Hitesh TK, chief information officer, Vodafone Idea, says, “We have been an AI and machine learning factory for years. This is critical to handle the volume of data generated by our 200-300 million customers.”
Across the city, a similar revolution is underway at IndianOil’s headquarters. Suresh Nambiar, executive director of information systems, speaks proudly about the company’s AI-powered predictive maintenance systems. “We are using AI to optimise refinery processes and improve supply chain logistics,” says Suresh. “This has significantly reduced downtime and increased operational efficiency.”
These reflect significant changes in the country’s largest economy. Companies People are adopting AI. But as the role of AI is growing, so is the need for a strong governance framework to ensure its responsibility and accountability. Ethical use – Especially in India’s key industries like telecom and oil & gas.
Rishi Arora, Managing Partner, India and South Asia, IBM Consulting, says 71% of CEOs in India believe that without stable governance, AI models will not succeed.
Strategy Groups and Hackathons
At IndianOil, the journey towards effective management AI Governance It started with them Digital Transformation initiatives. “When we started that transformation in 2019, we hired a consultant,” says Suresh. “We created a special purpose vehicle, a strategic information systems group, dedicated to driving IndianOil’s digital transformation.” The group, which started with just four members and has now grown to 30, has been instrumental in implementing AI governance practices across the organisation.
One of their key strategies is to conduct hackathons across the organization. “We conducted one for business intelligence tools, one for analytics tools, one for mobile tools, and one for generative AI tools in coordination with Microsoft,” says Suresh. These hackathons not only helped identify potential AI use cases, but also fostered a culture of responsible innovation within the company.
data governance & engineering
Hitesh says Vodafone Idea focused heavily on data governance as the foundation of its AI strategy. “We moved from multiple points of data sources to a single data lake.” This integration of data sources has been crucial in ensuring the accuracy and reliability of their AI models. Hitesh also emphasises the importance of proper data definition in AI governance. “Three people look at the same data in three different ways,” he says. “So, you need to have proper data definition. Otherwise, for example, a prediction from a customer service perspective will look accurate, but from a marketing perspective, it might not look like that.”
Hitesh says that to overcome this challenge and build trust in AI, they implemented a data engineering process. Both companies have also had to grapple with the challenge of privacy protection, especially in light of India’s new Digital Personal Data Protection Act.
Vodafone Idea had to take this challenge particularly seriously, given the nature of the customer data they handle is sensitive. Hitesh’s team had to ensure that their work process never stores or reveals any personal information of their customers. “Even for basic tasks like complaint resolution, we ensure we don’t reveal the exact location of customers,” he says.
Continuous monitoring and improvement of AI systems is another important aspect of governance, especially given the speed of advancement of AI models. Both companies have implemented processes for regular updates and optimizations to their AI systems.
Building talent, harnessing experts
Lack of skilled talent poses another governance challenge. Both Vodafone Idea and IndianOil have implemented extensive training programmes to upskill their existing employees. “We conducted a mandatory training programme on generative AI for all employees, regardless of their role,” says Hitesh. Ensuring that all employees understand the technology they are working with is considered a key part of a good AI governance strategy.
Despite this, most enterprises need to partner with technology companies such as IBM to address the multifaceted challenges of AI governance. Suresh says these collaborations not only bring advanced AI tools and platforms, but also provide valuable expertise in implementation and governance. “Technology players bring a wealth of knowledge and experience. They help us understand the intricacies of AI development, ensuring our strategies are in line with best practices and global standards,” he says.
As Indian enterprises expand their use of AI, the focus on governance will intensify. Rishi estimates that many pilot projects in AI will convert into full-scale implementations in 2024, especially in areas such as finance, talent transformation, and IT modernization.
