How to make AI your key to business success in India

As thousands of organizations in India start using AI to work more efficiently, innovate faster and gain a competitive edge, excitement about these technologies keeps growing. 

India’s AI market is expected to grow at a compound annual growth rate of 25%–35% up to 2027, according to the 2024 AI Adoption Index 2.0 published by the trade association NASSCOM. 

This growth is supported by an environment that includes an AI- and machine-learning-focused startup ecosystem and the government-supported INDIAai mission, which aims to develop robust AI computing infrastructure in the country.

However, the journey to full AI integration is not without its challenges. Organizations face several hurdles, including technological complexity, high costs and a shortage of skilled employees. These obstacles can impede the successful implementation and scaling of AI technologies.

Organizations are also facing risks associated with data security, regulatory compliance and ethical issues with AI, such as biased outputs, that could lead to a customer backlash or legal sanctions.

For example, according to Gartner®, “At least 30% of generative AI (GenAI) projects will be abandoned after proof of concept by the end of 2025 because of poor data quality, inadequate risk controls, escalating costs or unclear business value.”* 

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Infrastructure is not the full picture

The first obstacle that organizations have to overcome is the infrastructure itself.

Graphics processing units (GPUs), which were originally designed to handle the high computational demands of graphics and image processing, have now become integral to the field of AI because they can perform many operations in parallel. This accelerates computational processes and enables complex AI models to be trained more quickly.

But it’s no small feat for organizations to buy and install their own GPUs. The hardware is expensive, and setting up clusters of these GPUs in a data center requires expert skills. Instead, they turn to service providers who offer GPU as a service (GPUaaS). This gives them ongoing access to the latest GPU technology without the risk of getting stuck with slower hardware.

Then, they need algorithms and models to guide the computational power of the GPUs. The real value of AI comes from developing and deploying user-facing applications that do all the heavy lifting on the back end. Without this, having GPUs in place is like having a car with an engine but no steering wheel.

These capabilities include agentic modelling – AI systems that are similar to human agents in that they can act autonomously and make decisions based on their programming and learned experiences. It’s the next big thing, and it reinforces the need for specialist application-development capabilities.

The last part of the puzzle is taking these AI applications from proofs of concept to the point where they deliver sustained value creation for organizations, all while addressing key factors such as security and keeping data in an organization’s home country to comply with regulations.

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One platform, many benefits

It is clear that many organizations in India are ready to embrace AI in principle, but they will succeed only if they have expert help and they work within the right ecosystem.

This has prompted NTT DATA in India to launch our Accelerated AI Platform, which can support organizations through the various stages of AI adoption – from initial planning and strategizing to implementation and ongoing management.

We want to walk the road to AI success with our clients, starting with their GPUaaS infrastructure (or other configurations that involve accelerated central processing units) and the accompanying virtualization and management layers.

As a global IT services provider, we then also bring our application and consulting abilities into play. It’s an end-to-end approach that aligns our clients’ AI initiatives with their business objectives and delivers tangible benefits more swiftly.

Learn from the best

We worked with a large fast-moving consumer goods company in India to implement retrieval-augmented generation – training an off-the-shelf large language model with their contextual and customer data.

Their R&D team did vast amounts of manual database research on chemical compounds to create products such as new chip flavours. AI could automate much of these efforts.

Although the company had the funds and in-house talent, they still opted to work with an expert partner to achieve faster and more accurate results. We consulted with them to help set up the underlying infrastructure, and they have now halved information-retrieval time, reduced errors by 40% and achieved user adoption of more than 85% within three months.

As Indian organizations continue to embrace AI, new platforms will play a pivotal role in addressing their technical and strategic challenges.

Don’t be left behind in the AI journey. Make sure you use it to gain a competitive edge.

* Gartner Press Release, Gartner Predicts 30% of Generative AI Projects Will Be Abandoned After Proof of Concept By End of 2025, July 29 2024, https://www.gartner.com/en/newsroom/press-releases/2024-07-29-gartner-predicts-30-percent-of-generative-ai-projects-will-be-abandoned-after-proof-of-concept-by-end-of-2025. GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.