AI And 5G-Powered Partnerships: How CSPs Are Building New Revenue Models
Collaboration between the data processing potential of AI and the low-latency connectivity offered by 5G opens up opportunities for transformation in sectors including retail, healthcare and smart cities. This article explores how communication service providers can evolve to keep up with an ever-increasing demand for fast, reliable data, and the challenges they face along the way.
The convergence of artificial intelligence (AI) and 5G technology is driving the demand for connectivity and data-driven solutions across industries. Communication service providers (CSPs) are now utilizing AI and 5G-powered partnerships to create service differentiation and innovative revenue models.
Every eight to 10 years, the telecommunications sector experiences a notable technological shift. These shifts are often driven by advancements in infrastructure, such as the transition from 3G to 4G, then to 5G networks and now the anticipated rollout of 6G.
The integration of AI into 5G is leading to smarter networks that can adapt and optimize themselves in real time, bringing about a new era of intelligent communication. According to Precedence Research, the global AI in telecommunication market is expected to grow at a CAGR of 41.4% from 2024 to 2033, with applications across network security, optimization, customer analytics, virtual assistance and self-diagnostics.
The possibilities of predictive algorithms and AI-powered systems for optimizing network performance, preventing cyber threats and bringing data computation closer to end users are wide-ranging. Summarizing its effect, Nicola Morini Bianzino, CTO at Ernst & Young, says that in the near future, it is likely that AI will drive a substantial proportion of network traffic. Therefore, businesses must strategically plan for this inevitable shift to remain innovative and competitive.
AI Complementing 5G In Transforming Industries
AI-enabled 5G offers CSPs opportunities for monetization and growth. Innovative revenue models can also help companies spread risks and insulate the business from potential downturns or disruptions that could impact the core voice and data business. Below are just a few examples of how this is occurring throughout industries.
Smart Hospitals For Enhanced Care
In today’s data-driven healthcare operations, CSPs can play a role through customized data storage and processing of network data for optimized telehealth services. For example, in a remote area with limited medical access, a local hospital can partner with a CSP to enable video-based consultations and optimized connectivity for real-time consultations and surgical guidance.
Insights-Driven Retail Experiences
CSPs can benefit from the integration of AI-enhanced connectivity in retail. AI-powered security features in 5G networks detect and mitigate threats, ensuring the protection of customer data and enabling personalized retail experiences. For example, AI-driven real-time inventory insights enabled by 5G allow retailers to optimize supply chain management and gain valuable insights into consumer preferences for tailored product offerings.
Improved Traffic Management
Smart cities are made possible by the integration of 5G, connected devices and AI. This allows for real-time data collection, storage and processing, creating revenue opportunities for CSPs. CSPs can also use their expertise to offer turnkey solutions for AI-powered systems like traffic management, providing local governments with valuable insights to optimize traffic flow and improve public safety.
Smart Grids For Energy
Smart grids use advanced analytics to optimize energy distribution, balance supply and demand, and integrate renewable energy sources effectively. For example, a utility company can implement an AI-enabled 5G smart grid for instant communication and precise demand response.
Challenges In Monetizing AI-5G Investments
CSPs face challenges as they integrate AI with 5G that can impact their ability to effectively monetize these investments. Many lack the tech capabilities to deploy and manage AI-led solutions. Here are a few key obstacles that need to be addressed to ensure the full potential of AI-5G convergence.
Network Troubles
A key challenge is to ensure that standardized interfaces are universally adopted and effectively implemented across diverse networks and platforms. Achieving seamless interoperability requires overcoming technical complexities and aligning disparate systems and protocols for smooth communication.
Technology-First Strategy
In the absence of automation tools, CSPs are likely unable to streamline operations, upgrade processes and eliminate bottlenecks. Manual interventions can hinder their ability to improve time to market.
Data Complexities
In 5G networks, data quality is a significant issue due to an abundance of data sources and fragmented storage systems. Traditional analysis tools are not suitable for addressing the scale and complexity of this data.
Cybersecurity
Security of data over AI-enabled 5G networks is crucial. Measures like encryption, audits, authentication and intrusion detection are essential against cyber threats.
Network Slicing
CSPs can create multiple virtual networks within a single physical infrastructure, each tailored to specific use cases or customer requirements. However, managing and orchestrating these network slices efficiently while ensuring quality of service presents a hurdle.
Edge Computing
Integrating edge computing capabilities into a CSP’s infrastructure is critical to ensure low-latency applications, seamless coordination between edge nodes and centralized data centers, and optimized performance and reliability.
Talent Acquisition AI-enabled 5G networks require expertise in data science, AI, network engineering and cybersecurity. CSPs need to map existing skills to new demands and fill gaps through acquisition or upskilling.
Collaborative Models For Innovative Solutions
The convergence of AI and 5G is redefining connectivity, offering opportunities for CSPs to transform customer experiences. However, deploying and managing these solutions requires expertise in cutting-edge capabilities like network virtualization, software-defined networking (SDN) and network function virtualization (NFV).
As CSPs begin their journey from legacy infrastructure to an AI-enabled 5G network and systems, it’s critical to address the challenges that might be faced. To start, CSPs aiming to foster successful innovation within their business must shift away from the traditional R&D mentality. One way this can be achieved is by participating in collaborative R&D initiatives with universities and research institutions to advance AI and 5G technologies. In this way, CSPs can introduce more customer-centric, real-time innovations.
Technology partners can also support CSPs in building advanced threat detection and prevention mechanisms, implementing encryption and authentication protocols, and conducting comprehensive risk assessments. Partnerships can further help CSPs adhere to industry standards and legal requirements, maintaining trust with customers and regulatory bodies.
A McKinsey report states that “operators have a choice: they can relegate themselves to a minor role as this transformation unfolds, or they can try to reposition themselves as 5G business builders that serve as critical partners to organizations seeking next-generation, 5G-enabled use cases, such as automated manufacturing and autonomous vehicles.”
By working to overcome these challenges, CSPs can build a technological bedrock to launch AI-led solutions and monetize 5G investments better. The time is now to prepare for a future where holographic communication, quantum encryption, and AI-driven predictive analytics will reshape how individuals and businesses interact and connect globally.
This article was written by Karthik T S from Forbes and was legally licensed through the DiveMarketplace by Industry Dive. Please direct all licensing questions to legal@industrydive.com.