5 Questions to Anant Adya at Infosys on how AI is influencing the shift to the cloud

Q. Give us some examples

One of our health care clients, Molina Healthcare—and this is a published case study—acquires a lot of states [in the US] because they're in the payer [health insurance] space. It used to take a lot of time for them to onboard a new state onto their platform.

We created a reference architecture in collaboration with the customer, which brought down the process to less than eight weeks. This resulted in faster revenue recognition, improved visibility of the sales process for better projections, and the ability to run some processes in parallel. This is the power of cloud.

When a beauty products company was looking to expand into the US from the Asia-Pacific region, they wanted to be 100 percent cloud-native from the start, avoiding the complexities of setting up a data centre. Their goal was to grow revenues to a billion dollars in three to five years. This exemplifies how the cloud is evolving from simply optimising costs to enabling disruption in new markets.

We focus on three go-to-market strategies: First, IT efficiency, which enhances customer agility through cloud technologies; second, industry clouds that improve business agility, like our solutions for airlines and fintechs; third, innovation and co-creation for driving new ideas. By 2022, we shifted our focus from just technology to delivering measurable business outcomes, integrating technologies like IoT and AI. This approach allows us to form outcome contracts, ensuring we’re accountable for real results.

We worked with Daimler as it aimed to become an all-electric car company. We focussed on creating a hybrid cloud technology foundation that included public, private, and edge cloud components. Additionally, we enhanced factory efficiency using advanced technologies like Wi-Fi 6 and 5G. We also developed an agile operating model based on open-source and core technologies.

Similarly, with Kraft Heinz, we worked on data modernisation projects, partnering with Azure and Snowflake to improve efficiencies. These are just a couple of impactful case studies from our efforts.

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Q. Tell us about the shift to business outcomes.

Today, they’re increasingly focussed on business outcomes rather than just technical metrics like response times or infrastructure availability. For instance, clients want to know if they can print invoices on time or if their deliveries happen as scheduled. This requires us to work backwards, ensuring the technology supports these essential functions.

The emphasis is now on delivering measurable business results, which varies by industry. Many clients track metrics like net promoter scores or hiring efficiency in HR processes. This shift makes our role more relevant, as clients recognise that we provide value beyond just being a technology partner. Ultimately, we’re aligning our commitments to help them achieve their business goals.

Q. What happened when your cloud services met AI?

In 2023, we launched Topaz [Infosys’s AI services suite] alongside our existing Cobalt initiative, recognising that both are essential for driving business outcomes through six key technologies: Cloud, 5G, Edge, IoT, AI, and data. Our narrative has evolved since 2018 to emphasise increasing digital density within enterprises, where technology and processes integrate better and better.

As clients mature in their cloud journeys, they’re moving from mostly using infrastructure-as-a-service to adopting more software and platform solutions. With a solid cloud foundation, we can then build intelligent applications that generate valuable data, leading to insights driven by AI or generative AI.

Our current vision combines Topaz and Cobalt to ensure that enterprise data is ready for AI, supported by a robust data fabric. Ultimately, cloud will drive AI initiatives, and in turn, AI will enhance cloud consumption.

Q. Tell us about new, emerging roles in this context, and ones that are going away.

We’ve reimagined our service delivery model to emphasise a balance of people and tools. Previously, we operated with a 90 percent people and 10 percent tools ratio, but now it’s shifting to 70 percent tools and 30 percent people. This change is what our enterprise customers expect.

Additionally, as we move towards a more integrated stack with increased automation and AI, it’s essential for everyone involved in administration to know how to code, especially with tools like Puppet, Chef, Ansible, and Terraform. I believe that generative AI will create more opportunities and amplify human potential. If mainframes can thrive for over 30 years, I’m optimistic that nothing will truly disappear.

The shift from a 90-10 to a 30-70 model is relevant to operations. In managing application, infrastructure, help desk, and security operations, the right tools significantly enhance efficiency. For example, effective monitoring and event correlation allow us to triage issues faster, improving our margins and benefiting our clients simultaneously.

Take patch management: It once required around 20 resources to apply updates regularly, but now just three can handle it, thanks to advanced technology. This not only streamlines our operations but also enables those additional team members to contribute in other valuable ways within the enterprise. Overall, leveraging technology allows us to operate more effectively and deliver greater value to our clients.