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Press release
19 Mar 2026
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Zurich, Switzerland
AI Trends 2026: Between sovereignty, agent economy and regulatory turning point
- AI agents are experiencing a breakthrough and can be deployed productively, but are presenting companies with new demands in terms of stability, operations and governance.
- Increasing focus on sovereign AI: Technological independence is becoming a strategic location factor – not least because Switzerland and Europe are lagging behind in terms of computing capacity and AI models.
- Physical AI and AI governance are gaining in importance: AI-controlled robotics is changing production and logistics, while clear strategies, roles and regulations are crucial for the successful use of AI.
Zurich, 19 March 2026 – Artificial intelligence (AI) is continuing to develop rapidly – technologically, economically and geopolitically. As companies increasingly make use of AI, questions relating to regulation, location attractiveness and technological independence are intensifying. Against this background, EY Switzerland has identified key AI trends that will leave their mark on 2026, which it will expand on at the EY National AI Conference 2026 in Zurich on March 24.
The agent revolution: efficient, but not quite ready yet
AI agents have long since ceased to be experiments. According to EY’s CEO Outlook 2026, most CEOs (97%) report that their AI initiatives are meeting or exceeding expectations. The change is most evident in software development in that almost half of the program codes on the GitHub platform were written using AI tools by the end of 2025. AI agents write tests, fix errors and perform complex tasks for hours or days without human intervention.
However, what appears convincing in a demonstration is not the same as reliable operation in a productive environment. In the case of AI agents based on large language models (LLMs), the output can vary greatly for the same tasks. If several AI agents are involved in a process, any errors are multiplied, making it difficult to develop complex multi-agent systems.
These challenges can be met with a structured orchestration of AI‑agents. For most companies, it is not so much the AI‑model itself that requires the greatest effort, but the accompanying prerequisites such as security, test environments, incident management and stable deployment‑processes. The productive use of AI‑agents therefore requires organizational and technical structures similar to those commonly seen in software development – with clearly separated test‑ and production environments and development processes. While the technology is constantly evolving, many companies still lack the operational experience to operate such systems reliably and securely.
Sovereign AI: technological independence becoming a location factor
Sovereign AI refers to the efforts of countries and economic regions to develop their own AI models, data infrastructures and computing capacities in order to reduce dependency on foreign providers.
Adrian Ott, Chief AI Officer at EY Switzerland, said: “A large proportion of Swiss companies that use AI productively currently rely on models from major US providers, meaning that AI that supports business decisions in Switzerland has often been trained, regulated and operated outside Switzerland.”
What happens if access to the most efficient AI models is suddenly blocked for political reasons? Although there are a number of European and Swiss models, they currently lag behind the leading models from the United States for particularly demanding applications. In addition, Europe currently has only around 5% to 10% of the global AI‑computing capacity when it comes to developing new models, compared with around 60% to 75% in the United States.
According to the Global Economic Outlook 2026, trade policy interventions and geopolitical uncertainty remain key growth risks. Digital sovereignty is of crucial importance for Switzerland. As a result, the following key questions are coming to the fore for companies: Where are data processed? Who controls the underlying models? And how robust is your own AI architecture in the face of geopolitical and regulatory changes?
Physical AI: the silent revolution on the factory floor
While the public debate focuses on chatbots and text-based applications, physical AI is becoming much more important and is one of the major AI trends in 2026. Physical AI refers to the use of AI to control robots and machines.
A key driver of this development is the training of robots in fully simulated digital environments. Using so-called digital twins, millions of hours of workflows are mapped in virtual, simulation-based environments in which systems learn to deal with irregularities and unexpected situations before this knowledge is transferred to the physical world.
For companies, the questions this raises are not so much whether physical AI will change manufacturing and logistics, but rather how fast this development is progressing, who is prepared for it and how well they are prepared for it. Companies that already employ robots powered by physical AI are gathering valuable operational data, including insights into sources of error, tolerances, and edge cases. As technology matures, this experience can develop into a significant competitive advantage.
After all, a robot that has been in industrial use for more than a thousand hours is not only a machine worker, but also a supplier of an extensive training data set. It is virtually impossible for competitors to replicate this without direct access to real production environments.
Adrian Ott said: “Physical AI is currently receiving less public attention than generative AI, but it will permanently transform the largest and most important industries and, in turn, the global economy.”
Adaptive AI strategy: Strategy, governance and regulation become differentiating factors
Although most companies are already engaging with AI intensively, they often still lack the organizational foundations to be able to put it to good use. Experience from multiple EY projects across various industries shows that the greatest challenges lie less in the technology itself, but in the structure: a lack of AI strategies; unclear responsibilities; and governance frameworks designed to slow the pace of innovation.
At the same time, the regulatory environment is evolving rapidly. Governments are introducing new frameworks or clarifying existing laws and regulations to address issues of transparency, liability and data protection. Switzerland follows a sector-specific approach with a focus on international connectivity and tries to reconcile innovation with legal certainty. For companies operating across borders, this creates an increasingly complex set of rules that varies depending on the market and industry. In the Swiss financial sector, for example, this dynamic is already tangible. According to the EY Banking Barometer 2026, 78% of banks are actively working on introducing AI. This was up from around half of the institutions surveyed in the previous year (53%).
At the same time, data protection, regulatory requirements and operational resilience remain key challenges. The difference here is not so much whether companies use AI, but rather whether they have the necessary governance structures to operate AI responsibly and in a scalable and adaptable manner. These include clearly defined roles and responsibilities for AI decisions, robust controls that can keep up with the pace at which models and use cases evolve, and transparent decisions on data and model architectures that enable both internal oversight and regulatory audits. Ott said: “AI governance takes on the crucial task of anticipating regulatory developments at an early stage and continuously adapting internal processes before they become a risk.”
AI Trends 2026 will be presented and discussed in depth at keynote presentations, business panels and breakout sessions at the EY National AI Conference 2026 in Stage One in Oerlikon on March 24. Register here.
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EY’s organization is represented in Switzerland by Ernst & Young Ltd, Basel, with 10 offices across Switzerland, and in Liechtenstein by Ernst & Young AG, Vaduz. In this publication, “EY” and “we” refer to Ernst & Young Ltd, Basel, a member firm of Ernst & Young Global Limited.