IT Operations Automation
Vodafone Idea needed to embed generative AI across software delivery at scale while maintaining governance, protecting sensitive engineering data under sovereignty requirements, and reducing duplicated effort across more than 150 applications.
Reported impact
Vodafone Idea improved engineering productivity and go-to-market speed, infused generative AI into a majority of IT process steps, and created a scalable governance-first model for broader enterprise AI adoption.
Vodafone Idea partnered with IBM Consulting to make IBM Consulting Advantage the operating layer for an AI-first engineering model. ICA was embedded across the software development lifecycle, from business analysis and architecture through development, testing, deployment, and production support, so teams could automate repetitive work and augment decisions instead of adopting isolated AI tools. To satisfy data-sovereignty requirements, the solution uses a hybrid AI architecture: sensitive code and confidential documents are processed through an India-based third-party LLM service, while other use cases can draw on additional foundation models. IBM and Vodafone Idea then created a reusable ecosystem of more than 120 role-based ICA assistants for API design, code generation, testing, deployment validation, and analysis. A GenAI hackathon generated 138 use cases, many of which became enterprise-ready assets, turning AI adoption into a governed engineering platform rather than a pilot.
Engineering requirements, architecture artifacts, source code, test assets, deployment checks, and production incidents flow through IBM Consulting Advantage assistants, which automate SDLC tasks while routing sensitive use cases through the hybrid AI architecture required for data sovereignty.
Approximately 55% of IT process steps are now infused with generative AI
ICA was integrated across the software development lifecycle—from business analysis and architecture to development, testing, deployment and production support
The initiative has improved productivity by 25–30%
The transformation introduced more than 120 role-based ICA assistants
the solution uses a hybrid AI architecture
Review how this reference was scored and trace each normalized claim back to its documented source.
Scoring methodology
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Traceability
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
Related
IBM Sample May 14, 2024 Global satellite services provider The provider's Network Operations team struggled to collect, normalize, and analyze non-standard satellite and IoT performance data, forcing staff to manually assemble information from multiple subsystems before they… billions of individuals across the world IBM Cloud Pak for Watson AIOps · IBM Netcool Operations Insight · IBM SevOne IBM Sample Apr 3, 2024 WINDTRE WINDTRE needed to automate and accelerate claims handling for telecom service issues because high report volumes, stateful operational complexity, and repetitive service-desk tasks were slowing response times and… 10,000+ reports handled per month with AI and automation IBM Cloud · IBM Consulting · IBM Watson Knowledge Studio 
Google Cloud Sample Modified · Oct 8, 2026 Ericsson Telecom operators today face a rapid influx of artificial intelligence, orchestration, and automation tools. But converting these technologies into real business value is a constant challenge. To prove the business case… Accelerates and lowers the cost of launching new network services Gemini platform 