At a high level, enterprise AI feigns tasks previously only associated with the human mind, including reasoning, correcting, perceiving and problem-solving. But on the ground, it's central to companies' daily operations, churning through data for business insights, seeing and recognizing images, performing high-volume tasks with great efficiency, and enabling machines to learn without explicit programming.
At the core of these operations and data-intensive workloads is an AI infrastructure consisting of powerful hardware components, software and services. Assembling or enhancing this infrastructure, both in the cloud and on premises, requires a robust AI strategy from both IT and the business.
Storage is a top priority, specifically scalability as data volumes grow. Capacity, IOPS and reliability are also major factors. Networking is another consideration, as AI, specifically deep learning algorithms, requires high-bandwidth and low-latency architectures.
Enterprises also need powerful compute resources, including specialized and efficient CPUs and GPUs. Data prep, cleansing, access and governance also play a big role in enterprise AI initiatives. Finally, AI skills training, development, and recruitment are major considerations for enterprise AI projects.
Maintaining AI infrastructure and getting the most business value from an AI initiative requires data analysts and scientists, developers, security experts, and networking engineers with specific and advanced skills.
AI initiatives touch many parts of enterprise IT, and the market includes enterprise technology mainstays like Intel, IBM, SAP and Microsoft, as well as new power players like Nvidia and Amazon, to name a few. Because few IT endeavors rival the scope of an AI initiative, honing in on the various elements can be challenging for even the most seasoned IT shop.
In this guide, we break down enterprise AI and AI infrastructure, from defining the category and its practical uses to all the considerations for building and maintaining the infrastructure and engine that support the initiatives. Finally, learn about the products and players to inform your enterprise buying decision.