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    Home»Tech»Making the AI-powered case for legacy modernization
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    Making the AI-powered case for legacy modernization

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    There are two dimensions, as I mentioned. One is technical ROI or technology-related ROI, and second is business ROI. On the technical side, and as you heard from Asifa as well, the biggest benefits come from faster time to market, platform stability and resilience, of course, and a lot of times, in fact, almost in all the cases, lower operating costs, and that is one of the aspects associated with some of the legacy modernization programs.

    Besides this, access to broader, more readily available talent pool, and security management, and ensuring that the platforms are secure and free from, as much as possible, free from vulnerabilities in the current environment. At the same time, making it easier to innovate, releases become faster so that the feature delivery into the market becomes faster, and also able to respond to any new technology innovation that comes into play. But this is only on the technology side.

    On the business side, however, the returns are often reflected in customer outcomes, and what we typically see are improvements in measures such as net promoter score, and in this case, for example, application ratings that you see on the app store. Both of which are actually very strong indicators of customer satisfaction and digital experience quality. I think it is important for us to cover, look at the ROI from both technology, but more importantly, from a business perspective.

    The second part of your question was about what would be my advice to leaders, and I think Asifa covered it very well, where she mentioned that the one-team approach, the providing safe environment to the team to be able to say what is going well, but also what is not going well, and keeping your eye on the end outcome. I think those are very important things. But I would also like to add that don’t treat modernization as a technology initiative. It is a unique opportunity for us to rethink the business platform itself, and rather than pursuing a like-to-like migration, use the investment that you’re making to improve customer experience, simplify processes, and re-architect for capabilities such as real-time personalization and data-driven decision-making. The greatest returns come when technology transformation is directly linked to business outcomes.

    And finally, and this is something that I have seen from personal experience multiple times, is you have to think from first principles. AI does not replace good engineering practices. It enables organizations to execute those practices faster, and it enables it faster, but also more consistently and at greater scale. The foundations of good architecture, sound engineering, and clear business objectives will continue to remain important, and in fact, their importance is going to increase as we progress. That, I think, is what I would say anybody embarking on a legacy modernization program should be focused on.

    Megan: I love the idea that this is not just about migration. This a chance, as you say, to reimagine what you can deliver and what’s possible. Fantastic. Let’s close with a forward look. Asifa, what innovation are you looking forward to that wouldn’t have been possible before this, and what do you see on the horizon?

    Asifa: There’s definitely lots of things on the horizon. But what excites us most isn’t specific technology, it’s that the question in our conversations has changed. It used to be, can our platform support that? Now, it’s is that the right thing to do for our customers? And that’s a profound shift.

    There’s three things, Megan, that generally weren’t possible before, and we’ve touched on this a little bit, and Sanjeev’s touched on it as well. This first is speed as a permanent capability. Since launch, Android and iOS, the team has shipped multiple rapid-fire releases, including our migration to a new payment gateway. Bills are now completing four times faster, codes are reaching to testers in about an hour, and we’ve reduced our code base by 30%, and our application footprint’s reduced 18% as well. A simpler estate isn’t an aesthetic preference anymore, it’s what makes the next change cheap, and we’ve bought ourselves optionality to do that.

    The second is quality at that speed, which is the part we’ve been most skeptical about five years ago. AI-driven triage and predictive defect analysis, we ran it across nearly 1,400 cases to focus on testing on the highest risk journeys, which meant we went live with zero security defects and zero high severity defects, and Sanjeev mentioned that just before. The old trade-off between moving fast and moving safely is being renegotiated right in front of us, so that’s the second point.

    The third one is AI-driven accessibility testing, which the teams treated as a critical rather than an optional opportunity. In healthcare, people who most need to reach us are very often the people whom our poorly designed interface is a genuine barrier, and so being able to test that systematically at scale was a real advance for us as well.

    And Megan, you mentioned on the horizon. It’ll be remiss of me not to take the name of agentic AI. The shift from AI that supports a task to AI that completes an outcome end-to-end with proper governance, human oversight at the key decision points. What this program showed us is that the constraint is no longer the models. It’s whether your platforms, data, processes are more than enough to let AI act safely, which is precisely why this work mattered now. Sanjeev alluded to it as well about that underlying architecture. Responsible AI as a source of advantage, not a compliance exercise, I would say. In health, if people don’t trust how you’re using their information, nothing else you build matters. We didn’t modernize to have modern technology. We modernized to earn the right to do the next thing, and to do it in weeks rather than years.

    Megan: Absolutely. And now you have those foundations in place, like you say, all of these opportunities open up. Fantastic. And Sanjeev, just finally, as companies complete these migrations, what kinds of innovations and benefits are you seeing, and what do you expect in the next five years?

    Sanjeev: Sure. Again, good question, Megan. The reason is there is no uniformity on how these migrations are being done even today. As I mentioned earlier, so where there is simple lift and shift of existing code base onto a new platform, a like-to-like replacement, the benefits generally tend to be limited. Where we apply first principles, thinking about re-imagining, re-architecting, and refactoring the system to establish foundations for a far more flexible system, where rules are not boxed into the architecture, but are managed in a way that changes can be incorporated faster, personalization can be achieved in real time, and time to market improves multifold. That’s where we are really seeing far more benefits coming through.

    And to take the example of Bupa, it is a pretty clear step change, both in terms of customer experience and how fast teams can actually deliver now. I think the app ratings have gone up significantly. The customer experience has improved. Even simple things, such as login success rate, has improved quite significantly. And on the engineering side, we are now building and releasing features roughly about four times faster, and we are also seeing the migration of nearly 100% of the customers onto the new platform.

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