“We’ve been an AI and machine learning factory for years,” says Hitesh TK, chief information officer at Vodafone Idea.“It’s crucial for handling the volume of data generated by our 200-300 million customers.”
Across town, at the headquarters of IndianOil, a similar revolution is underway. Suresh Nambiar, executive director of information systems, speaks proudly of the company’s AI-driven predictive maintenance systems. “We’re using AI to optimise refinery processes and improve supply chain logistics,” Suresh says. “It has substantially reduced downtime and enhanced operational efficiency.”
These illustrate a significant shift in how the country’s largest companies are embracing AI. But as AI’s role grows, so does the need for robust governance frameworks to ensure its responsible and ethical use – especially in India’s critical industries like telecom and oil & gas.
Rishi Aurora, managing partner at IBM Consulting for India and South Asia, says that 71% of chief executives in India believe that without stable governance, AI models will not be successful.
Strategy group & hackathons
At IndianOil, the journey towards effective AI governance began with their digital transformation initiative. “When we started that transformation in 2019, we engaged a consultant,” Suresh says. “We carved out a special purpose vehicle, a Strategic Information Systems group, dedicated to driving the digital transformation of IndianOil.” This 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 has been to conduct hackathons across the organisation. “We did one for the business intelligence tool, one for the analytics tool, one for mobile tools, and one for generative AI tools, in coordination with Microsoft,” Suresh says. 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 their AI strategy. “We moved from multiple points of data sources into a single data lake.” This consolidation 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 a proper data definition. Otherwise, a prediction, for example, from a customer service point of view will look accurate, but from a marketing point of view, it may not look so.”
To address this challenge and build trust in AI, Hitesh says, 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 has had to take this challenge particularly seriously, given the sensitive nature of the customer data they handle. Hitesh’s team had to ensure their work processes never store or reveal any personal information of their customers. “Even for basic tasks like complaint resolution, we ensure we’re not revealing exact customer locations,” he says.
Continuous monitoring and improvement of AI systems is another crucial aspect of governance, especially considering the pace of advancement of AI models. Both companies have implemented processes for regular updates and adaptations to their AI systems.
Building talent, using experts
The shortage of skilled talent presents yet another governance challenge. Both Vodafone Idea and IndianOil have implemented extensive training programmes to upskill their existing workforce. “We conducted a mandatory training programme on generative AI for all employees, regardless of their role,” Hitesh says. Ensuring that all employees understand the technology they’re working with is seen as a key part of a good AI governance strategy.
Despite this, addressing the multifaceted challenges of AI governance requires most enterprises to partner with technology companies like IBM. Suresh says these collaborations bring not only advanced AI tools and platforms, but also valuable expertise in implementation and governance. “Technology players bring a wealth of knowledge and experience. They help us navigate the intricacies of AI development, ensuring our strategies align with best practices and global standards,” he says.
As Indian enterprises expand their use of AI, the focus on governance will intensify. Rishi predicts that 2024 will see many pilot projects in AI being converted into full-scale implementations, particularly in areas like finance, talent transformation, and IT modernisation.
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