People remain at the center of every AI-driven IT transformation, says Abhishek Goel
The word „responsible“ is crucial when we talk about a company-wide AI transformation, says Abhishek Goel, CIO of T-Mobile CZ and Slovak Telekom. The role of technology within large corporations is changing with the advent of artificial intelligence. This also applies to the telecoms sector. According to Abhishek Goel, Chief Information Officer at T-Mobile CZ and Slovak Telekom, the essence of this transformation lies in the fact that technology no longer serves merely as a support function, but is a key driver of business strategy, which requires a comprehensive approach to transformation and the responsible implementation of artificial intelligence.
As CIO, how do you see your role changing in a world where technology is no longer just a support function, but a core part of business strategy?The CIO role has changed dramatically because it is no longer just about keeping systems stable and delivering projects on time. Technology defines how fast a company can innovate, how well it understands its customers, and how resilient it is in a changing environment. Today, a CIO has to be both a technologist and a business partner. That means being someone who understands architecture, data, and security, and is able to translate them into business value. This is extremely important, especially in telecommunications, because our field is deeply connected with the customer experience.
IT transformation is omnipresent these days. What does it mean in practice for a large telecom operator?
It is never just about IT transformation; it is always a company or business transformation. Such a change is a long-term shift in the way we build, run, and innovate our technology, and how we simplify our architecture to make it more modular. We also try to find ways to work more agilely to deliver our digital services faster and to achieve a simpler, safer, and more resilient environment where our products and services are built. It is a truly substantial corporate transformation that changes both processes and systems.
What are the key ingredients to support agility?
To support agility, you need to have more fluid teams. There are no silos or departmental views. You can jointly create a team for a common goal. IT and business are two sides of the same coin, and their common goal is to deliver value to the customers.
Not only IT transformation, but AI is definitely everywhere today. What is your view on the difference between real AI value and the AI hype?
The difference is very simple. Real AI solves a real problem. Hype starts with the technology and then looks for a problem to attach it to. We try to do the opposite. We start with the problem we are trying to solve. It matters what you are trying to address with AI—be it a customer problem, an employee issue, or our own efficiency. Today, we focus mainly on areas like customer care, sales, finance, as well as IT and network operations, where AI can help automate many processes and deliver value. A good AI use case should have a clear purpose, clear ownership, and a clear way to assess it. At the same time, at T-Mobile, we are not afraid of failure or experimenting with AI.
Where do you see the greatest potential for AI within a telecommunications company?
There are several strong areas. Customer care is one of the most visible examples: AI can support communication through chatbots on websites and in apps, or voicebots on customer lines, helping customers get answers faster and enabling a more personalized experience. In network operations, machine learning can help identify anomalies and behavioral patterns, supporting predictive maintenance and faster reactions to situations that could influence service quality. We also see potential in sales, finance, and IT, including tools that support developers in their daily work. At the same time, AI is not only an internal topic. We are also bringing AI closer to customers through software and device-based solutions. For example, we introduced our own Magenta AI, which includes tools from 11ElevenLabs and Picsart, to everyone using the Můj T-Mobile app, alongside AI assistants integrated into devices such as the T Phone 3 and T Tablet 2.
Many companies are experimenting with AI pilots. What does it take to scale AI responsibly across a large organization?
The word „responsible“ is crucial when we talk about wide-scale AI transformation. Scaling AI is harder because it requires high data quality, security compliance, integration, and adoption. You also need to be clear about the costs. We are highly focused on using AI under strict compliance regulations, especially in the area of customer experience, because our customers and their trust are key to us. Responsible scaling also means keeping human control, continuously evaluating solutions and making sure AI is used as a support tool rather than as an uncontrolled decision-making mechanism. Furthermore, governance should be practical. It should help teams build the right things the right way and operate them sustainably.
You mentioned data. What role does data play in the AI journey?
Data is the foundation. Without trusted and well-governed data, AI will remain limited. Every telecom operator has extremely rich data. It comes from our network, interactions with our call centers, our digital channels, and many other domains. The challenge is to make this data usable while keeping it secure and compliant. This is particularly important when we talk about network care. You need high data quality, which means proper data management and data governance are required. That is exactly what T-Mobile is focused on—not just creating terabytes of data, but having a properly defined layer and governance that helps us use AI effectively. „AI-ready“ data means it is fully managed, fully governed, secure, and compliant, allowing us to truly use it to deliver value.
How do you balance innovation with security, privacy, and regulatory expectations?
We are still on the subject of responsibility. Innovation and security cannot be treated as opposites; otherwise, friction arises. In the telecom industry, trust is part of the product. Customers depend on our systems. We start with security the moment we think of an innovation. Security and compliance are embedded in our design. The ambition is not to slow down innovation, but to make it safe to scale. Especially AI may affect these issues because it processes sensitive information. We aim to improve the customer experience without compromising trustworthiness.
Do you expect AI agents and more autonomous systems to become part of enterprise IT?
Yes, but gradually and carefully. AI agents are definitely an important next step because they can move from answering questions to supporting workflows or even triggering actions. We already see AI helping with selected tasks in some areas. The next phase is to make these capabilities more integrated and useful. We focus on agent AI governance with a specific goal: to keep a human behind the wheel. It is a question of responsibility again. We have identities for our employees, but what are the identities of these agents? They trigger tasks, but humans bear the responsibility. We will need to manage what an agent can access, what it can do, who owns it, and how its behavior is audited. This is why the future of AI is closely connected with identity management, cybersecurity, monitoring, and accountability.
Large companies often struggle with legacy systems. How do you modernize without disrupting the business?
The key is to be pragmatic. In a large company—and T-Mobile is no exception—you cannot replace everything at once. Legacy systems often support critical processes, so modernization must be carefully sequenced. We look for areas where simplification brings the biggest impact: reducing duplication, improving integration, automating manual work, and creating a cleaner architecture for future services. It is also important to keep business continuity in mind. Transformation should feel ambitious inside the company, but seamless for customers.
Nowadays, the CIO position is very important. What are the biggest challenges for CIOs in large companies today?
I think the biggest challenge is managing several speeds at the same time. You are running the business, transforming the model, and you need to keep the company resilient and safe. All three are important, and all three are moving fast. Customers expect simple and fast digital interactions, regulators are getting stricter, compliance is becoming more demanding, and the business needs faster delivery and transformation. This is where the CIO role is getting critical and important for the organization to guide through this complexity. In practice, the CIO has to set clear priorities, build stronger teams, and choose where to standardize and where to differentiate. You must be sure that the technology decisions you are making are connected to your long-term business goals. This is why the CIO is gaining more and more strategic importance in companies.
How do you see cooperation between IT, business, and technology teams evolving?
It is getting more and more fluid. Digital products, networks, data platforms, and customer journeys — all these things cannot be built in silos. We need cross-functional teams. I want my technology people to understand business, and business people to understand technology. At T-Mobile, we are trying to truly bring IT, technology, and business people together to deliver results. The best results come when there is a shared ownership of outcomes. Cooperation between IT and technology is especially important because customer experience relies on both business interactions and digital channel interactions. Both the network must perform, and digital journeys need to be simple.
Looking ahead, what kind of IT organization will be needed for the next phase of digital and AI transformation?
I see it becoming more and more product-oriented, more and more automated, and more and more data-driven. In all these situations, it will definitely need strong engineering capabilities. It will require both strong engineering skills and a very strong understanding of business. Customer behavior is also changing in the age of AI. Many young people are trying different ways of interacting. That is how AI will change the way an IT organization develops, tests, and operates support systems. We already see these things completely changing in some areas. However, I strongly believe that people will remain at the center when it comes to judgment and ownership.
You can read the Czech version of the article HERE.
