By 2026, Indian employees will become 20% more productive owing to help from artificial intelligence, machine learning and natural language processing solutions in their decision making, according to a predictions report by global market research firm International Data Corporation.
About 60% of all Indian enterprises, by the next 4 years, will use AI/ML solutions as a critical component while taking their business decisions. Additionally, just in the next two years, 40% of large enterprises in the country will drastically expand the use of AI/ML solutions into critical functions such as marketing, supply chain logistics, legal, human resources and procurement.
“AI will increasingly fuel horizontal business function’s transition from administrative to strategic, and the workforce’s transition from consistent, to diversified and productive,” said Rishu Sharma, Associate Research Director, Cloud and AI, IDC India.
AI/ML will be combined with human expertise to increase employee productivity, deploy conversational AI applications across a wide range of use cases, and put start operations on certain workflows.
Another aspect that the report pointed out is process mining, defined as a method to turn event data into insights and actions. 30% of enterprises are expected to adopt process mining as an additional layer for business processes by 2025. IDC predicts that this 30% will be 20% more profitable in business as compared to peers who do not utilise process mining.
“With AI/ML offerings taking over/assisting humans in routine tasks in multiple industries including healthcare, BFSI, and others to stay competitive in changing times, employees will need to update their skills to work alongside new AI-driven workspace,” said Swapnil Shende, Senior Market Analyst, Cloud and Artificial Intelligence, IDC India.
The report also highlighted the growth of low-code adoption and how it will be used to pre-train computer vision models. By 2025, IDC predicts that 40% of companies using computer vision solutions will use a low-code environment to make their solutions learn and gain insights from sparse data sets.