Bharti Airtel has developed an in-house artificial intelligence platform called Agent Bridge and added GPU capacity across its data centres as it steps up the use of AI across its business. The company says these investments are helping it deploy AI applications faster in customer-facing services and internal operations.
Airtel Managing Director and CEO Shashwat Sharma shared the update during the company’s Q2 FY27 earnings call on November 6, 2026. He said Airtel had spent the previous two quarters building the foundation for wider AI integration across its digital platforms. The next priority is to scale applications that are already delivering results.
The company did not disclose the amount of GPU capacity added or provide a commercial launch plan for Agent Bridge. Its comments indicate that the platform is currently part of Airtel’s internal AI development and deployment strategy.
What Is Airtel Agent Bridge?
Agent Bridge is Airtel’s homegrown AI agent platform, developed to help the company activate AI use cases more quickly across its operations.
The platform is part of a broader effort to bring AI into Airtel’s digital systems rather than treating it as a collection of separate experiments. Sharma said the company had spent two quarters laying the groundwork and testing how AI could change the way its teams work.
Airtel is now focusing on expanding applications that have demonstrated value. These include customer support, recruitment, customer onboarding, network management and other internal processes.
The company has not disclosed the platform’s technical architecture, the AI models it uses or whether it will eventually be offered to external businesses. It also has not specified which of its existing AI applications are directly powered by Agent Bridge.
How Airtel Is Using AI Across Its Business
Airtel described several examples of how AI is already being used across its operations.
Customer support: AI-powered call centre bots were among the company’s earlier applications. These tools can help automate customer interactions and handle routine requests.
Recruitment: Airtel is using AI in parts of its hiring process, including screening candidates at scale. This can help recruitment teams manage large volumes of applications.
Video KYC: The company is applying AI to video-based Know Your Customer processes used during customer onboarding.
Finance and internal operations: Sharma cited the process of closing quarterly accounts as another area where AI is changing how employees work. The aim is to improve the efficiency of internal workflows.
Home broadband installations: Field engineers use AI-powered tools on their phones to help standardise installation and service work. This could support more consistent execution across field teams.
These examples show the range of applications Airtel is exploring, although the company has not confirmed that every one of them runs on Agent Bridge.
Airtel’s AI Decision Engine Has Generated Over 10 Billion Next-Best Actions
Airtel also highlighted the scale of its real-time, context-led decision engine, which has generated more than 10 billion next-best actions across its channels.
The system uses customer-level context to personalise content and recommendations. By bringing information from different points in a customer’s journey into a consolidated view, Airtel can make its interactions more relevant to individual users.
The company said it has also delivered more than one billion personalised content items and recommendations using this approach.
This is an important part of Airtel’s AI strategy because it connects data and decision-making with customer engagement. Rather than showing the same offers or recommendations to everyone, the company can use available customer context to determine what may be relevant.
AI Is Also Helping Airtel Reduce Network Energy Consumption
Airtel is using AI in its mobile network to manage energy consumption. Its AI-enabled radio access network (RAN) can dynamically determine when network equipment can enter sleep mode, helping reduce power use while maintaining network operations.
This is particularly relevant for a telecom operator with a large number of mobile sites, where electricity and energy costs form a significant part of operating expenditure.
The company has also discussed AI applications that support field operations and improve network efficiency. These uses show that its AI programme extends beyond customer-facing chatbots and digital services.
Airtel Adds GPU Capacity but Does Not Disclose the Scale
The addition of GPU capacity across Airtel’s data centres is another important part of the announcement.
Graphics processing units are widely used to run AI workloads, including model training, inference and other compute-intensive applications. More GPU resources can help an organisation deploy and operate AI applications at a larger scale.
However, Airtel has not disclosed how many GPUs it added, the total computing capacity available or the investment involved. It has also not provided a breakdown of how much capacity is being used for Agent Bridge and other internal workloads.
The investment should therefore be viewed as an expansion of Airtel’s AI computing infrastructure, rather than confirmation of a specific GPU-as-a-service launch.
Is Airtel Planning to Offer GPU Services to Enterprises?
During the analyst Q&A, Executive Vice Chairman Gopal Vittal discussed the possibility of Airtel entering the GPU services market. He distinguished between three broad opportunities.
The first is bare-metal GPU leasing, where customers pay to access GPU hardware. Vittal described this as a commoditised business and flagged counterparty risks, particularly among smaller companies operating in a market with strong demand.
The second opportunity is managed GPU services. These go beyond providing hardware and include software, orchestration and tools that help customers deploy and manage their workloads. Airtel said it is studying this segment.
The third opportunity is a broader AI stack for enterprise customers. This could combine computing infrastructure, software and AI capabilities through Airtel’s cloud business. Vittal said Airtel was hearing demand from enterprise customers for such services, but stressed that it was still early.
Airtel has also developed an internal platform to optimise the cost of running AI models across its own workloads. This experience could help the company understand the software and infrastructure requirements of enterprise AI services.
However, management did not announce a launch date, commercial commitment or specific investment plan for managed GPU services or a full enterprise AI stack.
Airtel’s AI Push Is Linked to Its Data Centre Ambitions
Agent Bridge and the additional GPU capacity fit into Airtel’s wider investment in data centres and cloud infrastructure.
Through Nxtra Data, Airtel is pursuing an ambition to build around 1 GW of data centre capacity over the coming years. During the same earnings call, management discussed its investment in a strategic land parcel that could support further expansion.
The company is also developing Airtel Cloud as part of its enterprise digital services portfolio. A larger data centre footprint and additional computing capacity could support both its internal AI requirements and potential future services for business customers.
For now, Airtel’s immediate focus appears to be using AI to improve its own customer experience, network efficiency and internal productivity. Its comments on managed GPU services and enterprise AI indicate a possible longer-term opportunity, but those offerings remain under evaluation.
The key development is that Airtel is building both the software platform and computing infrastructure needed to scale AI internally. Whether Agent Bridge and its GPU investments eventually become a separate enterprise business will depend on how the company develops its commercial strategy and responds to customer demand.
