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As organizations continue to adapt to the rapidly changing landscape of technology, data and analytics (D&A) remain central to their operations. Gartner’s latest report highlights key trends that D&A leaders should embrace to stay ahead in 2025. With AI emerging as the dominant force, businesses are focusing on utilizing AI-driven solutions to optimize data handling and enhance decision-making. In this article, we explore the top D&A trends identified by Gartner, including the rise of AI agents, the growing importance of small language models, and other strategies that will shape the future of business analytics.
Key Trends in Data & Analytics for 2025
Gartner has outlined nine trends for D&A leaders to follow, with AI technologies leading the charge. One of the most significant trends is the rise of agentic AI, which is gradually being integrated into various sectors, automating tasks, and optimizing business processes. D&A leaders are advised to leverage AI agents to streamline data sharing and automate decision-making processes, creating closed-loop outcomes driven by continuous data insights.
Another prominent trend is the shift toward small language models (SLMs). Unlike large language models (LLMs), SLMs are more cost-effective, faster to train, and better suited for specific tasks. Gartner encourages D&A leaders to explore SLMs for more accurate, context-aware AI outputs.
In addition, composite AI is gaining traction as organizations seek to combine multiple AI techniques to improve technological efficiency. Beyond generative AI and LLMs, businesses are encouraged to incorporate machine learning and data science to strengthen their AI capabilities.
Gartner also points out the growing importance of synthetic data, which helps fill gaps in datasets, particularly in AI projects where complete, organized data is crucial. Synthetic data is also valuable for protecting privacy by replacing sensitive information.
Other notable trends include metadata management tools, which help automate the analysis and use of metadata for data cataloging, data lineage, and AI-driven applications. Decision intelligence platforms and highly consumable data products are also on the rise, emphasizing smarter decision-making and the creation of reusable data assets that enhance business outcomes.
What Undercode Says:
Gartner’s trends clearly showcase a profound shift in how data and analytics will be used in the near future, with AI technologies driving most of the innovation. Let’s break down some of the major points and explore the implications of these trends in more detail.
AI Agents Take Over
AI agents are poised to revolutionize how businesses handle data and make decisions. These autonomous systems are already being integrated into operations to help streamline workflows and enhance efficiency. By automating data access and decision-making, organizations can free up valuable human resources and focus on higher-level strategic initiatives. This shift represents not just a technological advancement, but a cultural one, as businesses move away from traditional methods of data management and embrace automation.
The Shift from LLMs to SLMs
While large language models (LLMs) garnered significant attention in recent years, there’s a growing recognition of the benefits of smaller, more specialized models. SLMs offer faster training times, lower costs, and more accurate outputs for specific tasks, which is a win for businesses that need tailored solutions. This shift could signal the rise of more niche, application-specific AI tools, which could democratize access to AI by making it more affordable for smaller organizations and specialized use cases.
Composite AI: A Holistic Approach
The idea of composite AI, which involves using a combination of AI techniques, is gaining traction as organizations seek to optimize their AI strategies. While generative AI and machine learning have taken center stage, combining these technologies with other data science methodologies can provide a more holistic and effective approach to problem-solving. This trend suggests that businesses will need to broaden their understanding of AI and incorporate a wider range of tools to stay competitive.
Synthetic Data as a Privacy Solution
As concerns about data privacy continue to grow, synthetic data presents an innovative solution. By creating artificial datasets that mirror real-world data, businesses can protect sensitive information while still reaping the benefits of advanced analytics and AI. This trend highlights the importance of balancing innovation with privacy concerns, and organizations that can navigate this challenge will likely gain a competitive edge.
Metadata Management and Decision Intelligence
The rise of metadata management tools reflects the increasing complexity of data ecosystems. With data coming from various sources and formats, it’s essential to have tools that can organize, categorize, and make sense of it all. Furthermore, decision intelligence platforms represent a strategic shift in how organizations view data: not just as raw material for analysis, but as a key driver of smarter, more informed decisions. These platforms will enable businesses to act on data more effectively, leading to improved outcomes and a better bottom line.
Fact Checker Results:
- AI Agents: The trend of AI agents revolutionizing business operations is backed by growing adoption across sectors. It’s clear that automation and autonomous assistance are becoming vital to business strategies.
- Small Language Models: The shift from LLMs to SLMs is a practical move, given the smaller models’ cost-effectiveness and greater suitability for specific tasks. This trend aligns with Gartner’s predictions.
- Synthetic Data: The use of synthetic data to address privacy concerns is not just feasible but increasingly critical in the context of AI deployments. Organizations are already experimenting with synthetic datasets for privacy and data completeness.
References:
Reported By: https://www.zdnet.com/article/gartners-top-trends-in-data-and-analytics-for-2025-include-ai-agents/
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