Telecom operators are accelerating investments in artificial intelligence to build self-managing networks that deliver immediate financial returns, according to industry research published this week.
A Nvidia survey conducted between September and November 2025 found that nine out of ten telecommunications companies report positive revenue and cost impacts from AI deployments. The study gathered responses from 1,038 management and technical professionals across internet service providers, network equipment manufacturers, and system integrators.
Autonomous networks emerged as the top return-on-investment application, cited by half of respondents as their primary focus area. These AI-driven systems can self-configure, self-heal, and self-optimize with minimal human intervention.
Improved customer service ranked second at 41 percent, followed by internal process optimization at 33 percent.
Budget commitments reflect growing confidence in the technology's business value. Eighty-nine percent of surveyed organizations plan to increase their AI spending over the next twelve months, up sharply from 65 percent in last year's survey.
Thirty-five percent anticipate budget increases exceeding ten percent from current levels.
"Autonomous networks deliver immediate ROI by eliminating human effort from repetitive, reactive workflows," said Sebastian Barros, managing director of Singapore-based communications provider Circles in an interview. "The fastest impact areas are energy management, fault prediction, configuration drift correction and capacity planning."
The shift toward automation comes as more than seventy percent of companies across all industries now use artificial intelligence internally for various applications according to legal analysis. This widespread adoption creates new governance challenges around patent protection, solicitor-client privilege maintenance, and confidential information security when data flows through third-party AI tools.
Telecom operators currently operate mostly at lower autonomy levels within the TM Forum's five-tier framework. Eighty-eight percent of organizations report being between levels one and three, where systems provide recommendations but require human approval for significant actions.
Generative and agentic AI technologies to accelerate progress toward fully autonomous level five networks.
"Agentic AI accelerates this by coordinating decisions across domains in real time," said Chetan Sharma, CEO of Chetan Sharma Consulting in the same report. "Generative AI delivered fast productivity gains, but agentic AI is where telecoms begin to see structural ROI."
The telecommunications findings contrast with emerging workplace challenges documented in other sectors. Research published in Harvard Business Review indicates that while generative AI speeds individual tasks, it often leads to increased overall workloads as employees spend more time reviewing and correcting machine-generated outputs.
Software engineer Siddhant Khare described this phenomenon in an essay on AI fatigue: "AI reduces the cost of production but increases the cost of coordination, review, and decision-making. And those costs fall entirely on the human." His experience mirrors broader patterns where workers transition from creators to quality inspectors managing continuous machine output streams.
Despite these implementation challenges across different industries, economic projections remain optimistic about artificial intelligence's long-term impact. Canadian forecasts suggest the technology could add approximately 41,500 net new jobs annually while boosting national GDP by as much as nine percent through additional economic output approaching $298 billion by 2035.
Cambodian Deputy Prime Minister Vongsey Vissoth recently described artificial intelligence as a major economic growth driver for the next ten to twenty years during a government training session in Phnom Penh. He emphasized that countries failing to invest risk falling behind technologically and economically.
The European Union continues developing its artificial intelligence strategy focused on supporting domestic companies through improved data access and infrastructure investment according to analysis from Brussels-based economic researchers. Their approach aims to balance innovation with regulatory oversight through mechanisms like the EU AI Act implemented in 2024.
The industry's direction is clear: a Nvidia survey found that nine out of ten telecommunications companies already report positive revenue and cost impacts from their AI deployments.
