AI-Native Telco: Radical Change to Prosper in Challenging Times

Telecom Business Review | Saturday, July 27, 2024

Telecom companies can grow margins and protect core revenues with the help of artificial intelligence when deployed at scale. This opportunity, however, requires an entirely different approach.

FREMONT, CA: AI is unlocking use cases altering sectors across a broad swath of the global economy, from infrastructure that "self-heals" to completely reinvented (and touchless) customer service and experience, from large-scale hyper-personalization to automatically generated marketing messages and visuals utilizing Generative AI technologies such as ChatGPT all a reality today. These AI technologies can supplement and occasionally outperform conventional business functions significantly.

The effect of these solutions is becoming increasingly apparent. AI leaders—the top quintile of organizations that have taken the McKinsey Analytics Quotient evaluation—have had a five-year revenue CAGR that is 2.1 times greater than that of peers and a total shareholder return that is 2.5 times greater.

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Given the multiple issues the telecom sector has faced recently, such as declining revenues and ROIC, one could assume that the industry has already adopted this technology. Telcos have yet to completely embrace AI and an AI-centric approach. Instead, models are created once and are not modified as the business environment evolves. Machine learning (ML) is merely in name, restricting the system's capacity to learn from experience. Regrettably, AI expenditures are frequently misaligned with top-level management priorities; with such sponsorship, AI deployments stop, investment in technical expertise declines, and the technology stays mature.

Compare this disconnected condition to an AI-native organization. AI is a critical capability that drives decision-making across all organizational divisions and levels. Investing in AI is necessary to enable most C-suite initiatives, such as more tailored customer suggestions and faster response times in call centers. Champions of crucial AI initiatives are senior executives. Data and AI capabilities are administered as scalable and reusable goods. Even AI product managers working on core products are lauded for the organizational benefits they generate.

This level of AI maturity is difficult, but telcos can do so. In light of all the constraints businesses face, embracing large-scale AI deployment and migrating to AI-native status could be crucial to driving growth and revitalization. Telcos beginning to understand that this is non-negotiable, are increasing their AI expenditures as the business impact of the technology materializes.

The rationale for native AI integration

The following factors encourage this trend by telecommunications companies:

Increasing accessibility of leading AI technology:  AI-native firms such as Meta continue to expand the open-source ecosystem by making widely available new programming languages, data sets, and algorithms, thereby increasing the accessibility of top AI technologies. In tandem, cloud providers have developed several machine-learning APIs with rapid deployments, such as Google Cloud's Natural Language API. API provides access to generative AI technologies, such as ChatGPT, that may generate engaging responses to human queries. Along with the declining data processing and storage costs, these two aspects make it easier for businesses to implement AI.

The rapid proliferation of valuable data: Operators can collect, organize, and utilize more data than ever. This information comprises dataflows from unique app usage patterns, site-specific customer experience scores, and what may be purchased from or shared with third parties. A framework to govern the ethical deployment of AI is necessary for telcos to address consumers' and regulators' privacy concerns.

Validated usage scenarios and results: AI-Native enterprises across industries have implemented AI to accomplish four objectives relevant to operators around the globe: revenue protection and growth through personalization; cost structure transformation; seamless customer experience; and meeting new workplace demands. The operators can learn from them all. Streaming players, for instance, have been recognized for a long time for providing curated, individualized content recommendations based on previous user activity. To optimize cost and offer a flawless customer experience, one of the largest insurance providers in the United States uses AI assistants to reduce or even eliminate human contact when consumers buy coverage or cancel plans with other carriers. In turn, several of the world's greatest technology businesses are renowned for employing AI to highlight the characteristics of excellent managers and high-performing teams and then leveraging these insights to train corporate leaders.

Investments in technology are acknowledged as a business driver: In a post-pandemic environment, investors and executives agree that technology expenditures are not merely a cost center but a primary business driver with significant effects on the bottom line. IT spending is projected to increase by more than 5 percent in 2023, despite economic uncertainty and worries of a recession, with technology leaders under increasing pressure to demonstrate financial benefit.

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