Boardrooms buzzed about generative breakthroughs, yet a colder reality surfaced as a new survey found that the majority of enterprises still cannot move data freely enough to feed the very models they hope will transform the business. That tension between ambition and access set the stakes: growth
Operational missteps in aviation rarely stem from a lack of data; they arise when flight events, maintenance actions, and parts movements live in silos that resist timely reconciliation and leave crews guessing at the truth on the ramp. When a flight logbook update must traverse email chains before
Boardrooms wanted measurable AI impact yesterday, yet risk disclosures kept piling up as exposure widened from datasets and pipelines to model behavior and semi-autonomous agents that act without clear oversight or context. That friction showed up in the numbers: public AI-risk disclosures jumped
The moment agents stopped asking for dashboards and started filing tickets, shipping code, and adjusting prices, the quiet plumbing of data platforms became the frontline that decided whether automation saved money or broke production. Enterprises that once tolerated stale extracts and fragmented
Richard Lavaile sits down with Chloe Maraina, a business intelligence leader who turns big data into crisp narratives that executives can act on. With a front-row view of AI’s accelerating impact on leadership, operating models, and market structure, Chloe dissects the week’s pivotal moves—from
Market signals have grown so dense and fast-moving that any delay, mismatch, or silent error in data can ripple through models, distort risk views, and chip away at returns long before performance attribution catches the miss. That is the context in which OLZ AG, a quantitative asset and wealth
