Kamila Pope

For over two decades, organizations have pursued a common ambition to become “data-driven,” focusing on improving access to data, scaling analytics, and building modern platforms. With that ambition now largely within reach, data and AI leaders are facing the next frontier: how to progress from insight access to translating intelligence into consistent, high-quality decisions. The Rise of Decision Intelligence examines how leading organizations are responding to this shift in practice.

Traditional AI governance relies heavily on pre-deployment approval and static controls. Agentic AI makes that approach fragile. Because AI agents can change behaviour over time and act continuously, leaders describe the need for ongoing monitoring, not just upfront sign-off. This includes tracking behavioural drift, unexpected actions and execution outside normal business hours. Human-in-the-loop controls remain non-negotiable, especially for customer-facing or policy-relevant decisions.

Many leaders emphasise the power of defining and communicating their own leadership narrative: a story that connects their data expertise directly to business impact. “I make it clear that our work is not just technical but essential to the company’s success,” said Megan Reutin, Global Head of Data Science and Strategy at Grünenthal. “By showcasing early successes and tangible results, I build credibility and generate excitement among stakeholders”, she concludes.