IBM has expanded into tier 2 cities at a time when other technology companies are reassessing smaller centres. What is the vision behind this expansion?

One reason is diversification of location concentration. Today, it is important not to concentrate the nature of talent and technology work in a few locations. Then access to talent: wherever we have gone, we have found meaningful talent. Through regional engineering and technical colleges, we have found some amazing talent. Third reason is the ability to build more vibrant IT ecosystems, including business partners, also moving to these locations. In some of the first locations where we expanded, including GIFT City and Kochi, business partners we work with also opened offices there. That gave us greater opportunities for co-creation and co-development. Academia is another important part of that ecosystem. There is also an opportunity to work with governments. For example, in Lucknow, within our facilities, we have created an AI GovTech Centre of Excellence that we are working on with the Uttar Pradesh government. The fourth factor is work-life balance. These emerging technology locations offer employees a very different quality of life. You have IT parks, residential communities and employees who can often live much closer to where they work. Compare that with Bengaluru or Mumbai, where employees can spend several hours commuting every day. Work-life balance in these emerging locations is something employees genuinely value. We have also found that many employees are natives of these locations and are returning home.

How do you see the job market’s flip-flop on hiring software engineers and coders?

Is AI going to eliminate jobs – yes. Will it create new jobs? Yes! The real question is how we take advantage of technology not only at an individual worker level but also at a management level. At IBM, we are all encouraged to think about how we are using AI in our day-to-day work. I currently have multiple projects underway looking at how we can use AI to improve our day-to-day decision-making. It is not about how many but what type of engineers you need. You may need prompt engineering skills but can the engineers in different disciplines have the aptitude to work with these technologies or can they be skilled to do so? There is a huge backlog of software enhancements that clients want. With certain capabilities like IBM’s Bob, companies can accelerate the reduction of that backlog.

As AI moves from proof-of-concepts towards more widespread implementation, do we need a fleshed-out AI regulation?

The idea is that as implementation increases, organisations may need frameworks around the responsible use of AI. Regulation is generally introduced to prevent misuse, fraud and abuse. India has done well to take a precision regulation approach to avoid regulation that stifles innovation. When we built the WatsonX platform, we created governance capabilities around AI. There are several important questions organisations need to consider: Are you using personal information that you should not be using? What is the provenance and accuracy of the data? Who has permission to access it? Are the models being refreshed and governed appropriately? Can you explain the outputs and decisions generated by AI? Is there transparency around how AI is arriving at an answer? These are important elements of AI governance but not at the cost of innovations.

Amidst the data centre boom and local concerns, how do you advise customers when talking about the infrastructure?

IBM builds data centres around the world, and we have been strong advocates for green technologies and approaches that can better manage energy consumption. When companies ask me what they should do, I cannot advise them on their individual business models. But if you are building a data centre, environmental considerations should absolutely be part of the planning. How do you use greener energy? How do you address power consumption? How do you use more efficient technologies? Those are all relevant questions. We also advocate the use of more efficient infrastructure. We are building technologies where you can achieve significantly higher output with a much smaller footprint compared with traditional systems. Those are areas of innovation that will continue to become important. You cannot stop the evolution of data centres but sustainability, efficiency and environmental considerations must be part of it.

Beyond the expansion into tier-2 markets, what are IBM India’s other key business priorities?

Our strategy is centred on hybrid cloud, AI and delivering those capabilities with a strong sense of security. Across those areas, there are a variety of initiatives that we will continue to drive. Lightwell is an example of a security capability that we have introduced. Our broader business strategy continues, including our software portfolio, particularly around data and AI, hybrid cloud platform and the infrastructure work in India. I don’t see any change in our strategy around hybrid cloud and AI. We will continue to drive those priorities.

How have customers responded to your Lightwell vulnerability solution?

The response has been nothing short of amazing. In the US, we have several very-large banks and other organisations already signed up and at different stages of design and implementation work. In India, we have started proactively discussing the offering with customers. We currently have around 20-30 active conversations with large private- and public-sector organisations. These discussions include potential proof of concepts and how organisations can test the offering before moving towards adoption. There is significant interest from banking and financial services, for obvious reasons. However, there is also interest from areas such as citizen services and manufacturing.

As you have these conversations with customers, how have you seen the way enterprises view open source evolve?

The larger shift in conversations is around how organisations look at security as a systemic programme rather than an afterthought. The use of open-source is a given. To get on top of the associated security issues, you detect vulnerabilities that already exist and fix them quickly. The second concern is about rogue agents and other emerging risks. Detecting those vulnerabilities and addressing them is also becoming increasingly important. Security needs to be built into an organisation’s day-to-day processes. Next-generation SOC capabilities and our broader cybersecurity portfolio are becoming increasingly relevant in the world of enterprise AI.