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COINTURK FINANCE > Business > Telecom Operators Invest in AI for Enhanced Efficiency and Returns
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Telecom Operators Invest in AI for Enhanced Efficiency and Returns

Overview

  • Telecom companies are increasingly investing in AI for operational efficiency.

  • Network automation and internal optimization lead AI's ROI in telecom.

  • Autonomous networks are viewed as the future, despite existing constraints.

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Telecom companies are increasingly harnessing the capabilities of artificial intelligence (AI) to streamline operations and achieve substantial cost savings. A recent survey by Nvidia (NASDAQ:NVDA) shows a significant shift in how AI is being deployed, with results now being the main focus rather than just theoretical discussions. This trend highlights the growing importance of AI across various sectors within the telecom industry, providing both financial and operational benefits. Additionally, newer AI applications are being prioritized over traditional uses like customer service, bringing a fresh momentum to the industry.

Given the ongoing advancements in AI technology from years past, AI’s role in enhancing network and operational efficiency has gained momentum. Previously, customer service improvements were highlighted as primary contributors to AI’s value in telecom, but now, processes like network automation and internal process optimization are at the forefront, reflecting a deeper integration of AI across various sectors.

Contents
What Drives the ROI Shift?Are Internal Operations Overtaking Customer Service?Will Autonomous Networks Become a Reality?

What Drives the ROI Shift?

Nvidia’s insights indicate that network automation and internal process enhancements are eclipsing customer service chatbots as primary AI return on investment (ROI) sources. An impressive 50% of survey respondents prioritized network automation, underscoring the strategic shift toward optimizing network infrastructure as an AI application with significant leverage. Telecom operators are applying AI to predictive maintenance, traffic optimization, and spectrum allocation, aiming to reduce outages and energy consumption while improving overall efficiency.

Collaborations such as Ericsson’s with Mistral AI are focusing on integrating AI in network operations rather than public-facing AI models. This highlights the industry’s demand for more robust network management tools. On a similar note, AT&T is employing its Geo Modeler tool to test infrastructure deployment scenarios, ultimately aiming to save millions in capital expenditure through precise simulations.

Are Internal Operations Overtaking Customer Service?

AI utility is broadening to encompass billing reconciliation, workforce management, and fraud prevention, going beyond customer service improvements. Nvidia’s survey portrays a scenario where telecom operators leverage AI to streamline internal processes and achieve immediate, tangible benefits in efficiency. Automating processes in complex back-office operations helps reduce manual interventions and shortens operational cycle durations.

PYMNTS reports that AT&T’s deployment of AI agents to combat fraud is indicative of investment shifts focusing on internal efficiency. These agents analyze patterns in real-time and adapt dynamically, ensuring risk mitigation and improving operating margins amid high capital investment needs.

AT&T emphasizes the financial leverage of fraud prevention:

“These are capital allocation decisions measured in millions of dollars, underscoring why network-focused AI initiatives are becoming strategic priorities.”

Will Autonomous Networks Become a Reality?

The roadmap for telecom operators extends towards the realm of autonomous networks capable of managing themselves with minimal oversight. This ambition, informed by Nvidia’s findings, resonates with industry expectations of AI-native networks preceding the arrival of 6G technology. Bain’s analysis cautions that full autonomy involves significant hurdles, yet targeted AI initiatives are creating pathways toward more intent-driven network management.

Ericsson emphasizes embedding intelligence within network management:

“The emphasis is not on consumer-facing generative AI interfaces, but on embedding intelligence inside network management systems.”

AI’s integration into telecom operations signifies a pivotal shift towards more efficient, data-driven decision-making approaches. As telecom companies continue to explore AI applications, the focus remains on internal optimizations and network management, creating an ecosystem concentrated on robust, reliable systems rather than mere surface-level enhancements.

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Disclaimer: The information contained in this article does not constitute investment advice. Investors should be aware that cryptocurrencies carry high volatility and therefore risk, and should conduct their own research.

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