In the airline industry, timing and synchronization are everything when it comes to the customer experience. Mitigating unforeseen circumstances against customer expectations and good old supply and demand are all issues well within the wheelhouse of AI’s predictive capabilities.
As we grow smarter and more sophisticated, thanks to rapidly enhancing technological innovations, enterprise data management and analytics have to keep pace to ensure organizations continue to remain effective and data- and insights-driven.
Let’s not underestimate the sheer scale of the problem
As the world confronts new challenges, business priorities and job roles are rapidly shifting. Rethinking your entire strategy and the way you work means data and AI will play a more central role in how organizations move forward.
Take in the recent expert sessions that bring together technology
Data is the fuel, cloud is the vehicle, AI is the destination. The intersection of these three pillars of IT has been the focus of IBM. Through the launch of IBM Cloud Pak for Data, our modern data and AI platform, we have containerized numerous offerings and delivered them as
Many financial firms are increasing their use of AI models because they can represent the real world more accurately, and they can deliver better projections than traditional, rule-based models. But some AI models can add complexity and risk.
You can minimize that risk and also streamline the
Today’s market conditions elevate the need to put trusted data into the right hands almost in real-time. The market has been experiencing a dramatic demand for near-frictionless, fact-based decision-making processes. With business continuity top of mind, leaders are turning to DataOps programs to
CIOs and other technology innovators are boldly leading their companies through change during this unprecedented time. As IT leaders make their journey to the cloud and prepare their business for the future, greater application modernization and agility is needed to meet these new marketplace