Telcos actively spending in AI, infrastructure upgrades: Kyndryl's Paul Savill

Time of India

11-07-2025

NEW DELHI: New York-based Kyndryl that provides IT infrastructure services said that the telecom sector is evolving rapidly to embrace the 6G-led future, and together with artificial intelligence (AI), telecom carriers can automate necessary IT operations to cut time to market and enhance service reliability for subscribers. In an interaction with ETTelecom's Muntazir Abbas, Kyndryl Global Practice Leader— Network & Edge Paul Savill talks on telco modernisation, edge AI, cloud portfolio, and cybersecurity. Edited excerpts.
What are the top 2-3 sectors that you are currently focusing on?
Kyndryl is a leading provider of mission-critical enterprise technology services offering advisory, implementation and managed service capabilities to thousands of customers in more than 60 countries. We run and transform the IT operations for companies across different sectors, including banking, telecom, manufacturing, insurance, healthcare, and energy.
How do you think AI can help telecom carriers as they look to reduce time to market? With 5G coverage reaching 95% of subscribers in India, do you think it's high time for telcos to automate and modernise infrastructure?
The telecom industry is rapidly evolving toward a future shaped by 6G, digital twins, cloud computing, and other emerging technologies. However, traditional network infrastructures and management tools aren't built to support these advanced services, and the resulting IT complexity is only set to increase. Many telecom providers still rely on legacy systems and decades-old processes to run their IT operations. This makes it challenging to introduce modern AI solutions without risking disruption to current services. Carriers that fail to modernize will struggle to meet rising customer expectations for reliable, high-performance connectivity.
By combining AI, machine learning and big data, telcos can automate essential IT operations like event correlation, anomaly detection, and root cause analysis. This not only reduces time to market but also enhances service reliability and operational efficiency. Additionally, some of the leading telecom equipment manufacturers are making significant progress in developing agentic AI capabilities to proactively manage networks. While challenges remain, we view this as the next major evolution in network management automation.
Telecom carriers are looking at leveraging AI primarily to enhance customer experience, prevent customer churn, and bring new revenue streams. Your views based on your learnings and trends?
In a recent Kyndryl and Altman Solon study on generative AI in the telecommunications sector, customer service implementations of generative AI had the highest success rate, with about 80% of telecommunications companies scaling these use cases to production and ~45% achieving ROI targets. Other areas of significant success were IT and development, network, and business support services like finance, procurement and supply chain functions.
How do you think AI can improve edge computing, and what are its benefits to end customers?
Edge computing plays a critical role in AI deployments, especially in mission-critical environments where data needs to be processed quickly and efficiently. AI inference at the edge involves processing data closer to the source, significantly reducing latency compared to cloud-based inference. This is crucial for applications requiring real-time insights, such as gaming, healthcare diagnostics, and fraud detection. Edge AI also reduces the need to transmit large volumes of data to centralized cloud servers, leading to cost savings on network usage for data transport, ensures optimal network performance, and is helpful in environments with limited connectivity. Beyond performance benefits, data governance mandates – driven by regulatory requirements and the need to mitigate security risks, are also accelerating edge AI adoption.
What are your AI cloud offerings?
Kyndryl recently launched a suite of AI private cloud services to speed up enterprise adoption of AI solutions by providing a secure and customizable platform for companies to develop, test, and deploy AI applications such as generative AI and large language models. The platform can be used for services across the healthcare, financial services, manufacturing, and telecom, media and technology verticals.
Do you think telecom operators are spending much on infrastructure upgrades and AI?
Telcos are actively investing in AI and infrastructure upgrades. According to Kyndryl's People Readiness Report, which surveyed over 1,000 business and technology leaders across eight markets, 97% of telecom organizations are already using AI across multiple areas of their operations. In fact, investment in generative AI is growing so rapidly that many are overshooting their budgets. In another study done by Kyndryl and Altman Solon on generative AI in the telecommunications sector, we found that roughly 80% of executives reported exceeding their budgets when scaling AI projects, with a third exceeding budgets by as much as 50%. Some telcos are responding by refining their cost management and AI governance practices to improve outcomes.
Companies are also increasingly exploring multi-LLM strategies and diverse model deployment approaches to better manage expenses and optimize performance. While the technology is still in its early stages, there is broad consensus among experts that its potential will grow significantly as implementation strategies mature.
Who are your top telco customers globally?
Kyndryl's global telco customers include
Bharti Airtel
,
Vodafone
, Telefonica, MasOrange, and British Telecom. Kyndryl also partners with
Nokia
to provide private 5G, edge computing and data center networking services and solutions to global enterprises.
What is your cybersecurity portfolio? Since AI is becoming mainstream, do you think enterprises are still reluctant to adopt foolproof security?
Kyndryl helps businesses become more cyber resilient by enabling them to anticipate, protect against, withstand and recover rapidly against evolving enterprise risks through an end-to-end cyber resilience framework. This integrated approach helps protect brand reputation, builds trust and supports operational resilience and regulatory compliance by aligning security, continuity and recovery efforts.
The
Kyndryl Readiness Report
found that while 88% of business leaders see cybersecurity as a board-level priority, just 35% believe their organization is fully prepared to defend against cyber threats. The AI era introduces a new wave of security challenges – threats such as adversarial attacks, malicious inputs that mislead models, model poisoning and the corruption of training data all highlight the need for stronger model validation and data integrity.