Pressure Mounts on CIOs to Build More AI Apps (and Faster)
Article written by Isabelle Bousquette and was originally published on WSJ.com February 16, 2023.
A tightening economy and the viral popularity of ChatGPT is spurring business interest in new enterprisewide AI applications. But chief information officers say they cannot keep up with demand, citing the time and costs linked with building, training and rolling out AI models.
Magesh Sarma, chief information and strategy officer for AmeriSave Mortgage Corp., said his team has been inundated with requests to build AI apps aimed at tackling various cost issues.
“We cannot say ‘yes’ to all their requests,” said Mr. Sarma.
Algorithms, which can contain huge numbers of variables and constraints, are time-consuming and costly to build. His team spent several years and approximately $20 million to $30 million in each of those years building one complex algorithm that performs some parts of the loan-underwriting process, he said. He added that each algorithm is unique and requires varying amounts of time and capital, depending on its scope, scale and the number of variables.
Generally, most of the cost is the salaries of data scientists and machine-learning engineers, who write algorithms, train them on data, test them, tweak them and then monitor them after deployment. Compensation for these roles has risen, in part due to the scarcity of available candidates.
The median salary for data scientists in 2022 was $156,000, up from $151,840 in 2021, according to staffing firm Mondo, an Addison Group Company.
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Tech chiefs are facing a rush of demand from corporate teams for AI apps they hope will save money without too much delay.
The Wall Street Journal cites Mondo insights as a key source for understanding the growing demand in AI technology and the data analysts roles needed to support emerging trends.
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