iWorld
Telecom sector harnesses AI for next-gen network optimization
Mumbai: Driven by technological advancement, the dawn of the 21st century has set off a new era of evolution in several industries, including the telecom sector. Hence, the future belongs to those industries which have already put in place advanced technologies like artificial intelligence(AI), machine learning, and data analytics. Among various new-age technologies, AI has gained significant traction and is transforming the telecommunications industry. Thus, with the ability to process and analyse vast amounts of data in real -time, AI has become a game changer for telecom companies.
To highlight the fact, according to Precedence Research, the global AI in the telecommunication market is witnessing exponential growth, predicted to hit around $42.66 billion by 2033. This substantial expansion is expected to grow at a CAGR of 41.40 per cent between 2024 and 2033, indicating a revolutionary moment for both Communication Service Providers (CSPs) and technology consumers.
In India, ranging from AI-powered chatbots to AI-facilitated data analysis, AI integration into telecommunications is a significant breakthrough in the industry’s development. As technology progresses rapidly, telecom operators tend to better their networks with AI powered solutions, namely to increase its effectiveness, reliability, and performance. Artificial Intelligence, with its core capabilities, is changing the way telecom networks are maintained and managed, as it enables predictive maintenance and dynamic resource allocation, ushering in a new era of connectivity and innovation.
Significance of network optimization
Network optimization in telecom is a crucial procedure, assuring optimal data flow and service reliability in an increasingly connected world. It serves as the backbone for modern telecommunications, meeting the increasing demands. However, with benefits, the telecoms business has numerous issues, the most important of which are managing increased network traffic and preserving service quality in the face of rising data consumption. In this setting, network optimization emerges as a significant answer to these problems. It ensures that consumers receive high-quality, uninterrupted services by effectively managing data traffic and network resources. This method focuses on meeting current demands while proactively planning for future development and technical advancements, making it critical to telecom networks’ resilience and adaptability in the digital age.
How AI being used in telecom
Predictive maintenance: AI-powered predictive analytics assists telecoms in providing better services by leveraging data, advanced algorithms, and machine learning approaches to forecast future outcomes based on historical data. This means that operators can utilize data-driven insights to track the status of equipment and predict failure based on patterns. Implementing AI in telecoms enables CSPs to proactively address issues with communications hardware such as cell towers, power lines, data center servers, and even set-top boxes in consumers’ homes.
Fault detection: Living in an era where fraudulent activities have become increasingly prevalent, implementation of AI in telecom fraud detection has become crucial. AI and machine learning algorithms can detect anomalies in real time, effectively minimizing telecom fraud, such as unauthorized network access and bogus profiles. The system can automatically limit access to the fraudster as soon as suspicious activity is identified, reducing the damage. According to the Communications Fraud Control Association, with a 12 per cent increase in fraud loss reported in 2023, resulting in $38.95 billion loss, AI has emerged as a potent tool in detecting and mitigating frauds.
Automate optimization and configuration: AI-powered automation solutions streamline networkconfiguration and optimization processes by autonomously adjusting network parameters and settings in response to changing conditions. Through machine learning algorithms, AI systems learn from historical data and network dynamics to optimize configurations for factors like signal coverage, interference mitigation, and load balancing. This automation enhances network efficiency, reduces operational costs, and minimizes human errors.
Power of AI: Key to success!
The adoption of AI in India’s telecommunications sector has transformed network optimization strategies, enabling operators to elevate connectivity, reliability, and performance. From predictive maintenance to dynamic resource allocation, AI-driven solutions are fueling unprecedented advancements in network management and maintenance. By harnessing AI’s power, telecom operators can deliver exceptional customer experiences, optimize resource utilization, and stay ahead of evolving market demands in the digital age.
The article has been authored by Hi-COM founder & director Vikas Sharma.
iWorld
Meta plans 8,000 layoffs in new AI-led restructuring wave
First phase from May 20 may cut 10 per cent workforce amid AI pivot.
MUMBAI: At Meta, the future may be artificial but the cuts are very real. The social media giant is reportedly preparing a fresh round of layoffs, with an initial wave expected to impact around 8,000 employees as it doubles down on its artificial intelligence ambitions. According to a Reuters report, the first phase of job cuts is slated to begin on May 20, targeting roughly 10 per cent of Meta’s global workforce. With nearly 79,000 employees on its rolls as of December 31, the move marks one of the company’s most significant workforce reductions in recent years.
And this may only be the beginning. Sources indicate that additional layoffs are being planned for the second half of the year, although the scale and timing remain fluid, likely to be shaped by how Meta’s AI capabilities evolve in the coming months. Earlier reports had suggested that total cuts in 2026 could reach 20 per cent or more of its workforce.
The restructuring comes as chief executive Mark Zuckerberg continues to steer the company towards an AI-first operating model, committing hundreds of billions of dollars to the transition. Internally, this shift is already visible: teams within Reality Labs have been reorganised, engineers have been moved into a newly formed Applied AI unit, and a Meta Small Business division has been created to align with broader structural changes.
The trend is hardly isolated. Across the tech sector, companies are trimming headcount while investing aggressively in automation. Amazon, for instance, has reportedly cut around 30,000 corporate roles nearly 10 per cent of its white-collar workforce citing efficiency gains driven by AI. Data from Layoffs.fyi shows over 73,000 tech employees have already lost jobs this year, compared with 153,000 in all of 2024.
For Meta, the move echoes its earlier “year of efficiency” in 2022–23, when about 21,000 roles were eliminated amid slowing growth and market pressures. This time, however, the backdrop is different. The company is financially stronger, generating over $200 billion in revenue and $60 billion in profit last year, with shares up 3.68 per cent year-to-date though still below last summer’s peak.
That contrast underlines the shift underway. These layoffs are less about survival and more about reinvention. As Meta restructures itself around AI from autonomous coding agents to advanced machine learning systems, the question is no longer whether the company will change, but how many roles will be left unchanged when it does.
