AI adoption continues to accelerate, but not everyone approaches AI the same way. Some people experiment with every new tool they encounter. Others prioritize governance, trust and oversight. Some focus on business outcomes, while others are driven by curiosity and exploration. These differences matter. How you engage with AI influences
AI agents are moving beyond individual productivity and into government operations. According to Gartner, at least 80% of governments will deploy AI agents to automate routine decision-making, enhancing efficiency and service delivery by 2028. Because of this, government leaders are challenged to determine where they can deliver value with AI agents while maintaining public trust. Their
Most organizations are struggling to use AI insights. Even as it’s been easier than ever to produce predictions, recommendations and scores, many data science and business teams end up with a stockpile of unused information that doesn’t drive meaningful transformation. Decision intelligence helps organizations bridge that gap by embedding insights
Today, your life is being affected by decisions made by AI and machine learning systems. These technologies influence everything from hiring and lending decisions to the content you see online. When those decisions produce harmful outcomes, many people worry about the technology itself. But the greater risk beyond AI becoming
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
Marketers have made enormous strides with generative AI (GenAI) over the last year, moving from experimentation to large-scale deployment. But the next shift in AI maturity – agentic AI – is already underway. This shift will push organizations beyond prompt-based productivity and into a world where AI can act, learn
Georgia-Pacific didn’t treat AI as a science project or a luxury add-on while researching solutions. They made it core to operations, scaling intelligent decisions across an enterprise as massive as their manufacturing footprint. Georgia-Pacific manufactures products used every day, like bath tissue, boxes and lumber, across more than 150 sites
Hear from our experts how insurers can create AI safeguards and ensure safe model use.
