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|Publication Date:||3Q 2020|
This Omdia report covers a new arena of competition in the enterprise information and communications technology (ICT) industry. Technologies such as Kubernetes have made hybrid and distributed cloud infrastructures more manageable and operationally agile. The emerging Internet of Things (IoT) has led to a proliferation of connected sensors and also connected effectors such as robots. Meanwhile, 5G wireless networks have begun to appear within enterprises. These networks provide dramatically lower latency, enabling new applications in industrial control systems, robotics, autonomous vehicles, and augmented/ virtual reality (AR/VR). As a result, it is a competitive necessity for applications to migrate closer to the end user to fully benefit from lower latency.
The combination of these trends with one more—artificial intelligence (AI)—means that the edge is becoming to the 2020s what the cloud was to the 2010s: the strategic focus of competition in the ICT sector. The applications that enterprises want to deploy at the edge are ones that benefit from the spectacular improvements in AI and machine learning (ML) technologies seen in the 2010s—for example, machine vision, robotics, and time-series data analysis. Having proven itself in the cloud, AI is coming to the edge.
Players from multiple markets are being drawn to this new opportunity. Communications service providers (CSPs), the network vendors that support them, and a new breed of alternative service providers all hope that their expertise in wireless will permit them to own the edge. Semiconductor makers and server OEMs see a major new line of business for their existing server products. Hyperscale cloud providers see a potential disruption of their business model built on centralized data centers and managed services and hope to preempt it by leading the charge to the edge.
Key Questions Addressed:
- Which players are competing in the emerging 5G edge space?
- How do AI, private 5G networks, and edge computing interrelate?
- What are the typical use cases and what role does AI play in them?
- What are the various business and operating models, and which players prefer which models?
- What strategies are the major cloud providers pursuing?
Who Needs This Report?
- Artificial intelligence and machine learning practitioners
- Communications service providers
- Enterprises in vertical industries
- Semiconductor vendors
- Investor community
Table of Contents
Rise of the cutting edge
Edge computing as a driver of AI adoption
Understanding the competitive space
How this space differs from the broader AI market
“Data is the new oil”: Jealously guarded, dangerous if leaked?
Latency is king, so hot chips will only get us so far
Algorithms may be less important than adaptation
Conclusions and recommendations
For hardware vendors
For cloud service provider
For software vendors
List of Charts, Figures, and Tables
- AI chipsets for the edge are set to boom
- Edge servers are likely to be the key category in the enterprise
- Chipset revenue for edge servers
- Global enterprise LTE and 5G projects by type
- Global enterprise LTE and 5G projects by industry
- Players converge on the new opportunity space
- Business and delivery model scenarios
- AI business models by software vendor revenue, 2018–25 forecast
- Enterprises choose the multi-party option for 5G projects
- Four scenarios for the edge AI operating model
- Major applications and edge AI opportunities