Gartner research: Find the right ecosystem to succeed at the edge

25 July 2025
Alex Grawe Alex Grawe

Enterprise usage of edge computing is growing, and the requirements of Edge AI only makes the needs stronger. According to recent research from Gartner1, the share of organizations using edge computing will increase from 20% to 50% by 2029 and 60% of those deployments will use some form of AI.

Incorporating research across multiple disciplines and several surveys of IT leaders, Gartner has identified several recommendations for leaders to consider as they develop a strategy for leveraging edge computing, including:

  • Build a strategic plan to accelerate adoption of edge computing.
  • Focus on platforms, frameworks, and interoperability in the early stages to enable future expansion and scalability.
  • Choose partners that have broad market potential and maintain a fallback migration strategy.
  • Architect for flexibility by choosing solutions based on the offering’s ecosystem of partners.

Based on our experience at Cumulocity, these recommendations are spot on. Critically for AIoT and IoT solutions, an edge computing deployment is not about the right vendor but rather the right ecosystem. Connected solutions require a connected ecosystem.

The crux of a strong platform provider for AIoT is the ability of the platform to collect, store, and transfer data from a variety of sources; that is the key strength of Cumulocity DataHub. But there is more to a successful AIoT solution. AIoT requires:

  • Hardware: Physical assets outfitted with reliable sensors to generate data about real-time operating conditions.
  • IoT Platform: An application that provides built-in tools and capabilities to connect every “thing” in an ecosystem, providing functions including device lifecycle management, device communication, data management, integration, and application enablement.
  • Analytics/AI: By leveraging advanced algorithms, AIoT systems analyze vast amounts of data from IoT devices in real-time, allowing for faster decision-making. This enables use cases such as predictive maintenance, anomaly detection, and vision AI.
  • Deployment from edge to cloud: To optimize performance of AIoT, you must be able to operate at both the edge and the cloud. Running on the cloud provides scalable storage and processing capabilities, while running on the edge reduces latency and improves real-time decision-making capabilities, particularly in areas with limited connectivity. The ideal solution allows you to efficiently manage your solution across the edge-to-cloud continuum.

At Cumulocity, we are proud to work with an ecosystem of providers that help our customers in every aspect of their deployments. Our Device Catalog includes certified, fully integrated devices from leading vendors like Kunbus, Advantech, and Insys. Our Solution Partners include strong AI and analytics applications like those from Boon Logic. Strong system integration partners like Accenture and Inetum support deployments from edge to cloud. Cumulocity is a fully cloud-agnostic platform that works with all major hyperscalers and can be purchased through their marketplaces.

We are excited about all the things our customers are empowered to do as part of our connected ecosystem, and we’d love to talk with you about how Cumulocity and our partners can help your business.

Interested in joining the Cumulocity partner ecosystem? Register here.

1Gartner, Market Guide for Edge Computing, By  Thomas Bittman et. al, 16 June 2025

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