AI could help reduce Europe’s water losses
Europe loses around 23% of its treated water before it ever reaches consumers. The main reason is outdated and leaky pipelines. With droughts becoming more frequent, these losses are making water shortages worse and driving up costs.
Why Artificial Intelligence shows bias
AI systems are trained on human data and built on human assumptions. As a result, they exhibit predictable and systematic biases when evaluating people. These systems don’t truly “understand” individuals.
US Treasury publishes AI Risk Guidance
The US Treasury has released a comprehensive AI risk management guide for financial institutions, aimed at standardizing AI use and enhancing accountability. Built on existing standards, the framework includes over 230 control objectives across the entire AI lifecycle.
Strong Data Management key to AI success
There is an increasing gap between the hype surrounding artificial intelligence and the actual benefits it delivers for businesses. Studies indicate that up to 95% of AI pilot projects fail, primarily due to weak data strategies and insufficient foundations.
Transition from pilot projects to AI production
At AI Expo 2026 in London, industry leaders highlighted the shift from experimental AI pilot projects to robust, production-ready implementations, signaling a market in significant transition.
AI is not a bubble, but a technological change
The existence of an AI bubble is possible. If so, however, it has been created primarily by exaggerated expectations and hype, not by the technology itself.
Project Management drives AI-powered sustainability
Sustainability has become a central business priority, and AI offers significant opportunities to enhance it. However, this requires that AI is deeply integrated within the organization through effective project management.
AI faces the same data hurdles as Big Data
Companies are still struggling with the same data challenges that emerged during the Big Data era. Despite AI’s huge potential, its success still depends on transforming vast, scattered, and often inconsistent data sources into unified, AI-ready formats.