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New Rackspace Technology Report Finds AI/ML Technologies

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Rackspace Technology, a leading end-to-end, multicloud technology solutions company, today announced a new research report that finds that while Artificial Intellegence and Machine Learning (AI/ML) are on nearly every organization’s radar much work remains to be done to tap their full potential. Rackspace Technology polled 1,870 global IT leaders including India, across industries, including manufacturing, financial services, retail, government, and healthcare to understand the dynamics of AI/ML uptake. 205 Indian correspondents participated in the survey.

The India data reveals that while 68% of respondents said that AI/ML is a high priority for their organization, and 71% of all respondents reported positive impacts of on brand awareness and 68% on reputation, as well as revenue generation and 62% on expense reduction, 43% agreed that measuring and proving the technologies’ business value remains a challenge.

“As AI/ML budgets continue to increase, we are seeing projects proliferate across more areas of the organization, and it’s clear that the AI/ML is advancing in its importance and visibility,” said Jeff DeVerter, Chief Technology Evangelist, Rackspace Technology. “At the same time, the research makes clear that many organizations still struggle with getting stakeholder buy-in, addressing issues of data quality, and finding the skills, resources and talent to take advantage of the AI/ML’s full potential.”

According to the report – AI/ML is a Top Priority for Businesses, but are They Realizing Its Value? – AI/ML ranks among the top two most important strategic technologies for organizations, alongside cybersecurity. 60% of respondents say they are employing AI/ML as part of their business strategy, 70% IT strategy, while 63% of respondents are allocating between 6% and 10% of their budget to AI/ML projects. This compares to a reported spend (as a percentage of overall budget) of between 1% and 10% in last year’s survey.

AI/ML Projects are Accelerating

AI/ML are being used by organizations in an increasingly wide variety of contexts, including improving the speed and efficiency of processes (50%), personalizing content and understanding customers (49%), increasing revenue 49%, gaining competitive edge 51% and predicting performance (51%), and understanding marketing effectiveness (48%).

In an indication of the increasing maturity of the technologies, 37% of respondents said their AI/ML projects have gone past the experimentation stage and 28% are now either in the “optimizing/innovating” or “formalizing” states of implementation. Most organizations are also citing a wider range of use cases, including computer vision applications, automated content moderation, customer relationship management, and biomedical applications.

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