Welcome to the Journey to AI Blog, the new home for blog storytelling from across the IBM Data and AI business. Here you’ll find the latest news, client features, product launches, industry innovator spotlights and thought leadership from IBM executives.
Now more than ever, digital transformation
Your data and AI tools are important, and outcomes are critical, but with today’s data-driven world, businesses must accelerate outcomes while improving IT cost efficiency. But how do you achieve this?
First, Data and AI initiatives must have intelligent workflows where the data lifecycle can work
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.
It could be said there’s really no wealth but health itself, but in rural India, some 840 million people are challenged by obtaining the healthcare they need. For the average citizen, just getting to a medical appointment might require a day-long journey. Inadequate infrastructure
As companies progress on their Journey to AI, there is considerable focus on what needs to be available to build AI driven applications. The rungs of the AI ladder, which are best described as Collect, Organize, Analyze, Infuse, and Modernize are designed to strengthen a company’s
A colleague recently shared a great quote with me from a mainframe CTO expounding on which platform is the “blue ribbon” winner for managing data across mainframe, IBM i, UNIX and Windows.
“While everyone scurried around to figure out what platform won,
a clear victor emerged: data”
As the world confronts new challenges, it is a unique, unprecedented time to recast old ways of working and redefine industries. At this moment, although it may seem that global business is at its quietist, beneath a veneer of calm, feverish transformations are taking place across markets, behind
Keeping up with modern business
Business analysts today are expected to deliver insights and decisions on demand. Yet with continually increasing data complexity and volume, business analysts find it more and more challenging to produce accurate results in a timely fashion.
A common business hurdle
Modern Data and AI application deployments are expanding through open source containers and hybrid multi-cloud support, but how can you achieve the benefits of infrastructure optimization and unified operationalization without vendor lock-in?
In this era of increasing AI/ML workloads and the need
Two of the greatest challenges faced by organizations today are the rising volume of data and the lack of confidence to act on the insights this data reveals. Fortunately, there are AI-fueled data management solutions that directly address these two challenges to make data simple and accessible.