Enterprises Turning to Cloud for Unified AI, Data Platforms
According to a new ISG report, over one-third of enterprises are expected to deploy cloud-native AI and data platforms in their information architectures by 2026. The ISG Buyers Guide™ highlights that enterprises are turning to the cloud for AI strategies due to its ability to handle large data volumes and variable workloads. The report emphasizes the convergence of cloud, AI, and data platforms, with major cloud providers offering combined capabilities.
ISG evaluated 12 providers for its 2024 Buyers Guides, naming AWS, Microsoft, and Google Cloud as leaders in Cloud-Native AI and Data Platforms, and Oracle, IBM, and AWS as leaders in AI and Data Platforms. The guides aim to help enterprises optimize their software investments in these rapidly evolving areas.
Secondo un nuovo rapporto ISG, si prevede che oltre un terzo delle imprese implementerà piattaforme AI e data native nel cloud nelle loro architetture informative entro il 2026. L'ISG Buyers Guide™ evidenzia che le imprese si stanno rivolgendo al cloud per le strategie AI grazie alla sua capacità di gestire grandi volumi di dati e carichi di lavoro variabili. Il rapporto sottolinea la convergenza tra cloud, AI e piattaforme dati, con i principali fornitori di cloud che offrono capacità integrate.
ISG ha valutato 12 fornitori per le sue Buyers Guides 2024, nominando AWS, Microsoft e Google Cloud come leader nelle Piattaforme AI e Data Native nel Cloud, e Oracle, IBM e AWS come leader nelle Piattaforme AI e Dati. Le guide mirano ad aiutare le imprese a ottimizzare i loro investimenti software in questi settori in rapida evoluzione.
Según un nuevo informe de ISG, se espera que más de un tercio de las empresas implemente plataformas de datos y AI nativas en la nube en sus arquitecturas de información para 2026. La Guía de Compradores de ISG™ destaca que las empresas están recurriendo a la nube para estrategias de AI debido a su capacidad para manejar grandes volúmenes de datos y cargas de trabajo variables. El informe enfatiza la convergencia de la nube, la AI y las plataformas de datos, con los principales proveedores de nube ofreciendo capacidades combinadas.
ISG evaluó a 12 proveedores para sus Guías de Compradores 2024, nombrando a AWS, Microsoft y Google Cloud como líderes en Plataformas de AI y Datos Nativos en la Nube, y Oracle, IBM y AWS como líderes en Plataformas de AI y Datos. Las guías tienen como objetivo ayudar a las empresas a optimizar sus inversiones en software en estas áreas de rápida evolución.
새로운 ISG 보고서에 따르면, 전체 기업의 3분의 1 이상이 2026년까지 정보 아키텍처에 클라우드 네이티브 AI 및 데이터 플랫폼을 배포할 것으로 예상됩니다. ISG 바이어스 가이드™는 기업들이 AI 전략을 위해 클라우드로 전환하고 있다고 강조하며, 이는 대량의 데이터와 가변적인 작업 부하를 처리하는 능력 덕분입니다. 이 보고서는 클라우드, AI 및 데이터 플랫폼의 융합을 강조하며, 주요 클라우드 제공업체들이 통합 기능을 제공하고 있습니다.
ISG는 2024 바이어스 가이드를 위해 12개의 공급업체를 평가하고, AWS, Microsoft 및 Google Cloud를 클라우드 네이티브 AI 및 데이터 플랫폼의 리더로 선정했습니다, 그리고 Oracle, IBM 및 AWS를 AI 및 데이터 플랫폼의 리더로 지정했습니다. 이 가이드는 기업들이 이러한 급변하는 분야에서 소프트웨어 투자 최적화에 도움이 되도록 하는 것을 목표로 하고 있습니다.
Selon un nouveau rapport d'ISG, plus d'un tiers des entreprises devraient déployer des plateformes AI et de données natives dans le cloud dans leurs architectures d'information d'ici 2026. Le Guide des Acheteurs ISG™ met en avant que les entreprises se tournent vers le cloud pour leurs stratégies AI en raison de sa capacité à gérer de grands volumes de données et des charges de travail variables. Le rapport souligne la convergence du cloud, de l'AI et des plateformes de données, les principaux fournisseurs de cloud offrant des capacités combinées.
ISG a évalué 12 fournisseurs pour ses Guides des Acheteurs 2024, nommant AWS, Microsoft et Google Cloud comme leaders dans les plateformes AI et de données natives dans le cloud, et Oracle, IBM et AWS comme leaders dans les plateformes AI et de données. Les guides visent à aider les entreprises à optimiser leurs investissements logiciels dans ces domaines en rapide évolution.
Laut eines neuen ISG-Berichts wird erwartet, dass über ein Drittel der Unternehmen bis 2026 cloud-native KI- und Datenplattformen in ihren Informationsarchitekturen implementieren wird. Der ISG Buyers Guide™ hebt hervor, dass Unternehmen auf die Cloud setzen, um KI-Strategien zu entwickeln, da sie große Datenmengen und variable Arbeitslasten bewältigen kann. Der Bericht betont die Konvergenz von Cloud, KI und Datenplattformen, wobei führende Cloud-Anbieter kombinierte Fähigkeiten anbieten.
ISG hat 12 Anbieter für seine Buyers Guides 2024 bewertet und AWS, Microsoft und Google Cloud als führend im Bereich der cloud-nativen KI- und Datenplattformen benannt, sowie Oracle, IBM und AWS als Führer bei KI- und Datenplattformen. Die Leitfäden sollen Unternehmen helfen, ihre Softwareinvestitionen in diesen sich schnell entwickelnden Bereichen zu optimieren.
- Projected growth: Over one-third of enterprises expected to adopt cloud-native AI and data platforms by 2026
- Cloud platforms well-suited for AI workloads due to elastic resource capabilities
- Major cloud providers offering integrated AI and data capabilities
- ISG's comprehensive evaluation of 12 leading providers in the market
- Significant costs associated with AI systems and data processing
- Potential inefficiencies in AI processes can exacerbate costs
- Blurring lines between AI and data platform requirements may complicate decision-making
The shift towards cloud-native AI and data platforms marks a significant trend in enterprise technology adoption. With over one-third of enterprises projected to deploy these platforms by 2026, we're witnessing a transformation in how businesses approach AI and data management. This move is driven by the need for scalable computing resources to handle the massive data volumes required for AI models.
The convergence of cloud, AI and data capabilities offered by major providers like AWS, Microsoft and Google Cloud is reshaping the competitive landscape. This trend could potentially reduce barriers to entry for AI adoption among enterprises, as it simplifies the integration of these technologies. However, organizations must carefully evaluate the total cost of ownership, considering both the benefits of elasticity and the potential for cost escalation due to inefficiencies in data processing and AI workloads.
The blurring lines between AI platforms and data platforms represent a significant shift in enterprise architecture. This convergence is driving the development of more intelligent operational applications that can leverage AI insights in real-time. The traditional approach of separating operational and analytical workloads is being challenged, which could lead to more efficient and responsive business processes.
However, this integration also raises concerns about performance management and the potential for analytical workloads to impact critical operational systems. Enterprises will need to carefully consider their data architecture strategies to balance the benefits of integrated platforms against the risks of performance degradation. The emphasis on cloud-native solutions also highlights the growing importance of multi-cloud and hybrid cloud strategies in enterprise IT planning.
Through 2026, more than one-third of enterprises will deploy cloud-native AI and data platforms in information architectures, a new ISG report says.
The ISG Buyers Guide™ for Cloud-Native AI and Data Platforms, produced by ISG Software Research, projects that through 2026, more than one-third of enterprises will deploy cloud-native AI and data platforms in their information architectures. Most leading cloud providers offer both AI and data capabilities, while independent software providers offer AI and data platforms built to operate natively in and across cloud environments, the report says.
The report points out that AI requires large amounts of high-quality data that needs to be prepared, engineered and organized to feed and train AI models. The volumes of data necessary for accurate AI models place a significant demand on computing resources, which can often be best met with elastic cloud platforms. The cost of these systems can be significant, and any inefficiencies in the process can exacerbate the costs, the report says.
“AI workloads are highly variable and require large amounts of compute resources, making them ideal for the cloud environment,” said David Menninger, executive director, ISG Software Research. “Cloud, AI and data platforms should be evaluated together, rather than independently, to make the most informed decisions when selecting software providers.”
The increasing importance of intelligent operational applications driven by AI insights is blurring the lines that have traditionally divided the requirements for AI platforms and data platforms, the report says. While there have always been general-purpose databases that could be used for both analytic and operational workloads, traditional architectures have involved the extraction, transformation and loading of data from the operational data platform into an external analytic or AI platform. This enables the operational and analytic workloads to run concurrently without adversely impacting each other, protecting the performance of both.
The report notes the importance of coordinating cloud, AI and data efforts. Cloud platform providers have recognized the opportunity to help enterprises with this convergence, and all the top cloud providers are offering platforms that combine AI and data capabilities.
The Cloud-Native AI and Data Platform Buyers Guide includes an evaluation of platforms that provide three sets of capabilities: cloud, AI and data. To be considered for inclusion in this Buyers Guide, a product must offer services addressing key elements of cloud platforms that:
- Support a combination of public, private and hybrid cloud workloads;
- Include a general-purpose data platform, database, database management system, data warehouse, data lake or data lakehouse;
- Include data persistence, data management, data processing and data query functionality;
- Support database administrator, developer, data engineering and data architect functionality, and
- Support the AI-related capabilities of data preparation, AI/ML modeling, AutoML, GenAI, developer and data scientist tooling, MLOps/LLMOps, model deployment, model tuning and optimization.
A related report, the AI and Data Platform Buyers Guide, evaluates platforms that provide both AI and data capabilities. To be considered for inclusion in this Buyers Guide, a product must be marketed as a general-purpose data platform, database, database management system, data warehouse, data lake or data lakehouse. The primary use case is to support worker- and customer-facing operational applications and/or analytics workloads such as business intelligence or data science. The product should provide data persistence, data management, data processing and data query; database administrator functionality; developer functionality; data engineering functionality, and data architect functionality. It must also support AI-related capabilities, including data preparation, AI/ML modeling, AutoML, GenAI, developer and data scientist tooling, MLOps/LLMOps, model deployment, model tuning and optimization.
For its 2024 Buyers Guides, ISG assessed 12 providers: Alibaba Cloud, AWS, Cloudera, Databricks, Google Cloud, IBM, Microsoft, Oracle, Salesforce, SAP, Snowflake and Teradata.
ISG Software Research designates the top three software providers as Leaders in each category. For the 2024 studies, the leading providers in ranked order are:
Cloud-Native AI and Data Platforms: AWS, Microsoft and Google Cloud
AI and Data Platforms: Oracle, IBM and AWS
“The ability to meet enterprise needs for a unified AI and data platforms that can operate natively in or across cloud computing environments is now a key priority for assessing and selecting software products,” said Mark Smith, partner, ISG Software Research. “Our unique, groundbreaking research provides valuable insights to support that process.”
The ISG Buyers Guides™ for both Cloud-Native AI and Data Platforms and AI and Data Platforms are the distillation of more than a year of market and product research efforts. The research is not sponsored nor influenced by software providers and is conducted solely to help enterprises optimize their business and IT software investments.
Visit this webpage to learn more about the Buyers Guides for Cloud-Native AI and Data Platforms and AI and Data Platforms and read executive summaries of each of the reports. The complete reports, including provider rankings across seven product and customer experience dimensions and detailed research findings on each provider, are available by contacting ISG Software Research.
Organizations seeking guidance on Generative AI service providers can explore existing ISG Provider Lens™ research, upcoming studies and additional details in this digital brochure.
About ISG Software Research
ISG Software Research, previously Ventana Research, provides authoritative market research and coverage of the business and IT software industry. It distributes research and insights daily through its user community, and provides a portfolio of consulting, advisory, research and education services for enterprises, software and service providers, and investment firms. Its on-demand service provides structured education and advisory support through subject-matter experts. ISG Buyers Guides™ support the RFI/RFP process and help enterprises evaluate and select software providers through tailored assessment services and the ISG Software Research Value Index methodology. Visit www.ventanaresearch.com for more information and to sign up for free community membership.
About ISG
ISG (Information Services Group) (Nasdaq: III) is a leading global technology research and advisory firm. A trusted business partner to more than 900 clients, including more than 75 of the world’s top 100 enterprises, ISG is committed to helping corporations, public sector organizations, and service and technology providers achieve operational excellence and faster growth. The firm specializes in digital transformation services, including AI and automation, cloud and data analytics; sourcing advisory; managed governance and risk services; network carrier services; strategy and operations design; change management; market intelligence and technology research and analysis. Founded in 2006, and based in
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