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Konstantin Babenko - CEO - Processica

A recent study by McKinsey found that AI-driven automation in telecom operations could lead to a 25-30 % reduction in operational costs. This includes automating network planning, IT processes, and support functions, allowing companies to operate more efficiently and quickly. These improvements are becoming critical as telecom operators face growing pressure to roll out new technologies like 5G, maintain network performance, and reduce downtime.
 

In this article, we'll look at how Gen AI is transforming two major areas in the telecom industry: optimizing network operations and speeding up IT processes through automation. By using AI-powered solutions, telecom companies can improve network planning, accelerate software development, and reduce technical debt, positioning themselves for future success in a competitive market.
 

This move toward AI-driven operations goes beyond just improving efficiency—it's about reshaping how telecom operators manage their entire IT systems, enabling faster service delivery, lowering costs, and boosting customer satisfaction.
 

Network Operations Optimization

Telecom networks are growing more complex with the rollout of technologies like 5G and IoT, making efficient network management a critical priority. Gen AI offers telecom companies new ways to optimize network operations, improve capital efficiency, and reduce operational costs. One of the most impactful areas where Gen AI is being deployed is in network mapping and planning, where it can analyze unstructured data, streamline maintenance schedules, and optimize network resource allocation.
 

Network Mapping and Planning with Gen AI

Traditional network management relies heavily on manual processes and structured data analysis, which can be time-consuming and prone to human error. Gen AI, however, can process unstructured data such as supplier contracts, technical reports, and network component specifications to provide a comprehensive view of a network’s infrastructure.
 

For instance, a European telecom operator used Gen AI to automate its network mapping processes, reducing the time required for network audits and assessments by 40%. By leveraging AI’s ability to analyze vast amounts of unstructured data, the operator was able to more accurately assess compatibility between network components, predict maintenance needs, and identify areas where operational planning could be improved. This level of insight is vital for preventing costly network outages and ensuring optimal performance during peak usage times.
 

Capital Efficiency and Predictive Maintenance

Another key benefit of AI-driven network optimization is its role in improving capital efficiency through predictive maintenance. Gen AI can analyze historical data from network components to identify patterns that signal impending failures or maintenance needs. This proactive approach enables telecom operators to conduct maintenance only when necessary, avoiding unnecessary repairs while preventing costly breakdowns.
 

A report by Accenture highlighted that predictive maintenance driven by AI can reduce network downtime by up to 30% and lower maintenance costs by 20%. By shifting from reactive to predictive maintenance models, telecom operators can improve both network reliability and operational efficiency, resulting in significant cost savings.
 

AI-Enabled Operational Planning

Gen AI also enhances operational planning by offering real-time insights into network performance and resource utilization. This allows telecom operators to make more informed decisions about where to allocate resources, which areas require upgrades, and how to balance load distribution across the network. AI-powered tools can simulate network traffic under different conditions, helping to identify bottlenecks before they affect customer service.
 

In one case study, a large telecom provider used AI-based network simulations to optimize its 5G rollout, leading to a 15% increase in network capacity utilization. By analyzing real-time traffic patterns and predicting future demand, the operator was able to prioritize areas that would benefit most from 5G deployment, reducing both costs and rollout time.

IT Acceleration and Automation

In the fast-paced telecom sector, where the demand for speed, efficiency, and innovation is critical, Gen AI is transforming IT operations by automating software development, reducing technical debt, and streamlining deployment processes. The integration of AI-driven tools allows telecoms to rapidly adapt to changing technology landscapes while maintaining system reliability and reducing operational risks.
 

AI-Powered Software Development Automation

One key benefit of Gen AI in telecom IT operations is automatic code generation. AI models, such as OpenAI's Codex or DeepMind’s AlphaCode, can analyze high-level requirements and automatically write code snippets, reducing the manual coding workload. For example, a European telecom company reduced development time by 30% after deploying AI-assisted coding tools that generated and reviewed large portions of their software updates. These AI systems also performed unit testing, significantly reducing the number of bugs that would normally be caught post-deployment.

Furthermore, AI accelerates software migration by automatically analyzing legacy codebases and recommending the best approaches for refactoring or migrating to new platforms. A telco migrating its customer relationship management (CRM) system to the cloud used AI to review millions of lines of code, helping reduce migration time by 40%. AI not only suggested migration strategies but also optimized code to be cloud-native, ensuring smooth operations post-migration.

Mitigating Technical Debt with AI Automation

Technical debt is a persistent challenge for telecom companies, particularly when dealing with legacy systems and frequent updates. AI can help telecom companies manage and reduce this debt by continuously scanning their codebases, identifying inefficiencies, and recommending optimizations.
 

For instance, many telecom providers use AI-driven tools to perform static code analysis, identifying portions of code that could become future liabilities. These AI systems are capable of flagging outdated frameworks, inefficient code paths, and security vulnerabilities before they lead to system slowdowns or failures. A large telecom company in Asia used AI to analyze their software architecture and identified over 15,000 lines of outdated code in their billing system. By refactoring this code, they improved the system's processing speed by 25%, significantly reducing customer billing errors and minimizing downtime.

Beyond refactoring, AI helps reduce technical debt by automating the enforcement of best practices in coding. AI tools can automatically enforce coding standards and ensure that new code adheres to strict quality and security guidelines, preventing technical debt from accumulating. According to an internal report by a leading telecom in Europe, the company managed to lower their technical debt ratio by 20% within a year after incorporating AI-driven development practices.
 

Faster and More Reliable Deployments with AI

One of the major advantages of AI in IT automation is its ability to enhance Continuous Integration/Continuous Deployment (CI/CD) pipelines. For telecom companies that must manage massive networks and IT infrastructures, AI can automate the testing, integration, and deployment of new software updates, ensuring quicker and more reliable rollouts.
 

For example, automated testing powered by Gen AI allows telecoms to perform thorough, real-time testing of new features and services before deployment. A telecom company in North America implemented AI-based CI/CD tools that accelerated their feature deployment cycles by 45%, reducing downtime during maintenance windows and increasing network reliability. AI models predicted potential issues during the testing phase and suggested mitigations, reducing the risk of post-deployment failures.
 

Moreover, AI-driven automation enables rollback and recovery in case of deployment errors. By continuously monitoring deployment environments, AI systems can automatically detect abnormal behavior and trigger rollback protocols before customers are affected. This allows for smoother and safer deployments, minimizing disruptions to services.
 

AI-Enhanced Security and Vulnerability Management

With increasing cyber threats targeting telecoms, ensuring robust IT security is critical. AI is transforming security operations by offering real-time threat detection and proactive vulnerability management.
 

Gen AI systems can automatically detect vulnerabilities in code by leveraging large-scale datasets on known threats and vulnerabilities, helping telecoms stay ahead of potential exploits. A European telecom company reported a 50% reduction in security incidents after implementing AI-driven vulnerability scanners, which continuously monitored their codebase for weaknesses. These AI systems were able to detect and patch vulnerabilities faster than manual methods, significantly reducing the window of exposure.
 

Additionally, AI automates incident response by detecting and mitigating attacks in real time. Gen AI can analyze patterns in network traffic and detect anomalies indicative of cyberattacks, such as distributed denial-of-service (DDoS) or malware infections. A major telecom in the Middle East adopted AI-driven security operations, reducing their incident response times by 35%, while minimizing the need for human intervention in minor security events.

Final Thoughts

In my work with AI solutions, I’ve seen how Gen AI can truly transform telecom operations. Automating network planning, improving resource management, and streamlining IT processes isn’t just theoretical—it’s something we’ve helped our clients achieve, leading to noticeable reductions in costs and smoother operations. By using AI to predict maintenance needs and improve network mapping, telecom companies can stay ahead of new challenges like 5G and IoT.
 

Together with my engineering team, we’ve successfully implemented AI solutions that enhance network performance, speed up software development, and reduce technical debt for telecom operators. The results are clear: faster service delivery, less downtime, and happier customers.
 

AI is more than just a tool for efficiency; it’s a game-changer that helps telecom companies improve their overall operations and prepare for the future. Those that adopt this technology will be better equipped to handle the growing demands of the industry and stay competitive in an ever-changing market.