Artificial intelligence and machine learning have reached enterprise maturity – no longer just flashy add-ons, they are essential components in information architecture. Businesses across all industries can harness these technologies, but, as Hexaware’s Vaidya JR points out, they must have a clear picture of their strategic and business goals before implementation.
In an era of accelerated digitalization, artificial intelligence (AI) and machine learning (ML) have fast become part of the IT infrastructure of many businesses. Consequently, how these technologies are being used to derive meaningful insights from vast quantities of data is maturing rapidly.
“Early on, when organizations didn’t have access to the computing power and zettabytes of data that they have today, AI was only springing up in pockets,” says Vaidya JR, SVP and global head of data and AI at IT transformation specialist Hexaware Technologies, “The approach then was to see what AI could do for a company, without truly identifying a well-defined problem. Data science solutions were just a shot in the dark.
“Organizations were struggling to put their data to effective use, which led to limited value generated and ineffectual business results,” he adds. “You can crunch any amount of data, and create numerous models; it only adds value if there is a significant impact on the business. But the current attitude has completely changed across industries, without exception.”
Continue reading: https://techmonitor.ai/technology/ai-and-automation/artificial-intelligence-and-machine-learning
In an era of accelerated digitalization, artificial intelligence (AI) and machine learning (ML) have fast become part of the IT infrastructure of many businesses. Consequently, how these technologies are being used to derive meaningful insights from vast quantities of data is maturing rapidly.
“Early on, when organizations didn’t have access to the computing power and zettabytes of data that they have today, AI was only springing up in pockets,” says Vaidya JR, SVP and global head of data and AI at IT transformation specialist Hexaware Technologies, “The approach then was to see what AI could do for a company, without truly identifying a well-defined problem. Data science solutions were just a shot in the dark.
“Organizations were struggling to put their data to effective use, which led to limited value generated and ineffectual business results,” he adds. “You can crunch any amount of data, and create numerous models; it only adds value if there is a significant impact on the business. But the current attitude has completely changed across industries, without exception.”
Continue reading: https://techmonitor.ai/technology/ai-and-automation/artificial-intelligence-and-machine-learning
