For modern telecom providers, enabling a flexible, cloud-native, intelligent infrastructure is a path to both reduced operational costs and new revenue generation. But to truly harness the power of that digital transformation, operators also need to revolutionize their back office—and generational AI (GenAI) is a powerful tool to enable just that.
Operating at scale using large language models (LLMs), GenAI brings a host of game-changing functionality to both BSS and OSS, driving smarter and more secure networks.
Supercharging Customer Relationships—and Revenue
It's no secret that automation optimizes productivity. But with GenAI in the BSS mix, automation can be applied to even complex tasks that involve several different platforms, and lead to significant growth opportunities.
Tasks like managing multichannel customer interactions, fraud detection and remediation, and providing data analysis that streamlines billing and revenue assurance can all be transformed through GenAI, allowing for better employee efficiency and productivity, and more time to focus on high-value projects.
One success story is Lumen Technologies, which offers networking, edge, cloud, security, collaboration and managed services to help businesses grow and operate more efficiently. It was among the first companies to join Microsoft 365 Copilot for its Early Access Program in spring 2023. Microsoft 365 Copilot, Microsoft's GenAI agent, has since then played a critical role in the provider's evolution from a traditional telecom to a technology company, including on the back-office front.
For instance, it has implemented Microsoft 365 Copilot and Microsoft Dynamics 365, an integrated suite of enterprise resource planning and customer relationship management applications, to transform its customer service teams. Improvements include automating note taking and administrative tasks, creating presentations and proposals, and building comprehensive customer and prospect profiles.
“With a simple prompt in Microsoft 365 Copilot, we can ask questions about personas, the business, even their financials, and it summarizes that into one simple document, saving our folks time because they’re more informed and walking into meetings better prepared,” explained Delvin Holman, senior lead customer service enablement manager at Lumen. “And that’s helping us at Lumen sell more, as well.”
And indeed, using Microsoft 365 Copilot in customer experience efforts has reduced the time it takes for a seller to prepare for customer outreach from four hours to just 15 minutes. Lumen estimates that four hours saved per week comes out to about $50 million in revenue over a 12-month period.
Supercharging OSS
In OSS, GenAI plays a crucial role in network optimization, monitoring and managing telecom networks in real time. One of GenAI's most powerful OSS functionalities for example is predictive analytics and maintenance, which involves analyzing vast amounts of real-time information from network components, along with historical data on past outages or service disruptions and predicting potential network failures.
From there, it can recommend preventive measures, and proactively resolve issues before they impact performance. The result? Reduced operational costs and downtime, improved reliability, and happier customers.
GenAI-powered systems can also automate routine tasks like provisioning, fault detection, troubleshooting, capacity planning, and load balancing.
Bell Canada for instance is using GenAI to predict weather events that could lead to network outages, like snowstorms and periods of high winds. The operator is also overhauling its network incident-response processes for business customers by implementing connecting OSS data and other resources to automate scheduling and reduce drive time for repairmen.
GenAI: Driving Double-Digit Telco Operational Improvements
Bell Canada and Lumen join AT&T, SK Telecom, Vodafone and others in launching comprehensive GenAI initiatives. The word from these early adopters is that BSS/OSS improvements can help telecoms cut their operational costs by up to 50%, and lead to outstanding customer service and revenue outcomes.
According to a McKinsey survey of 130 telcos globally earlier this year, many early adopters are experiencing "significant double-digit percentage impact" through the use of GenAI. One European telco said that using GenAI to personalize content has improved marketing conversion rates by 40% (alongside significant cost reduction); and a Latin American provider increased call center agent productivity by 25% by using GenAI-driven recommendations for guiding the customer journey.
For Lumen, the real-world outcomes are impressive: In all, the carrier has already racked up $5 billion in new business that it attributes directly to the use of GenAI, and it expects to log $7 billion more in the near term.
It's clear that GenAI is an invaluable tool for igniting telecom business growth, and it's clear that the next generation of operators will use it as the beating heart of their BSS and OSS strategies. It's also poised to operationalize massive, brand-new revenue streams in a vertical that has seen saturation and stagnating growth for decades for traditional communications services.
As an example, Lumen's embrace of GenAI enables it to deliver novel, advanced capabilities to customers. In August, Lumen established a new Custom Networks Division to meet demand for AI-enabled connectivity from hyperscalers and other large enterprises. The division will provide customized network solutions that include dark fiber and custom fiber routes to support AI-intensive workloads, and for securing data center connectivity with advanced data protection.
"The chance for telcos to make this change has never been more accessible," according to the McKinsey survey report. "The industry has struggled these last 10-plus years to achieve the potential of 'traditional' AI, given the complexity and legacy processes involved. In addition to the significant impact gen AI can bring to bear with entirely new use cases and applications, its ability to learn from vast amounts of diverse data and interact in near-human-like ways may be the tipping point for accelerating broader AI programs and the building blocks that enable them, fueling company-wide transformations."