IT/ITes, manufacturing businesses to derive maximum benefit from AI-powered solutions: Report

According to the latest report by PwC titled Artificial intelligence in India – hype or reality, machine learning is the most popular (63%) AI-powered solution in the IT/ITes industry, followed by decision-support systems, Virtual Private assistants (VPA), robotics, etc. This sector is at the forefront of AI research and commercial deployments, it is likely to cater to multiple client industries with a range of AI-powered solutions.

 

The banking, financial services and insurance (BFSI) industry, however, considers robotics, along with machine learning and automated data analysts (44% of the participants for each), to have the highest impact on their business.

 

In the manufacturing sector, decision makers/influencers seem to lean towards a mix of machine learning solutions (50% of the participants), decision support systems, and automated communications and automated research and information aggregation solutions (40% of the participants each) in terms of how they perceive the above solutions to impact their business over the next few years. AI solutions, combined with other enabling fields such as industrial Internet of things (IIoT) devices and platforms, are expected to play a significant role in paving the way for smart manufacturing and Industry 4.0. 

 

Overall, the survey results have indicated that business decision makers/influencers perceive machine learning solutions, virtual private assistants followed by decision support systems, automated research and information aggregation solutions and automated data analysts to be the most impactful for businesses in the near future, with approximately 36–51% of the participants vouching for each of their expected impact potential. 

 

As AI is all set to bring about a revolution in the business landscape, businesses and consumers are bound to be divided on how quickly and eagerly they should adopt and integrate the new applications and workflows arising from it. During the initial phases in particular, businesses will need to identify the requisite data, direct training processes and refine outputs.