Harnessing AI For Growth: How Indian Enterprises Are Using AI to Transform Business Operations

Is AI-GenAI playing a pivotal role in improving processes and productivity across mainstay enterprises? Most companies think so and focus on leveraging these new tech opportunities to achieve sustainable growth. Data remains the critical base for AI/GenAI tools to understand and analyse the best way to increase efficiency and hourly productivity.  

This should not be a problem in a digital environment, as businesses tend to sit on vast amounts of data. However, most organisations struggle to derive meaningful business insights due to the presence of data silos, isolated data repositories that fail to bring the bigger vision. 

Moving business data to the cloud is one way out. Cloud systems provide scalable storage and consolidate data from different sources into a central repository. An EY-FICCI report also states that 78% of organisations are now implementing cloud strategies to modernise technology infrastructure and integrate intelligence into business applications. While companies failing to adopt cloud operations may not be able to utilise the full benefits of advanced technologies like GenAI, those doing so face significant challenges regarding effective and secure data management. 

To look at the hurdles and opportunities in AI-GenAI and data management, Inc42 and global IT services giant Oracle recently organised a roundtable in Bengaluru. Delving on the theme, Unlocking Data & AI Potential: Charting A Path To Innovation And Growth, it was the first of a two-part roundtable series titled Boardroom: Powering Data With AI and saw more than 10 tech leaders convene from various sectors, including deeptech, biotech, fintech, SaaS and more.

Moderated by Sameer Dhanrajani, CEO at AIQRATE & 3AI, the session brought together:  

• Naveen Budda, cofounder, KarmaLifeAI
• Vinay Rai, Executive VP, Netradyne
• Ramakrishna R, cofounder & CTO, CureSkin
• Alok Dube, chief architect, Embitel Technologies
• Henry Jacob, CTO, Quess Corp
• Parth Gaglani, head-product & analytics, Rocketium
• Amit Phatak, VP & head of decision intelligence, USEReady
• Dr Sudha Rao, cofounder & executive director, Genotypic
• Mayank Satnalika, director (AI and engineering), CloudSEK
• Anoop Mishra, senior director & head of data platform, Ace Turtle
• Pranjal Singh, data scientist, udaan
• Saravanan Palanivel, VP-cloud engineering leader, Oracle India

From Healthcare To Ecommerce: How AI Is Impacting Industries

The roundtable discussion began with a deep dive into specialised AI applications in different industry sectors. 

“AI has brought remarkable advancements in life sciences and pharmaceuticals,” said Rao of Genotypic. “In pathology [disease detection], for example, AI-driven image analytics can detect conditions like glaucoma earlier than traditional diagnostics. AI is also transforming demographic and genomic data use in image analysis, disease prediction, tumour classification and more.” 

Ramakrishna R explained how AI helps CureSkin build a large customer base beyond Tier I cities, although most dermatology specialists are based in those locations. “For us, AI is an optimisation tool bridging this gap,” he said.

“Besides, a single doctor can manage and treat hundreds of patients every day with the help of AI, a feat impossible to match without such technology,” he noted, highlighting AI’s prowess in diagnostic support and predictive analytics. 

Singh from Udaan (a B2B marketplace targeting SMEs) discussed the unique challenges businesses often face beyond the metros. “In Tier II and III cities [Bharat, to be precise], AI plays an important role in product discovery and related issues. Many customers in these regions are not tech-savvy. So, we have introduced features like vernacular and voice search to meet their preferences and improve their shopping experience,” he said.

Netradyne, a startup ensuring fleet safety, is another compelling use case. “We use AI, especially deep learning in computer vision, to enhance road safety. Our IoT devices with cameras and sensors are mounted on vehicles to monitor road conditions and evaluate driving safety. This technology has already led to a 50% reduction in accidents and the system is in the cloud for real-time analysis,” said executive vice-president Vinay Rai.

How Enterprises Are Navigating AI Adoption

In spite of doubts and fears, AI-GenAI and its many subsets have rapidly transitioned from futuristic concepts to core components of modern business strategies. Companies increasingly embed these technology tools into their operations as these technologies permeate everyday life. But this rapid adoption has a downside. The cost of adequate data security compels organisations to balance seizing tech advantages to drive growth and mitigating data risks.

“Yes, AI adoption is on the rise, but data security remains a significant concern,” said Dube of Embitel Technologies. “Many advanced language models, though highly effective, are not cost-efficient to run on-premises or on individual cloud instances. As a result, organisations often rely on well-trained models from open-source providers. While adoption is progressing, challenges around data security remain a barrier.” 

He explained that companies frequently utilise open-source AI tools for non-sensitive data they are comfortable sharing publicly. However, businesses remain cautious when handling sensitive information.

Saravanan from Oracle had a different perspective, though, he emphasised the synergy between AI & cloud for enterprises. 

He cited an example of “Horses for Courses” that every problem of GenAI will not be solved by one model and one model does not fit all. “For summarisation you require a model different from image creatio , than a language translation. Each model requires a set of data to get trained which are specific to use cases. Model using RAG (Retrieval Augmented Generation) trained on use case specific data, delivers higher accuracy with lesser hallucination,” he said.

Oracle for one, offers various models which are specifically trained for key enterprise use cases, some of them are Cohere, Llama, Hugging face & others 

“Data security is, of course, a concern for any AI use case. AI tools require large amounts of data, and the cloud provides a unified storage solution for this data. With more data, AI models become more efficient. Oracle offers solutions where your data remains within your own environment while still using shared AI models & delivers the results” he said

Saravanan added that for enhanced security, cloud providers often dedicate AI clusters to customers running large language models (LLMs), ensuring data isolation and protection through encryption.

“Most large banks have not fully embraced AI because they are often too comfortable with their existing rules and processes,” observed Mishra of Ace Turtle. 

Satnalika of CloudSEK concurred, saying psychological barriers hinder AI adoption in the financial sector. For instance, banks cannot justify subjective decisions like loan approval if the process becomes automated. 

Despite varying adoption rates across industries, one thing remains certain. Businesses are keen to keep pace with this latest technology to optimise internal processes, enhance customer service and maintain a competitive edge.

Industry data is in sync with this trend. According to a recent report, enterprise AI/ML transactions soared nearly 600%, jumping from 521 Mn a month in April 2023 to 3.1 Bn by January 2024. The US accounted for 40% of enterprise AI transactions, while India was second with 16% of global AI transactions, driven by the country’s increased focus on fostering innovation. The APAC region saw a 135% (1.3 Bn) jump in AI transactions, also attributed to India’s widespread adoption and usage of AI tools.

The road ahead is clear. Indian businesses will continue to invest aggressively in AI-GenAI and cloud technologies to stay competitive and drive growth. 

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