AI readiness is often framed around models, technology and talent. In practice, it starts with something more fundamental: trusted data. Without clean, integrated and governed data, even the most sophisticated AI systems can produce unreliable results and erode confidence across the business. I often meet with data industry professionals and
Most leaders do not have an AI problem. They have a readiness problem. In many small and midsized businesses, pilots are underway and use cases are defined. But when leaders step back and ask the harder question, "Is AI actually paying off?", the answer is often less clear. This gap
A quick search through headlines reveals a range of AI-related disappointments. Consider that 95% of GenAI pilots fail, according to MIT. Amazon’s Kiro agent recently sparked a 13-hour outage by deleting a production environment. And we can’t forget that the resource and energy strain from a new wave of AI
