The paper addresses a hidden risk in AI adoption: organisations may automate a workflow without fully understanding or preserving the human expertise that makes it work. Written procedures rarely capture every judgement call, exception or contextual cue that experienced professionals rely on. These can be lost when work moves into an AI-enabled system.

On September 30, 2026, Governor Gavin Newsom signed California Senate Bill 574 into law. The law takes effect January 1, 2027. SB 574 is the first law of its kind, and poses a question for the legal community: Does the responsible use of artificial intelligence (AI) in legal practice really require new legislative mandates when existing professional duties, judicial rules, and disciplinary mechanisms already address many of the same concerns?

This blog explores how companies across four key Swiss sectors : life sciences, academia, finance, and non-profits, are adopting AI tools, the lessons learned, and the governance protocols emerging from their experiences.

Paper 1 defines the problems of benchmark saturation as the loss of reliable discriminative power among top-performing models under comparison and identifies benchmark properties usually associated with saturation after an analysis of 60 benchmarks, and makes concrete anecdotally known characteristics of benchmarks, with implications for benchmark lifecycle management. Paper 2 questions the benchmark culture itself, and how this is perpetuating structural harms towards less r

In this article, Petruta Pirvan and Sonal Makhija explore several real-world use cases and highlight the practical challenges that organizations commonly encounter.The growing reliance on legitimate interest as the primary lawful basis for AI training has been broadly accepted by EU data protection authorities. In comparison to the impracticality of obtaining consent at scale, legitimate interest offers a more pragmatic path. However, its applicability depends on the specific

This article Sonal Makhija, an AI & data compliance lead at the H&M Group, where she has led the AI Act implementation. It explores the kind of legal ambiguity that small and medium enterprises face when navigating the AI Act and the resulting need for greater clarity and practical guidance. It also discusses how AI governance risks arising out of everyday AI use cases, which typically fall within limited to low-risk classifications under the AI Act, but pose significant secu

As AI agents become more capable — reasoning, collaborating, adapting, and acting independently — the questions of evaluation, safety, governance, and trust become even more urgent. To help shape this global conversation, we’ve highlighted a few key insights from the World Economic Forum white paper contributed to by Nebahat Arslan, our Global Head of Partnerships. These insights point to what responsible, inclusive AI must look like in the age of agentic systems.