Do you want artificial intelligence? Here’s how to prepare your data and infrastructure for AI
Artificial intelligence (AI) is reshaping our world. In business, this places IT managers in one of the most pivotal organizational roles today. IT managers are responsible for much more than IT infrastructure; They must drive adoption of innovative technology and partner closely with their data scientists and engineers to make AI a reality – all while keeping costs low and cyber resilient.
This is a big role. And it’s getting bigger. Artificial Intelligence and its unprecedented potential to transform businesses is increasing the CIO’s influence and responsibility within the organization.
For IT managers, building an AI-powered organization at scale can be challenging. However, organizations are more prepared than you might think, thanks to the data they already have. The key is to make data actionable for AI by implementing a comprehensive data management strategy. This is because data is often stored on-premises, in multiple clouds, and at the edge. Getting the right and optimal responses from GenAI models requires fine-tuning to industry and company-specific data. Companies need the right data management strategy and tool chain to discover, ingest, and process that data with high performance.
Without data, there is no AI, and breaking down these silos is the first step toward bringing AI to your data wherever it exists. Successful data management includes the ability to handle the exponential growth of data, regardless of data type and location, while appropriately managing the lifecycle of that data. Traditionally, data management and underlying infrastructure, including storage and compute, have been viewed as separate IT initiatives. In order for IT managers to set up their organizations for success and bring AI into their data, a more holistic view of IT infrastructure and data management is needed.
Building an AI-enabled solutionIn today’s rapidly evolving IT environments, crafting an AI-ready solution can be a competitive advantage. Beyond the traditional considerations of speeds and feeding, forward-thinking IT managers must ensure that their computing and storage hardware is scalable. This includes a robust infrastructure with the core principles of scale, security and performance, all at optimized costs. This infrastructure must be adequate to handle the exponential growth of data, especially with unstructured data. An estimated 90% of the global data landscape consists of unstructured data1. It grows at an estimated rate of 55-65%.2 Year after year and three times faster than structured data.
Unstructured data is often AI-ready, yet it holds some of the most value for organizations. Data scientists and IT teams must work together to prepare all their data and make it actionable, leveraging high-performance, scalable infrastructure to push AI forward. Once AI-optimized compute and storage are in place, IT managers can begin implementing a modern data warehouse as part of their overall data management strategy. Data scientists and engineers spend approximately 80% of their time preparing data3
Instead of actual analysis. Modern data warehouses enable the use of open data formats and distributed datasets across core, edge, and multi-cloud environments. This eliminates the hassle of data silos and makes data accessible for model training, analytics, and real-time inference. As a result, data scientists and engineers can query their data across environments and get AI insights faster.
You might be interested in Dell’s upcoming 30-minute online event on “AI Anywhere on Data Everywhere” on December 7y It’s 11 a.m. Central time. I’ll be there and love tOh do you have Joined.
Adopt real-time cyber protectionAs IT managers design and engineer AI-ready infrastructure, the underlying principle is data security. Cybercrime is on the rise and carries huge costs, expected to reach $10.5 trillion by 2025.4 So far about 76%5 Of organizations have already been subjected to a ransomware attack. Now, attackers specifically target unstructured data because of its sheer volume and the high-value information it contains.
To secure data and build resilience in the face of a persistent and escalating threat landscape, IT managers must put security at the forefront of AI deployments. This requires a dynamic, comprehensive, multi-layered approach to cybersecurity.
At Dell Technologies, best practices start with a comprehensive cybersecurity assessment through a Zero Trust lens. Next, AI-based threat and ransomware detection software is integrated into cyber protection solutions that allow organizations to analyze suspicious activity in real-time. If a threat is detected, proactive responses are activated to reduce the spread of the threat. In the unfortunate event of a cyber attack, cyber resilience services help speed up recovery time and restore operations quickly.
Make AI a reality for your organizationWhen you create a modern, secure data and AI solution, deployments at scale become possible. Today it is only about 12%6 of organizations have advanced AI to the point of transforming businesses. At the same time about 50%7 Many organizations have short-term plans to do so. The stakes are high, and those organizations working to accelerate the potential of AI are poised to emerge as tomorrow’s leaders.
That’s why Dell Technologies is ready with in-house experts, a secure, AI-ready data platform, and an open ecosystem of partners to help enable and advance AI journeys. These capabilities help organizations simplify data discovery, preparation, and management to unleash game-changing innovations in AI. Dell’s mission is to inspire organizations – across industries and sizes – to improve business outcomes by bringing AI to their data at any scale.
Please join me at our Dell event “AI Anywhere on Data Everywhere” on December 7thy From 11:00 a.m. to 11:30 a.m. Central time to learn more about how to make your data actionable for AI.
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(1) IDC white paper “High Data Growth and Modern Applications”; July 2022
(2) https://www.everestgrp.com/2021-07-intelligent-document-processing-idp-adoption-swells-as-enterprises-seek-to-lower-costs-through-automation-idp-market-to-grow- 55-65-next-year-press-release-.html
(3) Gartner Survey Analysis: Data Governance Struggles to Balance Innovation and Control. March 19, 2020
(4) Cybersecurity Projects 2022: eSentire | Official cybercrime report for 2022
(5) ProofPoint: 2023 State of Phishing Report