In an era where fraudsters are increasingly adept at exploiting vulnerabilities in real time, traditional fraud detection methods are no longer sufficient. Organizations must adopt modern streaming engine technologies that can process and analyze customer event data in real time, allowing them to detect and prevent fraud as it happens.
Financial services and healthcare organizations are leading the way with the adoption of AI. And many companies across all industries are building real-time machine-learning applications.
In this week's real-time analytics news: The New Jersey Institute of Technology (NJIT) will establish the Grace Hopper AI Research Institute to advance the university’s expertise in AI.
The future of cybersecurity will be defined by new threats emerging from AI and machine learning and evolving cloud vulnerabilities. As such, organizations will need to focus on Zero Trust and supply chain security to remain agile, proactive, and resilient.
The true value of intelligent manufacturing technologies like AI, digital twins, IoT, and more is unlocked when people are empowered to oversee, adapt, and optimize their use.
As the demand for real-time insights and decision-making continues to grow, the ability to process and analyze data instantly is becoming a competitive differentiator for organizations across all industries.
By adopting data-driven training solutions like XR, the aviation industry can effectively ensure engineers and mechanics have the necessary skillsets required for the most advanced aircraft while maintaining the highest standards of safety and efficiency.
As capital markets continue to evolve, the adoption of AI, digital twins, and data immediacy will be critical for firms looking to maintain their competitive edge. Such technologies are needed to drive superior outcomes in an increasingly complex and dynamic market environment.