Transparency as a competitive advantage: How responsible AI strengthens customer trust

Artificial intelligence (AI) plays a central role in digital transformation and is a crucial factor for innovation and efficiency. Companies are increasingly using AI to optimise processes, make data-driven decisions and create personalised customer experiences.

The success of AI initiatives, however, depends on customer trust. Transparency is a key factor for long-term success and achieving a strong market position. In this article, we explain how companies can win the trust of their customers and secure their competitiveness through transparent and responsible AI systems.

Warum ist Transparenz bei KI unverzichtbar?

Laut einer McKinsey-Studie nutzen bereits 84% der europäischen Unternehmen eine KI-Technologie und 54% setzen auf Generative KI – ein Trend, der weiterwächst. Die Transparenz im Umgang mit KI ist nicht nur ein technisches Detail, sondern ein strategisches Element, das direkten Einfluss auf die Wettbewerbsfähigkeit eines Unternehmens hat.

Die Verbindung zwischen Offenheit, Vertrauen und Kundenbindung

Heutzutage erwartet die Kundschaft eine verständliche Erklärung darüber, wie neue Technologien funktionieren und welche Daten verwendet werden. Systeme, die nachvollziehbar und transparent sind, finden eine höhere Akzeptanz sowohl bei der Kundschaft als auch bei den Mitarbeitenden.

Ein praktisches Beispiel: Unternehmen, die KI-gestützte Chatbots im Kundenservice etablieren, gewinnen durch Transparenz über deren Funktionsweise das Vertrauen ihrer Kunden. Wenn ein Chatbot etwa erklärt, wie er Anfragen analysiert und beantwortet oder bei komplexen Themen an menschliche Mitarbeitende weiterleitet, fühlen sich Kunden besser informiert und wertgeschätzt. Diese Offenheit fördert nicht nur die Akzeptanz von KI-Systemen, sondern stärkt auch die Kundenzufriedenheit – ein entscheidender Vorteil in einer Zeit, in der Servicequalität ein wichtiger Wettbewerbsfaktor ist.

Risks posed by lack of transparency

• Loss of customers: When systems are perceived to be unfair or lacking in transparency, companies quickly lose customers. One example of this is allegations of discrimination in automated job application processes.
• Damage to the company’s image: Negative reports in the media about ethical or technical deficiencies have a lasting impact on the company’s public image.
• Legal consequences: Violations of regulations such as the revised Swiss Data Protection Act (revDSG), the GDPR (in relation to the EU) or the EU AI Act can lead to heavy fines and legal problems – this applies particularly to Swiss companies that provide services to the EU.

The advantages of responsible AI systems

• Competitive advantage: Companies that make their processes transparent set themselves apart from the competition.
• Building trust: Openness promotes trust among customers, employees and partners.
• Legal certainty: Clear and transparent systems facilitate compliance with legal requirements and minimise liability risks.

Strategies for creating transparent AI in the company

The establishment of transparent AI systems requires a comprehensive approach, which includes technical, organisational and communication measures. We have put together a number of practical strategies to help companies ensure transparency.

Establish governance structures

Solid governance is the cornerstone of transparent AI. Responsibilities must be clearly defined to ensure all AI processes are controlled and monitored.

• Roles and responsibilities: Determine who is responsible for the development, implementation and monitoring of AI systems.
• Ethical standards: Integrate ethical guidelines into your AI strategy to ensure fair and non-discriminatory decisions.

Recommendation: Use our free AI checklist to introduce your AI systems in a structured manner.

Promote transparent communication

Open and clear communication is essential for building trust among customers and employees.

• External communication: Explain clearly how your systems work and what data is used. For example, an insurance company could explain in detail how responsible AI helps with claims assessment.
• Internal communication: Keep your team regularly informed about the use of AI to build acceptance and avoid misunderstandings.

Tip: Deepen your knowledge of transparent AI with our practical webinars on generative AI to give you and your staff the best foundation for working with AI.

Use explainable models

Explainable Artificial Intelligence (XAI) makes the decision-making processes of algorithms comprehensible to users.

• Technological approaches: Tools like LIME (Local Interpretable Model-Agnostic Explanations) or SHAP (SHapley Additive exPlanations) help to visualize complex processes and present them in a comprehensible way – an indispensable element of a responsible AI strategy.
• Example: An online shop could use XAI to ensure specific product recommendations are transparent. This not only builds customer trust, but also increases willingness to buy.

Implement documentation and audits

Complete documentation is essential to ensure that all processes are transparent. Regular audits will help you to identify vulnerabilities and comply with legal regulations.

• Audit processes: Check the quality and fairness of data sources, analyse algorithms for bias and document the results for internal and external stakeholders.
• Transparency reports: Create detailed reports on your measures to ensure ethical and fair use – this will strengthen the trust of your stakeholders.

Further training: Our AI Academy for executives offers special workshops to train decision makers in transparent processes.

Practical tips for preparing transparency reports

A transparency report makes it clear to stakeholders how your AI systems work:

• Data sources: Explain in detail what data is used and how it is processed.
• Insight into algorithms: Disclose your algorithms – within the framework of legal requirements.
• Fairness measures: Communicate the parameters you use to make decisions clearly and comprehensibly.

Training programmes to raise awareness among employees

Training and continuous professional development are essential to deepen understanding of transparent processes – especially in key areas such as IT and compliance.

• Contents: Training should cover legal principles (e.g. GDPR or EU AI Act) as well as ethical and technical aspects.
• Goal: Employees are enabled to critically question AI systems and actively contribute to their transparent use.

Recommendation: Take advantage of our practical AI Academy in everyday business life to make effective use of modern tools such as ChatGPT.

Ensuring transparency in the long term

To ensure transparency in the long term, it is critical to integrate it into the corporate culture. Openness and clarity should be practised at all levels of the company – from executive level to operational teams. A transparent corporate culture not only strengthens the trust of stakeholders, it also promotes compliance with legal requirements.

The EU AI Act, for example, requires providers of AI systems to issue clear instructions on the use and functionality of their systems. Companies should conduct regular training and awareness-raising measures to guarantee that all employees have the necessary AI skills. These measures not only improve legal certainty, but also contribute to the long-term acceptance of AI technologies.

Transparency as the key to trust and competitive edge

Transparency is a decisive competitive advantage when dealing with AI. Transparent processes enable companies to gain the trust of customers, strengthen their market position and mitigate legal risks. Invest in clear governance, open communication and ongoing training. Because responsible AI pays off in the long term.