Indian enterprises have been quick to adopt AI in the recent years and have cited it as a key to their fundamental to growth. Over the next 18 months, seven in 10 firms are anticipated to leverage cognitive systems, indicating that AI technology will reach mainstream adoption by mid-2019, according to an Intel report. Given this scenario, what would India’s AI Maturity index be like?
According to an the report on AI Maturity in India, China and India seem to be heading the maturity score in terms of progress and adoption. The reason could be because both countries have fewer legacy systems and business processes to contend with, making AI adoption and integration easier to accomplish.
Despite aggressive investment in cognitive technologies, AI maturity in India sounds like a long shot and we are yet to see whether the technology will be mainstreamed in a matter of 18 months. On the other hand, the Infosys report has a positive take on the current state of AI. According to their survey, organisations which have been using AI technology for two years expect their companies to reach maturity in an average of three years. Infosys defines maturity in terms of technological capabilities and the use of AI technologies by employees and customers becoming standardised.
While it is true that enterprises are stepping up investment in beefing up IT infrastructure and developing knowledge and skills within the business, commenting on AI maturity will be too early. As part of the mandate, enterprises, especially telecom and healthcare companies are under immense pressure to embrace digital transformation. Indian companies have been cautious because they don’t want to fall for the hype and jump into emerging technologies with POCs that don’t align with their business strategy. Also, investing in new technologies such as machine learning or blockchain doesn’t necessarily translate into revenue as the timeline for return on investment is unclear.
So far, the transformation charge in India has been led by financial services organisations who are more focused on improving customer experience and are leveraging AI to improve sales and marketing functions. Also, banks have implemented AI for regulatory compliance and fraud reduction.
Why Indian Organisations Are Lagging Behind
It is true that investment in AI technologies can fast track to the next level of digital maturity, and beefing up the current suite of technologies ERP, cloud, analytics will pave the way for transformation, and Indian enterprises, including SMEs have been showing a readiness in adoption.
Indian enterprises are ramping up the infrastructure for AI adoption. For example, a NASSCOM 2017 report reveals that Indian hospitals have now started leveraging analytics more rigorously for clinical and non-clinical data in India. The report on digital readiness, carried out in collaboration with Frost & Sullivan noted that 43 percent of hospitals feel that data integration is crucial for creating a platform to implement analytics. Meanwhile, in terms of readiness and digital transformation, Indian telecom companies are far behind their global counterparts in terms of automation.
So, does India need to catch up with global peers? According to Haritha Ramachandran, associate director, Digital Transformation (ICT) Practice at Frost & Sullivan, investment in infrastructure, cloud, and managed services aims can bridge the gap between Indian and global players. “Digital transformation will, however, require timely policy intervention and infrastructure for IT-BPM sectors to support cloud implementations and improve security. Furthermore, verticals such as BFSI are seizing this as an opportunity so their fintech peers do not disrupt them. At the same time, the manufacturing industry is also looking to take production lines to the next level with Industry 4.0,” he said.
Other Challenges Also Abound
Even though Indian enterprises fare well in terms of readiness and adoption, there are several other challenges in the AI journey.
- With a number of AI projects being piloted, the C-suite is still trying to understand the cost of deploying the solutions across the unit and this requires justifying the scale of investment as well
- Another area that needs to be addressed is of cybersecurity, when it comes to migration and analysis of data using cloud infrastructure. A report reveals that cybersecurity issues surpass cost of solutions
- The talent crunch problem for consultation and implementation of cognitive solutions has been widely discussed. In fact, shortage of adequate talent has been cited as the second biggest roadblock in adoption of AI technology.
- In organisations that are still exploring AI, senior management buy-in and leadership mindset are the main barriers to adoption
Leading Indian IT bellwethers like TCS, Infosys, Wipro, HCL and global players like IBM, Intel and CTS are encouraging AI innovation. Also, senior management personnel have taken an evangelising role, discussing about their use cases spanning many industry verticals. Besides productivity gains, cognitive solutions will lower the operating cost structures significantly and bring in increased margins as well.
Try deep learning using MATLAB