAI) to make the decision-making process easier to understand and build trust.

3rd Iterative implementation

Introduce AI gradually. Start with pilot projects to identify successes and weaknesses early on and make adjustments.

4th Collaboration between humans and AI

Rely on hybrid decision-making processes. Human expertise should continue to play a central role in achieving the best results.

5th Continuous education and change management

Train your employees regularly so they can understand and use the technology. Workshops and hands-on training promote trust and acceptance.

Conclusion: Successful introduction of AI as a change management process

The hype surrounding Gen AI shows that companies have recognized the benefits of this technology. But implementation isn't just a technical challenge—it requires fundamental cultural change. Success depends largely on how well the organization manages this change. Training, transparent communication, and gradual implementation are crucial to develop trust in AI capabilities. This is the only way the technology can develop its full potential and successfully support companies in the long term.

Are we ready to actively shape this change?

The journey has only just begun — and it is up to us to make it a success.