Enterprises are in the process of leveraging AI at scale, while multiple questions still linger – are the solutions capable of fulfiling business expectations? What are the key tenets of a successful AI implementation strategy? What role does data play for AI implementation to be successful? What are some of the key trends in AI in India in the past year? What is the role of data strategy in deriving the best value from AI investments?
Growth of Artificial Intelligence
Businesses in India, until a few years back, were not embracing AI as a mainstream technology. Multiple factors such as the increased need to improve early detection of disease and prevention; provide personalised learning; Industry 4.0; enhance
IT infrastructure resiliency, need for enhanced customer experience; and others lead to the adoption of advanced computing, thereby increasing overall AI spending in India. Moreover, factors such as the generation of huge data volumes, improved digital infrastructure, and technological advancements in data management and cloud have enabled AI growth in India. Seeing the widescale opportunity in improving efficiency that businesses can achieve, enterprises today are optimistic about leveraging AI. As per IDC’s worldwide Artificial Intelligence spending guide, V1 2022, the overall AI spending in India has reached $759.6 million in 2021, showcasing about three times the growth of over 216% when compared to the AI spend in 2018.
Benefits of AI
Benefits of AI vary across industries with different use cases ranging from analysing images in healthcare for early disease detection to robotic automation and advisory in BFSI and others. Despite the huge potential that AI can bring to businesses, certain challenges hamper the widescale adoption of AI in India. IDC research reflects that organisations need to overcome a variety of challenges to adopt AI solutions — disruptive results to current business processes, lack of follow-up from the business units, lack of necessary data, and others have been some of the reasons behind enterprise failures in their AI projects in India. The amount of data being generated and made available to train AI systems is critical for a successful AI implementation.
IDC‘s conversations with business leaders in India reveal that for enterprises, leveraging data to understand the entire ecosystem of partners, employees, and suppliers is among the top priorities. Moreover, according to IDC’s Future Of Intelligence August 2021 survey, 19.7% of respondents in India stated the lack of data literacy as a major enterprise intelligence challenge.
Driving optimal data utilisation
The Indian government’s push for digitisation along with the increasing adoption of AI/ML, deep learning, and IoT-based technologies has imbibed the need for developing a data culture within enterprises that drives optimal utilisation of data and content to enhance enterprise intelligence, and how a lack of data literacy acts as a major roadblock for that process. In February 2022, IDC predicted that by 2026, to elevate their data culture, 40% of large enterprises in India will have data literacy programs, including training to help employees spot misinformation and communicate or influence with data.
With data playing a key role in deriving insights and shaping business and operational strategies, organisations are realising the advantage of adopting AI/ML technologies in driving human-machine augmented foresight. IDC predicts that, in India, by 2024, 20% of business intelligence solutions will incorporate intelligent knowledge networks, extending core ML-based user augmentation with collaborative and collective intelligence functionality.
Aligning business intelligence with ROI
Enterprises in India are looking to incorporate AI/ML technologies into automating data processing and analytics workflow steps to enable business intelligence solutions to ingest, clean, transform, and catalogue data for real-time analytics. To enhance the quality of data analytics and forecasting models, businesses are looking to integrate Business Intelligence and Analytics (BIA) solutions with emerging technologies such as crowdsourcing, swarm intelligence, and prediction markets.
Vendors and service providers play a key role in the success of enterprise AI initiatives by providing the necessary skills and supportive IT infrastructure to deliver better ROI. As data becomes an integral component of enterprise intelligence, service providers have started focusing on providing solutions that enhance operational efficiencies, improve customer service, and achieve cost efficiency. Enterprises plan to focus on becoming more data-led to take critical business decisions and provide personalised offers or analyse targeted stuff for customers.