AI Adoption in Switzerland 2026: Does Gen Z turn to ChatGPT first?

How widespread is AI in everyday life in Switzerland? A study of 651 working adults on ChatGPT, Google and trust.

48 per cent of 15- to 24-year-olds ask an AI chatbot first, not Google. And when it comes to health questions, the most trustworthy source isn’t the first port of call. Our study of 651 working people shows just how far AI has become part of everyday life in Switzerland.

Download the study report for free now.

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Data has become one of the most valuable assets for businesses. The proper utilization of data can enhance processes, drive product strategies, and significantly improve the customer experience. However, not all data is created equal. To harness the full potential of data, companies must develop and implement a well-defined data strategy.

A data strategy is essential for several reasons:

  • It defines how data is collected, managed, stored, shared, and used within an organization.

  • Ensures data quality, consistency, and reliability, critical for data-driven decision-making.

  • Addresses data security and confidentiality, safeguarding sensitive information.

Crafting a Data Strategy using KPI’s

A data strategy is a comprehensive plan that integrates data into operational processes and ensures its effective use across the organization. It encompasses data quality, security, and the democratization of data use. The right data strategy strikes a balance between defensive and offensive approaches:

  • Defensive Strategy: Focused on minimizing risks, security, and compliance.

  • Offensive Strategy: Geared towards growth, innovation, and creating value through data products or services.

Learn how KPIs are integral to crafting a data-driven strategy that strikes the right balance between defense and offense, and how they play a pivotal role in your data-driven journey.

Data as a Product for New Business Areas

A result-oriented data strategy not only enhances decision-making but also opens new revenue streams and business opportunities. Companies can monetize data at different levels of maturity, from data products to data-driven offerings. Real-world examples include Hilti and Michelin, both of which have transformed their businesses through data innovation.

Data-Driven Decisions

Data-driven decisions are a game-changer in areas like innovation, product development, brand management, and marketing. This section provides a case study of a wine retailer that leveraged data to transition from mass marketing to highly personalized, content-based marketing, resulting in improved conversion rates.

Ensuring Data Integrity and Security

Data governance is crucial for maintaining data availability, integrity, and security. This section discusses key aspects of data governance, including data availability, data integrity, and data security, emphasizing the importance of data ownership, privacy, and compliance.