Edge AI: A game changer for telecoms and ODMs

Edge AI is a crucial step for AI-connected living. It also introduces challenges that telecoms and original design manufacturers need to be wary of to thrive in the era to come.

The introduction of “intelligence on the edge” (or “edge AI”) is a game-changer for telecommunications providers, the customers they serve, and the original design manufacturers (ODM) telecom relies on. By processing data closer to where it is generated and consumed, intelligence on the edge meets today’s need for faster data handling, minimizing latency and enhancing real-time decision-making. It’s also a key step in what we call AI-connected living —enabling the integration required for interconnected environments in smart homes, cities or factories.

But for all the benefits edge AI delivers to telecommunications businesses, their customers and ODMs, it also introduces challenges that these organizations need to be wary of in order to thrive in the era to come.

Empowering telecoms and ODMs

The benefits of intelligence on the edge for telecom businesses are clear. With this technology, they can deliver the following:

1. An enhanced customer experience: With edge computing, telecom operators can offer services with lower latency and higher reliability. This is particularly crucial for applications such as autonomous vehicles, smart cities and Internet of Things (IoT) devices, where real-time data processing is essential.
   
   For their part, telecom customers can offer highly personalized experiences. Whether it's tailored content recommendations or proactive healthcare monitoring, the ability to process data locally ensures that services are both timely and relevant.
   
   
2. Operational efficiency: By processing data at the edge, telecom businesses can reduce the load on their core networks, leading to cost savings and improved network performance. This efficiency gain allows operators to allocate resources more effectively and focus on innovation.
   
   
3. New revenue streams: The integration of AI at the edge opens up new opportunities for telecom businesses to offer value-added services such as predictive maintenance and personalized customer experiences.

For original design manufacturers, meanwhile, edge AI offers both opportunities and challenges. Increased demand for edge-enabled devices will create a profitable market for ODMs. At the same time, traditional devices will ultimately be replaced with smarter alternatives, leading to market cannibalization.

ODMs will need to invest in research and development to stay competitive by differentiating their products with edge computing features. Additionally, ODMs will need to collaborate with telecom businesses and technology providers to create solutions that deliver on the promise of AI-connected living.

Top four considerations for implementing edge AI

Edge AI represents a dramatic shift for the telecom industry and the businesses they serve. As we move closer to realizing its potential, telecom businesses, ODMs and their customers will need to consider the following:

1. Integration. Distributed networks will require new devices, local servers and specialized hardware to support on-site processing. Additionally, integration with existing technology infrastructures will likely require technical expertise to ensure seamless operation and compatibility.
   
   
2. Privacy and security. Businesses will need to be vigilant about detecting vulnerabilities within the edge AI ecosystem and implementing comprehensive security protocols to mitigate risks. This includes regular security audits, encryption and access controls to ensure data integrity and confidentiality.
   
   
3. Scalability and cost-effectiveness. To determine the most viable solutions for their organizations, businesses will need to carefully evaluate the total cost of ownership, including hardware, software, maintenance and support.
   
   
4. Ethics. Businesses should approach implementation responsibly, adhering to ethical guidelines and minimizing potential negative impacts. Best practices include transparent communication with stakeholders, compliance with data protection regulations, and open discussion of the broader societal implications of AI deployment.

Delivering on AI-connected living with edge AI

As intelligence on the edge gains traction, it will disrupt the telecommunications industry and enable a new era of AI-connected living. Telecom businesses and ODMs that embrace its potential will be poised to unlock the full benefits of this transformative technology.

Cognizant has reimagined the traditional CPU-based customer premise equipment with the industry’s first Reference Design Kit (RDK) customer premise equipment, running on an Nvidia GPU and AI-tech-stack-powered edge appliance.

In collaboration with Nvidia, Cognizant has delivered a new class of AI-native customer-premise equipment, designed to handle today’s edge workloads. With over 600 companies in the RDK community, it is set to drive the next generation of AI-native CPE devices, transforming customer experience, optimizing home networks, and accelerating adoption and innovation.