MQTT Trends for 2025 and Beyond: Powering the Future of AI and IoT

Rethinking MQTT for a More Intelligent and Connected Future

The Internet of Things (IoT) is no longer on the horizon—it’s here, growing rapidly with billions of devices already connected and billions more on the way. At the center of this explosion is MQTT (Message Queuing Telemetry Transport), a protocol originally designed for lightweight, reliable messaging in constrained environments. As the IoT landscape evolves, driven by the rise of AI, real-time data demands, and global scale, MQTT is transforming from a simple telemetry tool into a critical infrastructure layer for modern intelligent systems.

Here’s a look at how MQTT is changing and what trends to watch in 2025.

Laying the Foundation: Protocol and Transport Evolution

• Smarter Transport with MQTT over QUIC

  While MQTT has traditionally run over TCP, its limitations in mobile and unstable networks are becoming more apparent. MQTT over QUIC offers a faster, more resilient alternative, using UDP to improve connection setup times and reduce latency. It’s particularly valuable for applications like connected vehicles or remote industrial deployments. EMQX is the first broker to support this transport method, with standardization efforts ongoing through the OASIS MQTT Technical Committee.

  Learn more: MQTT over QUIC: Next-Generation IoT Standard Protocol

• What’s Next for the Protocol: MQTT 5.1 and Beyond

  MQTT 5.0 introduced features like topic aliases, session expiry, and shared subscriptions. Future enhancements aim to improve performance and control, including subscription filters for more targeted message delivery and batch publishing to reduce transmission overhead. These changes are being actively shaped by vendor implementations and community input, with additional focus on MQTT-SN for ultra-constrained devices.

  Learn more: MQTT 5.0: 7 New Features and a Migration Checklist

Scaling for Speed: Real-Time Messaging and Streaming

• Introducing MQTT/RT

  MQTT/RT proposes a real-time messaging layer designed for latency-sensitive use cases like robotics, autonomous systems, and industrial automation. It supports peer-to-peer architectures and diverse transports such as UDP and shared memory, making it a compelling option when traditional broker models become bottlenecks.

  Learn more: MQTT/RT Documentations

• Bringing Streaming Capabilities to MQTT

  Many IoT systems today rely on Kafka to handle high-throughput data. MQTT Streams aims to simplify that architecture by integrating similar capabilities, such as message replay, persistence, and deduplication, directly into MQTT brokers. This consolidation could reduce infrastructure complexity without sacrificing performance.

  Learn more: MQTT Queues and Streams Documentations

• Reliable File Transfers Over MQTT

  Standard MQTT isn’t ideal for large files like firmware updates or diagnostic logs. Extensions like those from EMQX enable chunked, resumable transfers using the existing MQTT framework. This approach avoids the need for separate tools like FTP or HTTP, simplifying the overall system architecture.

  Learn more: File Transfer over MQTT: Transfer Large Payloads via One Protocol with Ease

Enabling Smarter Systems: MQTT and AI Integration

• Connecting AI Models with MCP over MQTT

  The Model Context Protocol (MCP) helps standardize how AI models interact with other systems. Running MCP over MQTT allows low-power and intermittently connected devices to communicate with AI services in real time. EMQ is already building this into its MQTTX client, including natural language interfaces that let users control devices through AI agents.

  Learn more: MCP over MQTT: Empowering Agentic IoT with EMQX for AI-Driven Intelligence

• MQTT as the Communication Backbone for AI

  As AI becomes more embedded in industrial and consumer systems, MQTT plays a central role. It delivers sensor data for predictive maintenance, supports inter-device coordination in robotics, connects distributed AI models at the edge, and enables real-time data flow for digital twin simulations.

  Learn more: Integrating MQTT with AI and LLMs in IoT: Best Practices and Future Perspectives

Preparing for Scale: MQTT in Complex Ecosystems

• Serverless MQTT for Agile Deployments

  Platforms like EMQX Serverless make it easy to spin up MQTT services without managing infrastructure. This model is ideal for fast-moving projects, pilot programs, and small teams that need to prototype quickly and scale as needed.

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• Supporting Multiple Users with Multi-Tenancy

  Multi-tenant MQTT deployments allow different applications or users to share a broker while keeping data secure and organized. This reduces overhead and simplifies operations for large-scale platforms.

  Learn more: Multi-Tenancy Architecture in MQTT: Key Points, Benefits, and Challenges

• Global MQTT Networks through Geo-Distribution

  Distributed MQTT clusters can serve clients around the world with low latency and high availability. EMQX’s Cluster Linking feature synchronizes data across regions, supporting real-time use cases like connected vehicles and global manufacturing systems.

  Learn more: Beyond Boundaries: Exploring Geo-Distribution in EMQX for Enhanced Scalability

• Unifying Industrial Data with UNS and Sparkplug

  In industrial environments, Unified Namespace (UNS) has become a popular architecture for structuring OT and IT data. MQTT brokers often serve as the foundation for these systems. Sparkplug3.0 adds standardization to the mix, defining payload formats and device state protocols to support true interoperability.

  Learn more: 4 Reasons Why You Should Adopt MQTT in Unified Namespace

• Integrating with Enterprise Systems

  MQTT is increasingly connected to enterprise platforms like Apache Kafka and AMQP-based tools such as RabbitMQ. These integrations create flexible, end-to-end pipelines that support real-time data processing, event-driven workflows, and long-term analytics.

  Learn more: EMQX Data Integration

Powering the Edge: Real-Time Processing Where It Matters Most

Edge computing reduces latency and bandwidth use by processing data closer to the source. MQTT complements this by serving as the local messaging layer between devices, gateways, and the cloud. Together, they enable real-time automation, edge AI, and system resilience even when cloud connectivity is limited.

Bidirectional communication is especially important in edge scenarios, allowing not just data collection but also commands, model updates, and remote firmware delivery.

Learn more: MQTT for Edge Computing Solution

How to Prepare: Strategic Recommendations for 2025

• Adopt MQTT 5.0 to access the full suite of modern features
• Evaluate MQTT over QUIC for mobile or unreliable networks
• Build edge strategies that include local MQTT brokers
• Experiment with MCP over MQTT for AI and natural language interfaces
• Explore serverless and distributed options for agility and scale
• Monitor protocol developments from the OASIS MQTT Technical Committee
• Apply multi-layered security practices across your MQTT ecosystem

MQTT’s Role in the Next Generation of Connected Systems

MQTT is no longer just a lightweight protocol for telemetry. It is evolving into a foundational layer for intelligent, real-time, and scalable systems across IoT, AI, and edge computing. The organizations that invest in these capabilities now will be better equipped to lead the next era of innovation in connected technology.