https://mavai.ch/en/posts/Recent content in Insights on Mavai SchweizHugoenMon, 03 Aug 2026 00:00:00 +0000https://mavai.ch/en/posts/2026-08-03-eu-ai-act-enforcement/Mon, 03 Aug 2026 00:00:00 +0000https://mavai.ch/en/posts/2026-08-03-eu-ai-act-enforcement/Starting 2 August 2026, the European Commission’s AI Office and national authorities begin enforcing the AI Act. New transparency rules require AI systems to disclose their nature to users, and AI-generated or altered content must be labelled and machine-readable. Swiss organisations building or deploying AI systems—especially those with EU customers—need to understand the enforcement structure and their obligations.https://mavai.ch/en/posts/2026-05-01-un-ai-governance-july/Mon, 04 May 2026 00:00:00 +0000https://mavai.ch/en/posts/2026-05-01-un-ai-governance-july/UN meetings in April exposed four tensions shaping AI governance: who has the infrastructure and capacity to develop AI, how data should be governed across borders, whether developing countries can access and transfer technology, and whether regulation steers or constrains innovation. These questions will dominate July’s global AI summits—and the answers could shape international AI policy for years.https://mavai.ch/en/posts/2026-04-06-microsoft-e7-copilot-swiss-private-banking/Mon, 06 Apr 2026 00:00:00 +0000https://mavai.ch/en/posts/2026-04-06-microsoft-e7-copilot-swiss-private-banking/Microsoft 365 E7 makes AI-assisted productivity commercially accessible for the front office. But for a Swiss private bank, the licence is the easy part. Confidentiality, data sovereignty, FINMA expectations, and the US CLOUD Act all shape whether — and how — Copilot can be deployed safely.https://mavai.ch/en/posts/2026-04-02-quantifying-uncertainty/Thu, 02 Apr 2026 00:00:00 +0000https://mavai.ch/en/posts/2026-04-02-quantifying-uncertainty/The NASA risk matrix has two axes. Consequence is tractable. Likelihood — especially for stochastic AI systems — is not. Regulators are now demanding quantitative evidence, and probabilistic testing is how you produce it.https://mavai.ch/en/posts/2026-04-01-us-switzerland-ai-regulation/Wed, 01 Apr 2026 00:00:00 +0000https://mavai.ch/en/posts/2026-04-01-us-switzerland-ai-regulation/Switzerland’s AI governance landscape is shaped not only by the EU AI Act and the Council of Europe’s AI Framework Convention, but increasingly by the technical standards and frameworks emerging from the United States. Understanding how these interact is becoming essential for Swiss compliance professionals.https://mavai.ch/en/posts/2026-03-26-swiss-testing-day-compliance-ai/Thu, 26 Mar 2026 00:00:00 +0000https://mavai.ch/en/posts/2026-03-26-swiss-testing-day-compliance-ai/Swiss Testing Day 2026 made one thing clear: compliance and AI are no longer parallel conversations. From Bertrand Meyer’s keynote on software verification to a standout talk on why AI is useless for compliance — and indispensable — the conference showed that testing non-deterministic systems is the defining challenge for quality professionals today.https://mavai.ch/en/posts/2026-03-25-deepfakes-banking/Wed, 25 Mar 2026 00:00:00 +0000https://mavai.ch/en/posts/2026-03-25-deepfakes-banking/Deepfake technology started as a curiosity. Today, regulators, law enforcement, and central bankers warn it poses real threats to financial institutions — from CEO impersonation to onboarding fraud. What can banks do about it?https://mavai.ch/en/posts/2025-03-27-switzerland-coe-ai-convention/Wed, 25 Mar 2026 00:00:00 +0000https://mavai.ch/en/posts/2025-03-27-switzerland-coe-ai-convention/On 27 March 2025, Switzerland signed the first legally binding international AI treaty. Twelve months on, no country has ratified it, the EU is moving faster, deepfake fraud in Switzerland has exploded, and a domestic legislative bill is due by the end of 2026. Here is what has happened — and what has not.https://mavai.ch/en/posts/2026-03-21-why-probabilistic-testing/Sat, 21 Mar 2026 00:00:00 +0000https://mavai.ch/en/posts/2026-03-21-why-probabilistic-testing/Swiss regulators are asking for evidence that AI systems perform reliably. Traditional testing can’t provide it. Here’s why statistical approaches are the answer.