Cloud and AI strategies are not one-size-fits-all. From client engagements, we understand the journeys to cloud and AI are complex and unique to each organization. Cloud strategies can include many dimensions of cloud consumption, including public and private, shared, dedicated, on premises and off premises. The average enterprise is leveraging multiple clouds. AI adds another layer of complexity as organizations experimenting with AI struggle to find the right infrastructure to run these compute-intensive workloads.

It's not unusual today to see people talking about artificial intelligence (AI). When I was a kid in the 1980s, AI was depicted in Hollywood movies, but its real-world use was unimaginable given the state of technology at that time. While we don't have robots or androids that can think like a person or are likely to take over the world, AI is a reality now, and to understand what we mean when we talk about AI today we have to go through a -- quick, I promise -- introduction on some important terms. Simply put, AI is anything capable of mimicking human behavior. From the simplest application -- say, a talking doll or an automated telemarketing call -- to more robust algorithms like the deep neural networks in IBM Watson, they're all trying to mimic human behavior.

Our data-centric world is driving many organizations to apply advanced analytics that use artificial intelligence (AI). AI provides intelligent answers to challenging business questions. AI also enables highly personalized user experiences, built when data scientists and analysts learn new information from data that would otherwise go undetected using traditional analytics methods. AI-driven analytics delve more deeply into organizational data, deriving smarter insights that can give businesses a powerful competitive edge. A well-considered data strategy is essential from the start.

Science fiction movies have been warning us for decades that artificial intelligence (AI) is going to rise up and take over the world. As it turns out, those movies were right; AI is poised to take over the world. More accurately, the organizations that are able to adopt, implement and maintain AI as a part of their business model will have a competitive edge in the marketplace. Fortunately, accomplishing this may be easier than you think. There are still many people who think of AI as a technology of the future, but the truth is that AI is already here as a part of our daily lives.

As artificial intelligence (AI) capabilities mature, enterprise leaders are continuously evaluating use cases that can transform their business. A key challenge that slows down AI adoption is the abundant but untamed data that is not ready for AI. There is a strong correlation between companies outperforming in AI adoption and the ones that have a robust data infrastructure aligned with their business architecture. According to the 2018 IBM Business Value survey, Shifting Toward Enterprise-grade AI, 65 percent of outperformers surveyed capture, manage and access business, technology and operational information on key corporate data with a high degree of consistency across the organization versus 52 percent of all others surveyed. IBM recently introduced IBM Cloud Private for Data (ICP4D), a data and analytics platform, to help make your data estate ready for AI.

If you read the tech press, you'll hear that artificial intelligence (AI) is all the rage these days. And whether or not they are doing it well, everyone is saying that they're engaging in AI. One thing is certain: organizations across industries are running fast to be a part of the AI revolution. In this two-part series, I'll examine what's driving this rapid pace of adoption, and why some companies are seeing far more success than others. In part one, I'll discuss some of the needs inherent in creating an AI solution.

Last week, I talked about how implementing AI solutions in your organization is a lot like climbing a ladder–going it alone can be risky, but a good AI infrastructure is like having a trustworthy friend to help steady your climb. In my view, a crucial piece of that infrastructure support is the IBM Power AI Enterprise Platform. This new technology offers a comprehensive infrastructure environment designed to address the key requirements for AI initiatives. In other words, to help you start climbing the AI Ladder with confidence and speed, mitigating risk. Let's take a look at how PowerAI Enterprise helps accelerate each step of your AI journey.

Artificial intelligence (AI) is rapidly being adopted by organizations of all sizes and yielding impressive results, transforming businesses and industries globally. While senior executives, managers and senior IT architects are often catalysts for change, it is the developers who are deciding which specific products and technologies individual companies will use on their journey to AI innovation. Interestingly, while many AI projects get started following executive mandates, often it is the AI developers and data scientists who shepherd new and innovative AI projects along in the organization. AI developers and data scientists aren't as motivated by executive mandates as they are by the combination of experimentation, the desire to proactively satisfy new client demands, and of course by the fun realized in delivering new and innovative AI solutions. In many cases, it's the AI developers and data scientists who also can quickly establish which specific AI tools and algorithms will immediately help an organization solve business problems.

October 11, 2018 Written by: Douglas O'Flaherty Autonomous vehicles will transform our daily lives and our communities. What seemed like science fiction a decade ago is now visible as test vehicles gather data, tune sensors and develop the artificial intelligence (AI) to make cars self-driving and safer. Every major auto company, their suppliers and startups across the globe are using the latest technology in an arms race to the future where cars drive themselves. It isn't enough for the vehicle to navigate itself. It must also be prepared for the unexpected.

Enterprises embarking on an AI journey have a much greater opportunity for success when they have executive leadership support and the right talent in key AI roles. You know your business best and are in a position to make the right choices for your company. To help you think about your AI journey, here are suggestions from IBM concerning who should be on your AI team. Our experience suggests that these specific roles should be filled to get buy-in on the project and create a successful solution. Enterprises that have successfully implemented AI have strong executive leadership support for the new technology.