Mobile World Congress (MWC) 2024, held earlier this year in Barcelona, Spain, was all about the growing impact of AI in the telecommunications industry. The event showcased how AI advancements are poised to boost efficiency and productivity and drive innovation in new areas.

Generative AI (GenAI) was a central topic, dominating the exhibition halls, panel discussions, and keynote speeches. Despite the enthusiasm for AI, industry experts questioned whether telcos have the foundational components to support these AI-driven ambitions. Many discussions aligned with Quantexa's mission to help companies harness and maximize AI's potential by addressing core data-quality issues and ensuring that data-driven decisions are reliable and impactful.

The data-quality dilemma

Leaders from companies like AT&T, Orange, and Telefonica discussed data quality and management challenges in the context of AI integration. Telcos have vast amounts of data, but poor data quality remains a significant barrier to successful AI implementation.

Steve Jarrett, Orange's chief AI officer, discussed the importance of "data democracy." The core idea is that high-quality data needs to be accessible across business functions. This approach makes it easier to put more AI use cases into production throughout the organization.

However, telcos are not new to AI, having used it across various business functions for some time. AT&T has a rich history with AI dating back to the 1950s, largely through its R&D arm Bell Labs (now part of Nokia). The company was instrumental in early machine learning research.

Today, telcos like Telefonica have significantly embraced AI. In the past decade, more than 500 AI applications have been deployed, ranging from network optimization to enhancing critical infrastructure security. This demonstrates how telcos can leverage AI to improve operational efficiency and bolster key business areas.

Putting generative AI into action

One of AI's key promises is to solve complex problems by analyzing large volumes of data, recognizing intricate patterns, and applying complex rules or contexts. AT&T discussed its generative AI tool, "ASK AT&T," as an example of a strategic application to support data-driven decision-making. This tool is designed to optimize knowledge management and enhance employee productivity while keeping data within governance parameters.

Broader AI advancements were also discussed, including techniques like Retrieval-Augmented Generation (RAG), which improves the accuracy of large language models by incorporating information retrieval through knowledge graphs. This approach allows telcos to embed their specific domain knowledge into AI, leading to more accurate and contextually relevant results. However, the chief data officer of Telefonica warned that even with the benefits of RAG, the effectiveness of GenAI still depends on maintaining high data quality at the foundational level.

It's time to put a greater emphasis on ESG

In other news, environmental, social, and corporate governance (ESG) moved considerably further up the agenda. Telcos openly discussed their dedication to transparency and accountability within their ESG initiatives. High-profile commitments, such as the one from Orange Business and Cisco, were spotlighted at MWC. The two companies have entered a memorandum of understanding to reduce greenhouse gas emissions by leveraging shared expertise and resources. Their collaboration specifically targets the complex issue of Scope 3 emissions. Scope 3 emissions are defined by the U.S. Environmental Protection Agency as emissions that "are the result of activities from assets not owned or controlled by the reporting organization, but that the organization indirectly affects in its value chain."

These partnerships highlight a growing recognition within the industry of the need to establish a robust ecosystem to address environmental impacts. This approach goes well beyond individual company boundaries, extending into the collective effects of the supply chain. Accurate ESG reporting is crucial in this context and will require telcos to enhance data precision and meet goals and regulatory standards.

A call to focus on data management

As we look forward to the next Mobile World Congress, it is crucial that we address the issue of data management. Without the proper establishment of foundational components and practices related to data management, it will be difficult to accomplish much regarding this year's AI-related initiatives. The success of these efforts will be heavily dependent on the quality of the underlying data.