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.
