By Rahul Pradhan, VP of product and strategy, Couchbase

Generative AI made waves in 2023, sparking immense excitement and leading to substantial investments through 2024 across business and verticals to leverage AI across products and business models. But as this initial excitement cools and organizations face the realities of the real impact of AI, the question that arises is what's next after chatbots and copilots. In 2025, agentic AI, an evolution of AI beyond the reactive capabilities of chatbots, is set to take center stage. These intelligent, goal-oriented agents will power significant innovation, especially by leveraging edge AI, vector databases and hybrid data models. Below, I share my top predictions for 2025 on how agentic AI will transform industries, and what foundational changes are needed to fuel its growth.

Agentic AI Poised to Power Next Wave of Innovation in 2025

Agentic AI will be the leading force in the AI industry in 2025, fundamentally reshaping what we think AI can achieve. Unlike the current iteration of AI, which is largely responsive, agentic AI is designed to understand context, establish goals and adapt actions to fulfill them autonomously. Imagine systems that do not just respond but proactively initiate solutions - these will transform both consumer and enterprise interactions.

These agents require more than just a single large language model; they rely on compound AI systems. Such systems bring together multiple models, each with specialized capabilities, and integrate them closer to data sources. They need the ability to interact with both structured and unstructured data in real-time, seamlessly making decisions with contextual awareness. All of this must be achieved while maintaining rigorous security standards and privacy controls.

The companies that excel in integrating these diverse models and infrastructures will be poised to lead the next wave of AI-driven innovation. They will provide the foundation upon which agentic AI can unlock new efficiencies and opportunities.

The Rise of Agentic AI and Compound Systems Will Fundamentally Reshape the Role of Databases

Databases are undergoing a major evolution. For agentic AI to fulfill its potential, databases must move beyond traditional architectures. In particular, the rise of compound systems means that databases must incorporate vector capabilities natively, enabling them to handle embeddings and vector searches for unstructured data. This empowers agentic AI to understand and interpret text, images and other data formats in a nuanced way, making sense of complex relationships and drawing inferences more efficiently.

Multi-model databases-supporting structured, semi-structured and unstructured data-will be crucial. They offer agentic AI a single environment from which it can retrieve data in whatever format is optimal for its task, allowing for more efficient processing and better contextual decision-making. Integration between these databases will be paramount, enabling a cohesive operation where AI agents can draw from diverse data sources to make informed, autonomous decisions.

Edge Databases Will Become Essential for AI

Edge AI will lead to a change in how data processing occurs from a centralized approach to a more distributed one. Companies will adopt edge computing for real-time decisions with minimal latency. To fully support agentic AI, the edge must become a key component of its infrastructure.

Edge databases will be a critical part of this evolution. Lightweight, resilient and capable of operating even with intermittent connectivity, these databases bring processing capabilities closer to the data source.  Edge databases allow AI applications to rapidly perceive their environment and take immediate action. By processing data at the edge, agentic AI can perform time-sensitive actions, such as managing industrial equipment or making real-time retail recommendations. Plus, edge databases provide the low-latency data access and processing required for agentic AI to truly behave as a responsive, autonomous agent. The ability to rapidly ingest, analyze and act on local data empowers agentic AI to quickly adapt to dynamic real-world conditions, a key tenet of agency.

As agentic AI proliferates, edge databases will become a critical infrastructure for powering these autonomous, intelligent applications.

Cloud Meets Edge as Hybrid Data Models Emerge

2025 will witness a significant rise in hybrid data models that operate seamlessly between the edge and the cloud. While edge databases provide real-time responsiveness crucial for autonomous decision-making, cloud systems will continue to serve as essential repositories for long-term storage, large-scale analytics, and model training. This combination allows organizations to capitalize on the strengths of both environments: the cloud's depth and computational power, and the edge's agility and immediacy.

Hybrid architectures will play a vital role in areas like autonomous vehicles, healthcare diagnostics and predictive maintenance. These applications will demand immediate responses to time-sensitive data while benefiting from the insights and depth provided by centralized analytics.

2025 Will Mark a Shift Toward Edge AI Models With Vector Databases

As AI models continue to grow in complexity and specificity, there will be a marked shift towards vector databases integrated into edge devices. Vector databases, which facilitate similarity searches across high-dimensional spaces, will power real-time insights by supporting edge AI models.

Industries like retail, logistics and healthcare will use this combination to deliver hyper-personalized experiences, optimize last-mile delivery and enhance patient monitoring. The power of vectorization - which underpins capabilities like facial recognition, product recommendations and anomaly detection - will increasingly be harnessed at the edge for on-device intelligence.

Beyond AI Chatbots: The Age of AI Agents

As we close the door on 2024, there are clear infrastructure changes that organizations will need to make to see the benefits of the rising trend that is agentic AI. In 2025, the rapid evolution of AI will hinge on foundational shifts in how data is processed, stored and leveraged. As organizations adapt to these demands, those that master their data processing, storage, and retrieval mechanisms to support low-latency, multi-model environments-while integrating edge and cloud seamlessly-will lead the charge in unleashing agentic AI's full potential. These advances will mark a new era of AI-driven transformation, unlocking unprecedented autonomy and efficiency across industries.

Organizations that get it right won't just be adopting AI-they will be empowering a new kind of AI-driven world, one where autonomous, intelligent agents reshape what's possible across sectors from healthcare to smart cities and beyond.

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ABOUT THE AUTHOR

Rahul Pradhan is VP of Product and Strategy, AI, Data and Analytics at Couchbase (NASDAQ: BASE), provider of Capella, the developer data platform architected for critical applications in our AI world, which  30% of the Fortune 100 depend on. Rahul has over 20 years of experience leading and managing both Engineering and Product teams focusing on databases, storage, networking, and security technologies in the cloud.