How Generative AI Is Reshaping Data Management: our key takeaways from the Gartner 2025 Predictions.
The data management landscape is on the cusp of a transformation, driven by generative AI (GenAI). According to the Gartner recent report, "Predicts 2025: 4 Ways AI Will Disrupt Data Management Markets and Solutions, predictions will help data management leaders plan for the disruptive impact of generative AI on their data management solutions, architectures, operating models, skills and use cases.”
Ready to dive into 4 Ways AI Will Disrupt Data Management Markets and Solutions? Read the Gartner® full report here.
Here’s what we feel, data leaders need to know.
1. The Shift Toward Unified Data Ecosystems
Historically, organizations have struggled with fragmented data management tools, leading to high integration costs and inefficiencies.
What This Means for Enterprises:
- Stop investing in isolated point solutions; instead, adopt platforms that offer integrated data management capabilities.
- Leverage GenAI-powered data fabric to automate metadata management and improve data governance.
2. AI-Augmented Data Engineering & Integration
GenAI is rapidly transforming data engineering workflows. Large language models (LLMs) are already being embedded into platforms to automate data ingestion, transformation, and policy definition.
Key Recommendations:
- Adopt AI-enhanced data integration tools to simplify engineering tasks and accelerate data pipeline development.
- Invest in metadata management to ensure LLM-driven query generation remains accurate and reliable.
3. Democratization of Data with Natural Language Interfaces
A major breakthrough in data accessibility is the rise of natural language-driven data interactions. Business users and citizen data scientists will be able to leverage AI-driven assistants to generate SQL queries, automate reports, and interact with data platforms without deep technical expertise.
Action Items for Data Leaders:
Implement self-service data preparation tools enhanced with LLMs to empower non-technical users.
Ensure your data ecosystem supports retrieval-augmented generation (RAG) to enhance AI-driven decision-making.
4. AI-Optimized Cloud Financial Management (FinOps)
Managing cloud data costs is becoming increasingly complex, but GenAI-powered FinOps tools are emerging to address this challenge. Organizations will be able to use natural language interfaces to identify cost-saving opportunities and automate optimization efforts.
Steps to Take Now:
- Gartner suggests, “Prepare for next-generation CFM by seeking out CFM/FinOps vendors with an established roadmap for delivering AI- and GenAI-enhanced tooling and instrumentation.”
- Use active metadata to measure business value and optimize cloud spending dynamically.
5. GenAI Business Applications Will Be Built on Existing Data Platforms
Rather than adopting standalone AI solutions, enterprises will build GenAI applications directly on their existing data management platforms
How to Prepare:
- Evaluate whether your current data management platform can support GenAI use cases like knowledge retrieval and automated analytics.
- Prioritize RAG-as-a-service capabilities within your existing data ecosystem to ensure seamless AI integration.
The Future of Data Management Is AI-Driven
The rapid evolution of GenAI is forcing data leaders to rethink their strategies. By embracing AI-powered automation, self-service analytics, and cost optimization tools, organizations can unlock new efficiencies and drive innovation. The key to success lies in adopting an AI-ready data ecosystem that can support the next wave of intelligent applications.
Is your organization prepared for the future of AI-driven data management? Explore how EDB’s advanced PostgreSQL solutions can help you navigate this shift and stay ahead of the competition.
Discover 4 Ways AI Will Disrupt Data Management Markets and Solutions. Read the Gartner® full report here.
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Gartner, Predicts 2025: 4 Ways AI Will Disrupt Data Management Markets and Solutions, By Ehtisham Zaidi, Robert Thanaraj, Adam Ronthal, Xingyu Gu, Nina Showell, Thornton Craig, Michele Launi, Roxane Edjlali, 9 December 2024
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