The generative AI market is overflowing with assistants. Most follow the same pattern: generate a draft, hand it to the user, and leave the final execution to a patchwork of
Artificial intelligence inside large organisations is shifting from experimentation to execution. For years, enterprise AI largely meant assistive tools that helped employees draft content, answer questions, or automate isolated tasks.
As AI agents move from experimental demos to production systems, engineering teams are running into a familiar problem: reliability. Large language models are inherently probabilistic. A prompt that succeeds once
As the artificial intelligence industry pivots toward agentic AI — systems capable of autonomously executing multi-step tasks — a clear geographic split is emerging in how the technology is being
For many large enterprises, the most valuable applications of artificial intelligence are emerging far from email inboxes and chat interfaces. At PepsiCo, AI is being tested where errors are expensive
Insurance giant Travelers is rapidly expanding its use of artificial intelligence, recently announcing a new agreement that equips roughly 10,000 engineers and data scientists with AI assistants. Yet company leadership
Primary healthcare systems across parts of Africa are under mounting pressure. Rising patient demand, chronic staff shortages, and shrinking international aid budgets have left clinics struggling to maintain even basic
Corporate networks are quietly filling up with AI agents, creating a growing governance blind spot for technology leaders operating across complex, multi-cloud environments. As business units rapidly adopt generative AI
Anthropic’s Economic Index offers a rare, data-backed look at how large language models are being used in the real world. Rather than relying on surveys or executive sentiment, the report