The technology industry continues to be a hotbed of innovation, driven by technological advances, increased connectivity, the urgency to make companies more efficient and competitive in an ever-changing marketplace, and the growing importance of technologies such as: activities are promoted by Machine learning, natural language processing, data analytics, predictive analytics. These technologies enable network administrators to optimize network performance, automate routine tasks, improve security, and improve overall network management efficiency. According to GlobalData’s report on “Innovation in Artificial Intelligence: AI-Assisted Network Management,” over 3.6 million patents have been filed and granted in the technology industry in the past three years alone.
However, not all innovations are the same, nor do they follow a constant upward trend. Instead, their evolution takes the form of an sigmoidal curve that reflects a typical life cycle from early emergence to accelerated introduction and finally to reaching stable maturity.
Identifying specific innovations, especially those in the emerging and accelerating stages, is essential to understanding the current level of adoption and the expected future trajectory and impact.
Over 300 innovations shape the tech industry
GlobalData’s Technology Foresights uses an innovation strength model built on over 2.5 million patents to plot the S-curve of the tech industry, with more than 300 areas of innovation shaping the industry’s future.
Within emerging The innovation stage, finite element simulations, ML-enabled blockchain networks, and generative adversarial networks (GANs) are disruptive technologies that are in the early stages of application and should be followed closely. Demand forecasting applications, intelligent embedded systems, and deep reinforcement learning are some of them. To accelerate An area of innovation where adoption is steadily increasing.in mature Innovation areas, wearable physiological monitors, smart lighting and smart climate control systems are now well established in the industry.
The S-curve of innovation artificial intelligence in the technology industry
Network management powered by AI is an important area of innovation for artificial intelligence
AI-assisted network management refers to the use of artificial intelligence (AI) algorithms and technologies to automate and enhance network operations and management processes. This includes automating tasks such as analyzing network data, predicting network performance, troubleshooting, configuration, and policy enforcement. By embedding AI, organizations can streamline network management, reduce operating costs, and improve overall performance.
GlobalData’s analysis also reveals the companies at the forefront of each innovation area and assesses the potential scope and impact of patent activity across different applications and geographies. According to GlobalData, there are more than 240 companies working on the development and application of AI-assisted network management, ranging from technology vendors, established technology companies, and up-and-coming startups.
Leader in AI-assisted network management – a disruptive innovation in the tech industry
‘Application Diversity’ measures the number of different applications identified for each relevant patent and broadly divides companies into ‘niche’ or ‘diverse’ innovators.
“Geographic coverage” refers to the number of different countries in which each relevant patent is registered, reflecting the breadth of intended geographic application, ranging from “global” to “local” .
Number of patents related to AI-assisted network management
Source: GlobalData Patent Analytics
Cisco is one of the leading patent applicants in AI-assisted network management. The company’s patents are for dependency mapping of applications that can be automated within a network. Networks can capture traffic data for flows traversing the network using sensor networks that provide multiple perspectives on the traffic. Networks can analyze traffic data to identify network endpoints.can also identify Specific network configurations from traffic data, such as load balancing and subnetting schemes.
A network can partition endpoints based on network configuration and perform similarity measurements of endpoints within each partition to determine clusters for each partition. Clusters make up the nodes of the Application Dependency Map, and relationships between clusters can be made up to make up the edges of the Application Dependency Map.
Other prominent patent applicants in the AI-assisted network management field include Huawei and International Business Machines (IBM).
In terms of geographic deployment, Ipanema Technologies leads the way, followed by Adaptive Spectrum and Signal Alignment (ASSIA) and Permutive. In terms of application diversity, Ayyeka Technologies takes the top spot, followed by AO Kaspersky Lab and Amazon.
AI-assisted network management provides automated processes, improves network performance, enhances security, optimizes resource allocation, and enables data-driven decision making. By leveraging AI algorithms and technology, organizations can transform network operations, improve productivity, reduce costs, and gain an edge in a rapidly evolving digital environment.
To better understand how artificial intelligence is transforming the tech industry, visit GlobalData’s latest Thematic Research Report on Artificial Intelligence (AI) – Thematic Intelligence.
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GlobalData, a leading provider of industry intelligence, provided the underlying data, research, and analysis used to create this article.
GlobalData’s Patent Analytics tracks patent filings and grants from offices around the world. We use text analysis and formal patent taxonomies to group patents into key subject areas and associate them with specific companies across the world’s largest industries.
