An increasing number of organizations are coming to the realization that Artificial Intelligence (AI) is needed to drive revenue and business goals in the future. In fact, 76% of IT decision-makers surveyed by IDC said AI will be a key part of their digital transformation strategy over the next one to two years.[1]
AI is a journey that begins with data and therefore cannot exist without an information architecture (IA), but being able to gain business value and insights from data is not always easy. Legacy infrastructure is inadequate for AI workloads and data silos make it difficult to get a holistic view of all your information, limiting the value of AI.
Additionally, organizations are moving towards hybrid cloud to respond to evolving business needs. As data is increasingly distributed, it becomes a struggle to provide adequate protection and management. Infrastructure that was not built for AI and hybrid cloud is not flexible enough to respond to modern workloads and demands without adding complexity.
The best AI is built on a foundation of data that is collected, organized, and analyzed carefully, then infused into the business. This foundation should also be open, flexible, and allow access to data of every type, regardless of where it lives. Every successful AI project goes through a multistep process that starts with having the right data and progresses to using AI broadly.
Adopting AI is not without its challenges. The general-purpose storage infrastructure that organizations are accustomed to using needs to be replaced or supplemented with storage systems that are geared towards AI-specific tasks.[1] When adopting AI, here are some of the challenges that organizations often face:
Moving from experiments to scaling AI for business value.
Modernizing for an AI-focused digital transformation requires expertise in new standards of developing, implementing, and maintaining AI solutions at scale.
Legacy infrastructure/complexity.
Organizations can no longer use traditional, general-purpose computing or legacy storage infrastructure. This outdated infrastructure increases complexity and is not flexible enough to respond to AI workload demands. Instead, they must employ a scalable compute with an equally scalable, high-performing, integrated, flexible, and secure storage infrastructure.
Data silos.
Storage is typically implemented with specific storage solutions that create silos of data. These silos are not integrated together, nor are they integrated with a comprehensive set of infrastructure solutions, resulting in a lack of global data access.
It is no surprise many organizations are not sure how to proceed and do not have a clear understanding of how best to leverage AI to their advantage. Therefore, IBM has put together a prescriptive approach to accelerating the journey to AI called the AI Ladder™. The AI Ladder is a framework that accelerates your ability to collect and organize data, gain deeper insights by leveraging AI-driven data analysis and infuse your enterprise with these insights.
As companies begin to modernize, they seek to provide an architecture that will propel them into the future. The journey to AI is about moving data from collection to insights with an IA that can easily be integrated throughout the organization. It is important that each part of the AI Ladder provides an integration to the entire journey. Starting a project on one part of the journey is fine, but it is critical to ensure the project considers an overall IA for AI to optimize resources and modernize your infrastructure for expanding AI workloads.
The AI Ladder:
Collect
Data is the fuel that powers AI, but it can become trapped or stored in a way that makes it difficult or cost-prohibitive to maintain or expand. You will need to unleash that data so it can expand from edge to core to public cloud within a simple and cost-efficient infrastructure. IBM Storage for data and AI makes data simple and accessible for hybrid cloud with AI storage solutions that fit your existing business model.
Organize
AI can only be as good as the data it relies on. Businesses must fully understand what data they have so they can leverage it for AI and other organizational needs, including compliance, data optimization, data cataloging and data governance. IBM Storage for data and AI provides insights into data from multiple sources by automatically and continuously indexing objects and files when changes are made and storing this information in the built-in storage catalog.
Analyze
Analysis is critical to the AI journey and must provide high performance for fast analysis and seamless connection to both the data lake and the storage catalog. Organizations must plan for issues beyond the deployment of AI; you need to build AI infrastructures that give you confidence in your data and that enable you to access it wherever it resides. IBM Storage for data and AI provides high-performance access to data and an integrated AI infrastructure for analysis.
Infuse
Business challenges can become an opportunity to explore, understand, predict, and bring an AI infrastructure to every organization. IBM Storage for data and AI is empowering you to use data and AI storage to leverage that infrastructure in more ways that bring value to your organization.
Modernize
A solid IA is the foundation for AI and hybrid cloud. Modernizing your infrastructure means building a foundation that not only takes advantage of cloud-native technologies, but also drives AI throughout the organization. IBM Storage for data and AI delivers the flexibility needed to respond to AI workloads and integrates with Kubernetes and the Red Hat® OpenShift® platform, making it easier to deploy cloud-native applications.
AI initiatives are easier and more likely to succeed if they are built on a solid foundation. IBM Storage for data and AI provides that foundation with a collection of offerings that modernize your IA and address the top business challenges associated with deploying AI workloads.
IBM Spectrum® Scale
IBM Spectrum Scale is a highly scalable, data-efficient, high-performance storage solution with enterprise security and a global parallel file system for both file and object storage data. IBM Spectrum Scale enables the unification of data across a hybrid cloud into a single scale-out storage solution for the entire data center from edge to core to public cloud. IBM Spectrum Scale is available both as a software-only solution or as an integrated appliance.
IBM Cloud® Object Storage
IBM Cloud Object Storage is a highly scalable cloud storage solution for unstructured data that provides on-premises and cloud-based dedicated services. IBM Cloud Object Storage uses an innovative approach for cost-effectively storing large volumes of unstructured data. It delivers the capabilities required to provide continuous access to data assets while improving research outcomes, decision making, business responsiveness and regulatory or legal demands.
IBM Spectrum Discover
IBM Spectrum Discover is a multisource data catalog that automatically and continuously indexes objects and files whenever changes are made using the metadata. It can also be used to create custom tags and policy-based workflows to orchestrate content inspection and activate data in AI, machine learning (ML) and analytics workflows. IBM Spectrum Discover helps enable faster AI analysis, compliance classification, image and video indexing, personal data identification, AI data pipeline integration, real-time data discovery and new insights to optimize data and find bad or duplicate data.
The decisions you make as you build your AI foundation have far-reaching implications that will impact your organization every step of the way and, ultimately, determine business outcomes. That is why having the right partner from the outset is critical.
IBM Storage for data and AI is more than a set of storage products and solutions. It consists of a storage strategy that will help you on your journey to AI and hybrid cloud. IBM continues to drive leadership for scalable, high-performance workloads as well as efficient, secure capacity storage for file and object-based solutions. Additionally, IBM Storage for data and AI solutions come ready with broad support and integration with Kubernetes and the Red Hat OpenShift platform.
Our solutions provide a flexible, high-performance IA for AI that modernizes your infrastructure with global data access and services that are simple to manage, faster to access and optimized to scale with cost efficiencies to drive down expenses and bring more value to your organization.
Contact us to learn more about IBM Storage for data and AI.
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[1] IDC White Paper, sponsored by IBM, Accelerating AI Modernization with Data Infrastructure, doc # US47460721, February 2021.
