AI adoption across enterprises is moving faster than most leaders expected. Many organizations are rolling out internal GenAI apps/tools with access to multiple models like chatbots, agents, workflows, and automation tools across their business functions. On paper, it looks like real progress. In practice, the value story is far less convincing. Despite widespread adoption, m...

As organizations scale artificial intelligence to increase speed and efficiency, many are unintentionally creating an unmanaged Algorithmic CMO: a system that relentlessly optimizes tactical performance metrics while quietly eroding long-term customer equity and enterprise value. The problem is not that AI is ineffective, but that it is governed under the wrong parad...

As organizations deploy increasingly autonomous artificial intelligence systems, many are discovering that existing governance and operating models are ill-suited to software that can independently perceive, decide, and act. While recent advances in generative AI have focused on model capability, the more consequential challenge for enterprises lies in governing systems tha...

For nearly two decades, the corporate case for ESG has been built on a confident proposition that virtue reliably produces value. From Davos panels to CEO letters and sustainability indices, the refrain has been consistent. Firms that reduce environmental harm, improve labor practices, and strengthen governance should face fewer disruptions, earn greater stakeholder trust, an...

Most companies see AI as a data and technology challenge. Collect more information. Train larger models. Scale automation across the enterprise. While these efforts are essential, companies making the most progress with agentic AI recognize something deeper: The real differentiator is not the data or even the models, but the “tacit knowledge” embedded in the judgment of their...