Artifical Intelligence market sees wide adoption in India


The India AI market is witnessing a broad based awareness and  adoption of AI among both enterprises and providers. Approximately 80% of enterprises  have at least one AI model in production, indicating an extensive penetration of AI/Machine  Learning (ML) across enterprises vs. global. Within providers, too, 64% have AI/ML as a  core element for many of their products, as against 56% of their global counterparts.

These are among the findings from the AI Maturity Index, in Bain & Company’s new report  titled, ‘From Buzz to Reality: The Accelerating Pace of AI in India’, in collaboration with  Microsoft and Internet and Mobile Association of India (IAMAI), launched today at the  IAMAI Digital Transformation Summit, by Shri Amitabh Kant, CEO, NITI Aayog. Approximately 150 providers and 340 enterprises were surveyed for the AI Maturity Index to  examine their relative strengths across metrics such as level of adoption, deployment of use  cases, data management, technology adoption, and talent.

“There is a significant uptick in interest in adopting AI to drive business outcomes. While the  stated breadth of AI adoption is significant, penetration of the technology across use cases is  still low, with several organizations still in the early stages of adoption.”, said Velu Sinha,  Partner, Bain & Company and co-author of the report. “While the availability of data  and cloud-based infrastructure have aided AI adoption, concerns related to data security,  infrastructure, and management continue to be the most significant barriers for enterprises.”

AI is no longer a fringe technology in India

High level of its adoption in India shows that AI is no longer a fringe technology although  penetration in application is relatively low with only 35% broad adopters (i.e. more than three  models in production at scale) among enterprises.

The thrust in adoption for enterprises is maximum in sectors such as communication, over the-top (OTT) and gaming (55%); technology (48%); and financial services (39%). Further,  more than 90% of the digital native companies in CPG & retail and financial services have  demonstrated AI/ML adoption.

In addition to having some of the highest proportions of adopters, communication and OTT  and gaming organisations have also implemented AI across the most significant number of  use cases compared to other industries. Auto and logistics organisations have demonstrated

relative strength in critical data, technology, and talent capabilities. Whereas, industrial goods  and manufacturing and healthcare lag most among other industries. The healthcare sector is  hampered with respect to data processing and governance technologies.

Sudheer Narayan, Partner, Bain & Company and co-author of the report, said “Cost  optimisation through automation defines AI adoption across most sectors including auto and  logistics, industrial goods and manufacturing; with retail and financial services using AI for  personalisation at scale for end customers. Adoption of these use cases is expected to  broaden as data quality and infrastructure scalability improve. We expect healthcare and  CPG and retail to grow fastest in AI/ML spending (~25% year-over-year) with high-value  use cases such as drug discovery (healthcare) and targeted personalised marketing (CPG  and retail), respectively.”

As per the report 87% of enterprises expect to increase annual AI spend by more than 10%  and 94% of AI adopters likely to increase the share of AI/ML-based applications in upcoming  three years.

Technology solution providers are the drivers of AI adoption in India

Providers in India, led by cloud platforms, AI-first SaaS companies, and IoT providers are  either ahead of or at par with their global counterparts concerning AI capability on scale implementations. Of India’s providers’ prototypes, 65% reach production scale—a significant  lead over global providers’ 49% success rate. However, most organizations are still in the  early stages of AI adoption, implementing just a few use cases.

Cloud platforms and IoT providers emerge ahead among the other segments of providers on  the AI Maturity Index. While IoT providers invest in hiring the right talent, cloud platforms  have demonstrated greater maturity by continuously updating their models, and adopting  practices for customers to securely share their data.

Cloud platforms demonstrate an edge when it comes to product development and overall  model maturity. More than 80% of the AI/ML features introduced by cloud platforms in India  reached production scale and exceeded the expected gains.

“Cloud-led data and AI is driving meaningful innovation and transforming every industry  and every sector in India today. AI offers a huge canvas for enabling homegrown innovation  and we have an opportunity to make AI work at scale for India, enabling investment, job  creation and inclusion for all.”, said Rohini Srivathsa, National Technology Officer,  Microsoft India. She further added, “Especially for small businesses and start-ups across  the country, AI offers a competitive advantage and the ability to grow and innovate at scale.  The findings from the report underscores the fact that AI is no longer a futuristic technology,  but is driving real change here and now, and increased adoption of AI will be crucial to  driving equitable growth across sectors”

The build vs. buy preference

Among Enterprises, there is a clear and increasing requirement to ‘build’ for their own  customized needs. In the next three years, 49% of enterprises plan to increase the proportion  of build, compared to 29% that plan to increase the proportion of ‘buy’. A higher preference

to increase the proportion of build is seen in industries such as technology (70%), CPG and  retail (52%), and industrial goods and manufacturing (48%).

While small enterprises prefer to buy pre-built models (45%) due to the high cost of building  in-house, they also experiment with easily accessible open-source tools and frameworks for  cases they want to develop. Digital native companies have shown a similar trend.

Providers, too, are inclined toward building their models using third-party support or open source tools/services. Their reliance on cloud platforms for pre-built models and packaged  solutions is expected to decrease in the coming years (from 36% of the AI feature/use cases  in 2019 to a projected 29% in 2023).

The need for customization and integration provides an opportunity for providers to offer  professional services for customising models and integrating with existing systems and data  for training and deployment

While Indian enterprises are keen to build their AI/ML models in-house, they exhibit a  preference to buy the scale cloud infrastructure and AI work benches, which helps them to  experiment at will on an elastic compute-storage enablement. Cloud platforms have played a  dominant role in increasing the preference to build by offering an end-to-end ecosystem.

Dr. Shubo Ray, President, IAMAI, said “As the AI landscape is rapidly maturing in India,  companies need to understand how to leverage AI to drive business value. In this report, we  capture the adopters’ perspective for AI technologies and aim to raise awareness and foster  AI adoption in India.”

Talent gaps

Although India constitutes a small share (i.e., 1%) of the global market, it produces 16% of  global AI talent, placing it among the top three contributors in the world.

Much of the talent today exists in AI application development due to avenues available for  upskilling, retraining, self-learning, and experimenting with open-source tools. Skill gaps are  most widely observed for providers in data science, data operations, and legal/compliance  areas. On the other hand, enterprises lack domain-specific expertise, data  visualisation/analysis talent, and data engineers.

The talent equation in India in terms of quantity will only get better, but a clear distinction  will emerge between the data engineers, data scientists, and product managers. Cloud  platforms and providers with better quality data scientists and product managers will be better  placed to lead in the market.


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