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ISG research shows enterprises are aligning AI and data platforms to scale AI deployments with accuracy, compliance, and real-time results. The 2026 ISG Buyers Guides evaluate 83 providers for AI and data management in enterprise environments.
Enterprises are increasingly aligning their AI and data platforms as they move beyond experimental AI initiatives toward large-scale, production deployments. New research from Information Services Group (ISG) highlights the growing need for cohesive systems that deliver real-time, relevant, and personalized AI outcomes while maintaining accuracy and regulatory compliance.
Many organizations face difficulties with siloed, inconsistent, and inaccessible data when attempting to scale AI. This data often requires extensive cleaning, organization, and compliance measures before it can effectively support AI models. As AI use cases expand and demand higher volumes of data, infrastructure costs rise, making close coordination between AI and data platforms essential for operational efficiency.
“As organizations take AI programs beyond experimentation, they need enterprise-grade software to build and maintain both AI models and the data those models use,” said Matt Aslett, director of research, Analytics and Data, at ISG. “There are a growing number of options, including integrated AI and data platforms and specialized tools that can be aligned with a coordinated AI strategy. Successful scaled deployments require careful planning and platform selection.”
Enterprises are seeking AI platforms capable of efficiently preparing, training, deploying, and maintaining models while applying strong governance and monitoring. At the same time, data platforms must ensure data validity and trust. The demand for real-time, personalized results in areas such as pricing, recommendations, fraud detection, and forecasting is blurring the traditional boundaries between AI and data platforms.
This shift is moving organizations away from batch-oriented analytics toward operational data platforms that can perform AI inferencing at scale. Rapid adoption of generative and agentic AI is further driving changes, with data platforms now needing to handle vector embeddings for improved natural language processing and retrieval-augmented generation. ISG expects continued development of hybrid operational and analytic processing capabilities through 2028.
The 2026 ISG Buyers Guides assess 83 software providers and their products for managing AI models and enterprise data. The series includes guides for AI platforms, emerging AI providers, AI agents, sovereign AI and data, data platforms, and emerging data providers.
Oracle was named the top Overall Leader in all AI and data platform categories for established providers. Other Overall Leaders include Databricks, IBM, AWS, and InterSystems.
In the emerging providers categories, Domino Data Lab, H2O.ai, and Hugging Face led in AI platforms, while MariaDB, Aerospike, and PingCAP led in data platforms.
Multiple providers received Exemplary or Innovative ratings across various categories, including AWS, Databricks, Google Cloud, IBM, Microsoft, Oracle, SAP, and Teradata, among others.
“Enterprises can no longer afford fragmented approaches to AI and data. They need comprehensive strategies to ensure their AI investments deliver useful, accurate results,” said David Menninger, executive director, software research, ISG. “This research provides independent insights, informed by extensive research, on platforms for all aspects of AI deployment and maintenance and the data foundations underlying those functions.”
This development is particularly relevant for organizations in SaaS, IT services, and technology sectors that rely on robust data platforms to support enterprise AI initiatives with accuracy, compliance, and scalability.
About ISG
ISG is a global AI-centered technology research and advisory firm. A trusted partner to more than 900 clients, including 75 of the world’s top 100 enterprises, ISG is a long-time leader in technology and business services that is now at the forefront of leveraging AI to help organizations achieve operational excellence and faster growth. The firm, founded in 2006, is known for its proprietary market data and research, in-depth knowledge and governance of provider ecosystems, and the expertise of its 1,500 professionals worldwide working together to help clients maximize the value of their technology investments.
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