HONG KONG, July 4, 2025 /PRNewswire/ — On June 28, Tencent Cloud released a newsletter titled Data + AI: Build NextGen Data Intelligence Platform featuring Gartner® research, analyzing the pain points enterprises face in the era of generative AI. It also provides a comprehensive overview of Tencent Cloud’s Data + AI product matrix which offers integrated solutions to help enterprises tackle these challenges.
The newsletter points out that in the AI era, the focus of corporate competition is shifting from “model competition” to “competition for high-value data assets” as data quality has often become the core bottleneck in AI development. Enterprises urgently need to build systematic data engineering capabilities to unlock the potential of AI through continuous data iteration and optimization, rather than frequent model adjustments.
The newsletter also cites how traditional data platforms face significant challenges in meeting the demands of generative AI. The challenges include large amounts of unstructured data lying dormant, disconnections between data and AI development leading to long deployment cycles, batch processing struggling to deliver real-time responses, inconsistent data standards across departments causing governance challenges and compliance risks, and business personnel highly dependent on IT for data access, resulting in slow responses.
Gartner research shows that organizations deploying retrieval-augmented generation (RAG) pipelines for their generative AI applications need access to unstructured data, which constitutes 70% to 90% of the data in organizations today[1]. By 2027, the IT spending focused on multistructured data management will account for 40% of total IT spending on data management technologies and services.[2]
To address these challenges, the newsletter proposes that enterprises need to build a Data + AI integrated platform. The key capabilities of such a platform include the composability of data and AI technologies, end-to-end lifecycle development from data to AI and business integration, processing and enhancement of multimodal data, and unified metadata-driven governance and compliance.
Among them, the composability of data and AI technologies has become a core capability. LLMs undergo generational upgrades every 3 to 5 months, and technologies such as vector search and lakehouse architectures are advancing rapidly. In this context, enterprises need to build a “pluggable” architecture.
Meanwhile, the end-to-end lifecycle from Data to AI management has become a standard practice, involving data processing, model construction, and business integration. For example, in the financial industry, real-time data pipelines are used to integrate multi-source data, enabling rapid iteration of risk models and reducing the compliance response time from months to hours.
Multimodal data processing capabilities define the upper limit of value. AI applications need to integrate structured and unstructured data to transform diverse types of data, such as text, images, and videos, into “intelligent fuel.” For example, retail companies can integrate online and offline multimodal data to create 360-degree customer profiles, driving a more than 30% increase in precision marketing efficiency.
In addition, the introduction of Agentic Analytics enables intelligent automated decision-making. For example, AI agents are used to identify and repair faulty data and dynamically track data lineage.
Tencent Cloud is committed to building efficient and intelligent enterprise-level infrastructure for enterprises through the deep integration of data and AI technologies. The Data + AI capacity of Tencent Cloud takes data management as its core and integrates products and services such as AI computing power, data storage and analysis, data governance, security management, AI model training, and real-time decision-making. It provides an end-to-end solution from data ingestion to intelligent applications.
According to the 2024 Gartner Data and Analytics Governance Survey, almost half of the respondents identify “difficulty in standardizing data across different departments/BUs” as among their organizations’ top D&A governance-related challenges.[3]
In practical implementation, Tencent Cloud WeData one-stop intelligent data platform enables enterprises to seamlessly manage the entire data-to-AI lifecycle. At the data layer, DataOps ensures real-time integration of multi-source data and automated data pipelining, while built-in intelligent quality monitoring intercepts abnormal data. This is combined with a unified semantic layer that consolidates enterprise-level metrics and data models. At the AI layer, MLOps integrates with popular machine learning frameworks to support the automation of key processes, from feature engineering and model training to online inference.
Building on a unified data development experience, Tencent Cloud’s ChatBI and data analysis agent significantly lower the barriers to data applications. Business personnel can automatically generate visual reports through simple conversations, increasing demand response speed by 10 times. Tencent Cloud WeData Agent, powered by LLMs, proactively executes tasks such as automatically fixing data pipeline issues and predicting storage bottlenecks to allow for early scaling, showcasing the practical value of agent-driven analytics.
In the future, the Data + AI platform will evolve toward natural language interaction, AI-driven automated optimization, and deep integration with generative AI. Gartner forecasts that by 2028, 80% of GenAI business applications will be developed on organizations’ existing data management platforms, reducing implementation complexity and time to delivery by 50%.[4]
GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.
About Tencent Cloud:
Tencent Cloud, one of the world’s leading cloud companies, is committed to creating innovative solutions to resolve real-world issues and enabling digital transformation for smart industries. Through our extensive global infrastructure, Tencent Cloud provides businesses across the globe with stable and secure industry-leading cloud products and services, leveraging technological advancements such as cloud computing, Big Data analytics, AI, IoT, and network security. It is our constant mission to meet the needs of industries across the board, including the fields of gaming, media and entertainment, finance, healthcare, property, retail, travel, and transportation.
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[1]Gartner Inc., Develop Unstructured Data Management Capabilities to Support GenAI-Ready Data，G00821728, Sharat Menon, Radu Miclaus |
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[2]Gartner Inc., Emerging Tech: Data Fabrics with Multimodal Data Focus for Generative AI-Enabled Applications，G00818141, Radu Miclaus, Sharat Menon |
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[3]Gartner Inc., Market Guide for Agentic Analytics，G00824122, Anirudh Ganeshan, Souparna Palit, |
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[4]Data Management Is the Sole Differentiator in a Commoditized and Multipolar LLM World, G00828308, By Xingyu Gu, Mark Beyer, |
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SOURCE Tencent Cloud
