Generative AI race creates new commercial models for IT services firms

This year’s French Open tournament is a different experience for fans and players with generative Artificial Intelligence (AI)-powered insights, videos, and reporting, thanks to a partnership between Infosys and the French Tennis Federation. Integrating AI with cloud offerings has brought a new spell of such opportunities for Indian IT firms.

Last month, leading IT firms including Tata Consultancy Services (TCS), Cognizant, Wipro, Mphasis, and Infosys were on a spree to launch their generative AI platforms. The focus is to offer clients an enterprise-scale platform to explore unprecedented use cases with generative AI in a responsible way, along with enhancing internal capabilities to effectively manage workloads.

As the name suggests, generative AI refers to algorithms that can produce new content, including audio, code, images, text, simulations, and videos by analysing huge collections of data.

A common theme in the platforms launched by all the IT firms is their focus on using the cloud as a gateway to deliver AI services. Deploying large-scale generative AI scale has created a demand for huge data storage and compute power on top of the infrastructure, platform, data, and software services built on the cloud.

“We are seeing strong interest from our clients for efficiency and productivity-enhancing programs, even as businesses are keen to secure their future growth. Our own business operations have been hugely benefited by Infosys Topaz bringing the power of generative AI platforms and data solutions. Today, our clients are building new paths to expand revenue-creating opportunities and grow with Infosys Topaz,” Salil Parekh, CEO & MD, Infosys said while launching the new solutions in the company’s AI-first offering Infosys Topaz.

The new platforms of TCS and Wipro are powered by Google Cloud’s Generative AI tools – Vertex AI, Generative AI Application Builder, and Model Garden collection of foundation models.

According to a recent report by Bloomberg Intelligence, rising demand for generative AI products could add about $280 billion of new software revenue over the next 10 years, driven by specialized assistants, new infrastructure products, and copilots that accelerate coding. Major cloud hyperscaler platforms Amazon Web Services, Microsoft, and Google have already started leveraging this opportunity.

Akhilesh Tuteja, Partner and Head, TMT (Technology Media and Telecommunications), KPMG in India says generative AI created a timely opportunity to reduce the overall cost of delivery, through productivity and efficiency enhancement, and also provide new revenue opportunities. He said platform partnerships would be critical for the new segment.

“Generative AI models (especially Large Language Models) are a significant focus area for hyperscalers, who are investing heavily in driving scale and innovations. They offer scalable computing and storage resources and a variety of AI frameworks and tools, which are essential for training and running generative AI models,” Tuteja said.

He added that IT services companies extensively leveraged hyperscaler innovations in their platforms, improving their existing offerings, and introducing new use cases at speed. “Through the help of available generative models and the power of hyperscalers, IT services companies are able to create proof of concepts in days instead of weeks and months.”

As per the Bloomberg Intelligence report, the generative AI market is poised to explode, growing to $1.3 trillion by 2032, from a market size of just $40 billion in 2022. Life sciences and education are likely to see rapid growth from their position as a fraction of larger software segments today.

In the new model of generative AI platforms, Indian software firms aim to use their existing domain knowledge and investments in research and innovation to create industry-specific use cases. TCS has developed a large portfolio of AI-powered solutions and intellectual property in the areas of AIOps, Algo Retail™, smart manufacturing, digital twins, and robotics. Cognizant’s AI teams have enabled AI-guided decisions in areas such as price optimization, predictive healthcare analytics, and crop science optimization.

“The easiest and most common approach today is to use enterprise APIs in available models. I see the onset of newer approaches including relatively smaller and more efficient models, and multi-modal integration. These trends will require even more integrated partnership models,” Tuteja said.

 He added, “IT services companies are also likely to build and offer industry platforms, designed to create industry-specific use cases and solutions at speed. This will likely change the commercial model.”