Utilities and power generation companies are bolstering operational efficiency and plant reliability by implementing advanced ...

Effective evaluation and governance of predictive models used in health care, particularly those driven by artificial intelligence (AI) and machine learning, are needed to ensure that models are fair, ...

Traditional testing, though valuable, is often reactive and identifies quality issues only after they have occurred. This can lead to project delays and financial and reputational losses. In fact, ...

Modern credit risk management now leans significantly on predictive modelling, moving far beyond traditional approaches. As lending practices grow increasingly intricate, companies that adopt advanced ...

Processing data closer to its source (edge computing) combined with AI allows for faster analysis and decision-making in preventative maintenance, as well as enhances data security. The work flows in ...

Predictive models are used across the student life cycle in higher education, to gauge yield in admissions as well as retention and graduation initiatives, as campus leaders look to understand what ...

Zohar Bronfman is the cofounder and CEO of Pecan AI, a predictive analytics platform making advanced AI accessible to business teams. For decades, predictive analytics was a capability largely ...

Discover why the transition from AI chatbots to autonomous agents is raising alarms about data loss, action blindness, and ...