Shaping AI Transformation in Switzerland From the pilot phase to an AI strategy

In 2026, an AI boom is driving the Swiss economy. AI innovations enable efficiency gains, reduce costs, and create sustainable value for both businesses and the general public. Advanced language models offer significant potential, particularly in the public sector: they automate the processing of inquiries and improve service quality.

The foundation for a successful AI transformation is a structured strategy that combines innovation, compliance, and competitive advantages. Adapting AI to Swiss values is crucial for societal acceptance. Compared to other countries, Swiss regulation presents specific challenges and opportunities.

Ironforge supports government agencies and companies in Switzerland in deploying AI in a regulatory-compliant and effective manner over the long term.

Many organizations in Switzerland have launched initial AI initiatives. Pilot projects are underway, generative systems are in use, and automation is being implemented in specific areas. The public sector, the financial sector, the pharmaceutical industry, and SMEs are benefiting in particular. A real-world example: In the city of Zurich, an AI-based system significantly reduces the time required to process citizen inquiries and increases public satisfaction. Yet the structural framework is often lacking. Responsibilities remain unclear, data quality is insufficient, and regulatory requirements are incorporated into planning only at a late stage.

Complex operating conditions

The revised Federal Act on Data Protection (FADP) has been in effect since 2023 and sets clear requirements for the processing of personal data, including by automated systems. At the same time, many Swiss organizations are aligning themselves with the EU AI Act, which regulates AI systems according to risk categories and introduces transparency and documentation requirements.

The federal structure complicates the situation. The federal government, cantons, and municipalities each operate with their own data protection requirements, IT architectures, and decision-making processes. Many Swiss organizations are unfamiliar with the relevant AI regulations. AI solutions that work in one canton cannot be easily transferred to another.

On February 12, 2025, the Federal Council discussed an overview of possible regulatory approaches. A draft for public consultation on AI regulation is to be prepared by the end of 2026. In parallel, an implementation plan is being developed for non-legally binding measures such as industry-specific solutions or voluntary commitments.

Particularly in the public sector, healthcare, and the life sciences industry, demand is growing for transparency and traceability in AI systems. Guidelines and overviews on AI regulation and data protection help public administrations establish best practices.

Anyone using AI in core processes, such as application processing or decision support, must take these requirements into account from the very beginning. Making adjustments later is costly and risky.

Common Areas of Conflict in Organizations

AI is effective only where data quality, process logic, and responsibilities are clearly defined. In practice, recurring obstacles emerge:

• Data is scattered across different systems
• Ownership of training and decision-making data is unclear
• Models are put into production without clear control mechanisms
• Automation changes roles and responsibilities
• Regulatory requirements are incorporated into planning too late

What connects these hurdles: AI initiatives launch without clear goals and without buy-in at the executive level. They get stuck in individual departments and have too little impact. Without measurable goals, neither progress can be demonstrated nor acceptance built. Without executive-level support, AI projects get stuck in individual departments. Companies that view AI merely as an experiment struggle to demonstrate ROI and overcome regulatory hurdles.

A structured AI strategy with clear goals and compliance requirements forms the foundation for innovation, efficiency gains, and competitive advantages.

Interventions in credit decisions, claims processing, or administrative processes directly impact quality, compliance, and reputation. Without clear guidelines, there are no efficiency gains—only risk.

Benefits of AI for Organizations

The strategic use of AI offers organizations in Switzerland the opportunity to fundamentally improve their operations. AI applications automate repetitive tasks and free up valuable resources. Employees can focus more on complex, creative, or customer-facing activities.

At the same time, AI enables the intelligent analysis of large volumes of data. Organizations gain new insights, identify trends early on, and make more informed decisions. Integration into existing processes optimizes workflows and supports the development of innovative services and products.

For companies and government agencies, this means not only a reduction in operating costs but also an increase in competitiveness. The ability to adapt flexibly to changing market conditions and tap into new potential is becoming a decisive factor for success.

Our Approach: Clarity Before Technology

Ironforge helps organizations in Switzerland implement AI within existing frameworks. The starting point is not the technology itself, but its business relevance: Which processes are suitable for automation? Which decisions can be supported or replaced? What data is available in the required quality?

Based on this, we develop a realistic vision. We define governance structures, control mechanisms, and documentation requirements early on. We clearly define responsibilities between business units, IT, and risk management before implementation begins.

Support from senior management and the integration of innovation and compliance are critical success factors. As a Swiss company, we have practical experience with local regulatory frameworks and support organizations with market knowledge that no other provider can match.

Change Management as a Key to Success in AI Transformation

The implementation of AI requires more than just a technical project. It transforms processes, decision-making logic, and roles. Administrative staff become reviewers. Managers make data-driven decisions. Departments take responsibility for model quality and result verification.

Open, ongoing communication is key: Employees must understand why AI is being used, what goals are associated with it, and how their tasks will change. Transparency builds trust and fosters acceptance. Equally important is targeted training so that the workforce can fully leverage the potential of AI applications.

Those who put people first and view the introduction of AI as a collaborative effort lay the foundation for a successful transformation.

Integration instead of a siloed solution

Automation is not introduced as an isolated innovation project, but rather integrated into existing process and architectural structures. The targeted use of AI systems helps increase efficiency and reduce costs by automating routine tasks and accelerating processes. In administration in particular, the automated processing of inquiries enables optimized data organization and improved service quality.

The customer perspective is becoming increasingly important: AI enhances the customer experience through personalized, efficient services across various industries.

Ironforge leverages ]init[’s AI infrastructure and platform components. The ]init[ AI Platform enables robust, privacy-compliant AI applications, whether on-premises or in suitable cloud environments. The platform complies with the GDPR and the EU AI Act. For Swiss organizations that do not wish to transfer data to external providers, this is a key advantage.

From Orientation to Implementation: “AI Practice Guide”

Our practical guide, published in collaboration with ]init[, addresses the question of which AI models are suitable for Swiss government agencies and how they can be implemented. Structured guidelines, practical overviews, and checklists provide a clear starting point.

However, there is a crucial step between the initial overview and a productive AI solution: preparing your own organization. Many government agencies find that technical issues can be resolved quickly, while governance, data responsibility, and process maturity require more time. Who is responsible for AI decisions? How are requirements from the DSG and internal control obligations taken into account from the very beginning?

The “AI Practice Guide” provides a comprehensive overview of the possibilities and limitations of artificial intelligence. Large language models open up far-reaching opportunities for innovation and efficiency gains in the public sector and in industries such as administration, healthcare, and pharmaceuticals.

Across 37 pages, we address key questions in the areas of fundamentals, AI models, data, implementation, and legal frameworks. This overview helps you develop your own guidelines and unlock the full potential of AI for your sector.

Download it here for free.

Assessing the State of AI: The First Step

Before organizations begin implementation, it’s worth taking stock. A structured analysis provides clarity on the current state of data, process maturity, and automation potential.

An AI assessment with Ironforge answers the key questions: Where does your organization stand today? Which prerequisites are already in place, and which ones still need to be established? Which AI initiatives can be implemented in the short term, and which ones require more extensive preparation?

The result is not an abstract strategy paper, but a concrete roadmap with prioritized next steps.

Request an AI Assessment