Generative artificial intelligence (AI), renowned for its prowess to produce fresh content like conversations, narratives, graphics, videos, melodies, and programming, is becoming an increasingly popular subject in the telecommunications space. Recent projections indicate an immense potential for growth in its use.

A survey with Altman Solon has revealed that up to 48% of telecommunication experts are likely to adopt generative AI within two years, a promising rise from the current 19%.

Initially, generative AI will likely tap into existing models and resources, especially in the customer experience (CX) domain. Many telecommunications companies are already utilizing AI to enhance communications and increase efficiency. An impressive 92% of those surveyed picked high likelihoods for implementation in customer service and chatbots. Among these, 63% shared that the implementation process is already in progress. The introduction of generative AI could map out smoother interaction paths with real-time call evaluation and interactive voice response, assisting agents in quick issue resolution.

The second phase will involve meticulously tweaking these models to meet specific telecommunication objectives using proprietary data. A recent example of this is the remarkable venture by Snowflake and DigitalRoute, merging data from billing support systems (BSS) and operational support systems (OSS). Using Llama 2, an open-source foundation model created by Meta, more ease in identifying and addressing network issues impacting vital clients is attainable.

A final wave will prioritize creating new industry-specific foundation models, focusing on telecommunication data. A significant 65% of telcos anticipate training ready-made models to match their requirements. An eager 15% expressed a desire to build foundation models from within. This creates a promising avenue for AI software vendors and early telecommunication adapters to collaborate on designing new foundation models that can cater to network function software design and network failure resolution.

A successful implementation strategy begins with a strong foundational data strategy, as generative AI heavily relies on the quality of data it uses and the platform it is built on.

However, data protection is another significant area of concern. According to our survey, nearly 61% of telcos express anxiety about data security, privacy, and governance with generative AI. This necessitates a team capable of addressing these security risks comprehensively involving IT leaders, business leaders, security teams, compliance teams, and legal teams.

Apart from overall security, companies must also consider the regulations with data usage and future ownership claims. It’s crucial that businesses perform thorough assessments of their data organization, data platform strategy, and ensured return on investment. Nonetheless, generative AI extends exceptional opportunities in its wide range of applications, advancing the technological transformations of our times. Hence, it is a tool businesses ought to explore.