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Communications service providers (CSPs) are at an inflection point. From stagnant revenues, to network pressures to meet 5G demands, to the challenge of delivering innovative customer experiences, the telecom industry is under enormous pressure to transform.
Over the past few years, CSPs around the world have turned to artificial intelligence (AI) to address some of these challenges, but the vast majority of operators' operating expenses are still spent on infrastructure and data management. This limits their ability to leverage core data assets and develop differentiated customer experiences that meet individual needs.
Enter generative artificial intelligence, a type of machine intelligence that has received a lot of attention lately. We've all marveled at its ability to generate text that reads like a human, create new images, and even build musical scores. It is a fascinating addition to the AI toolset and complements machine learning (ML) and its ability to recognize patterns to make predictions, discover efficiencies, or interpret large datasets.
But while there is a lot of hype surrounding generative AI, at Google Cloud we look at it through a more pragmatic lens of the telecom industry. Generative AI can accelerate transformations already underway, with the potential to simplify many of the tools and processes CSPs use on a daily basis, bringing a new level of natural interaction between humans and computers, and enabling machines to be programmed to perform a task Manipulates verbal requests and responds in a natural, interactive manner.
Generative AI builds on existing Google Cloud data, AI and ML services:
For example, call center AI, which enables human-like interactions between callers and computers, has been successfully adopted by CSPs for years, increasing customer and call center worker satisfaction.
When we add generative AI to this technology, CSPs and their customers will see greater capabilities and impact, for example, virtual agents can not only provide useful information, but also allow customers to make payments and perform other transactions. With generative AI, CSPs will be able to leverage customer call summaries to better understand customer sentiment and identify cross-sell and up-sell opportunities.
CSPs can also easily and quickly build and deploy virtual agents that inform customer conversations, enabling more innovative and personalized customer interactions. And that's just the beginning.
Three Focus Areas
The contact center is just one of the areas where practical and generative AI will help drive new value. When reflecting on the major challenges facing CSPs today, three areas where generative AI could be transformative stand out:
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Personalized experience : In addition to further improving customer call center interactions, generative AI can also provide better personalization in e-commerce interactions—an important factor in helping customers choose phone calls and calling plans. Personalization is also important for reducing churn, offering relevant new services and managing the customer lifecycle. For example, generative AI could enable CSPs to craft campaign content tailored to specific topics and target individual customers with customized text and images.
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Autonomous Networks : Generative AI will also help to provide AI for AI by connecting multiple complex AI/ML models used in network planning and operations with large language models (LLMs) that can understand network behavior and plan actions in areas such as network capacity. Autonomous networks pave the way for planning and performance. For example, generative AI will enable CSPs to train models using customer experience and sentiment data to build better predictive capabilities. Importantly, the customer data sets used to tune these models are not public, but curated internal customer data—significantly enhancing privacy, authenticity, and relevance while protecting intellectual property. Additionally, generative AI will be able to aid in network planning and design, which requires high-level reporting and analysis.
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Streamline operations : Operations center uptime and field service efficiency are critical to managing costs and improving customer satisfaction. In particular, applying generative AI to field service equipment could speed up diagnosis and analysis, even help with installation, parts, and troubleshooting, and minimize the number of times companies have to send out trucks and improve field service training. Generative AI will also increase the productivity of the IT development process, supporting code generation and troubleshooting to deliver reliable software products and services.
Data is safe and reliable
An under-discussed area in generative AI is the importance of data quality and data security in building and training the LLMs that power the technology. Many CSPs are concerned that intellectual property will leak into and out of LLM, compromising the security of their systems and intellectual property. We have long provided industry-leading data security and privacy technology, and through generative AI integrated with Vertex AI, we can ensure that all data is safe in the CSP environment.
At the same time, to ensure their LLMs generate accurate information, CSPs are building scenarios and use cases to train on smaller, controlled amounts of their own data, sometimes with input from partners and others. Highly trusted source. Google Cloud also provides tools like Prompt Engineering, Tuning, and Reinforcement Learning from Human Feedback to further ensure data authenticity and reliability. This could lead to the first generative AI applications for smaller, higher-impact problems, such as optimizing network topology.
Human Factors
Of course, people are critical to the success of generative AI, whether it’s solving a problem in a call center, field service workers combining AI information with their own expertise, marketing and creative teams brainstorming with generative AI for new presentations and marketing materials, or operations engineers adding and approving AI suggestions. We've built a lot of amazing technology to help enhance what humans couldn't: synthesize millions of records and assets to help inspire new workflows and productivity.
Telecommunications is a rapidly changing industry, tech-savvy and eager to learn and deploy the best new technologies, which includes generative artificial intelligence. Every meeting with a CSP sparks new ideas, sparks more use cases, and leads to more industry-changing initiatives. It's exciting to see this rate of change, and we're just getting started.