Mental health is one of the most pressing challenges of the 21st century. Mental disorders like depression, anxiety and stress-related disorders affect around 1 billion people worldwide, with cases rising each year. Traditional mental health care systems are struggling to keep up with the growing demand, leaving many without access to the support they need.

The humanitarian sector is racing to adopt artificial intelligence for mapping vulnerable populations, but are we moving too fast without addressing fundamental questions about data sovereignty, algorithmic bias, and community agency? The International Committee of the Red Cross recently showcased their work using artificial intelligence to map vulnerable populations across conflict zones

With the increasing complex data that businesses have to handle, a new age of analytics is dawning. Conventional dashboards and manual data queries are no longer fast and expansive enough to make business decisions on time. Enter agentic AI a massive move towards AI systems that not only process information,

As the adoption of artificial intelligence (AI) advances in healthcare, key considerations can help validate that the technology is purpose-built to help clinicians protect patient safety. The emergence of large language models (LLMs) prompted one research team to compare how well this technology performs compared with traditional clinical decision support

In boardrooms across the world, a familiar scene unfolds daily: executives hunched over spreadsheets, dissecting metrics, optimizing processes, and chasing the next quarter’s numbers. It’s a dance of efficiency we’ve perfected over decades, one that has undoubtedly driven remarkable progress. Yet beneath this symphony of optimization lies a quieter truth: