At IBM, we understand both the exponential benefits AI can offer your organization as well as the unique challenges implementation can present. In 2018, we formalized the AI Ladder to provide a prescriptive approach to successful AI, and to impart lessons we've learned through over
IBM Watson Studio enables organizations to develop models and simplify and scale AI across any cloud while simultaneously automating the AI lifecycle. What do end users say about it? Here are a few quotes from among 94 reviews of Watson Studio on Gartner Peer Insights, a free peer review and
At a point in the not-too-distant future, AI will comprise an integral part of everyday business tools. But you need not wait for tomorrow, because, IBM Cognos® Analytics puts AI in the hands of users today to help them prepare, analyze, visualize their data and share insights
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.
Talent: It’s a key issue impacting today's AI-hungry organizations. While AI skills are in high demand, organizations admit they’re hard to come by. In fact, the lack of talent scarcity has been called out as one of the top three hurdles to AI adoption, after data complexity, and a
As communities and businesses worldwide look to understand the economic impact of COVID-19 and prepare for an eventual recovery, the biggest test of decision-making will be the data that will inform the business decisions. Was it trusted? Was it timely? Was it enough?
To date, there
During IBM’s first Data and AI Virtual Forum, a Forrester-led panel of AI leaders – who happen to be women – discussed how their organizations have achieved business-critical AI outcomes in the face of known skills gaps.
Moderated by Srividya Sridharan, a vice president of Research
We live in the age of connectivity. Everyone and everything is constantly connected; yet, in most organizations, business unit planning operates in silos. This fragmented approach is often the result of spreadsheet-driven planning processes, which impede collaboration.
As we enter a new era of
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
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
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
India’s current patient to physician ratio prevents thousands from receiving individualized care needed. iKure has developed a network of facilities with an integrated EMR system that brings care to rural communities in India, Vietnam, and Africa at an affordable and convenient way.
The data science market is evolving rapidly. Businesses need to respond to a volatile climate and be able to scale cost-efficiently by automating AI lifecycle management. A key phase in the AI lifecycle is model selection, training, and deployment. Many data scientists and developers today want to
Many enterprises have a tangled data management system, comprised of an assortment of products assembled together, in an attempt to meet the complex needs of modern day data management. The labyrinth of convoluted data management systems often evolves as a natural response to data
Artificial Intelligence has penetrated every industry in some form or another. From powering recommendation engines for consumer products to helping extend credit products in a more efficient manner, AI is becoming an imperative that no C-level executive can choose to delay. Even