AI & ML Storage & DR

Full Benefits of AI/ML Yet to Be Realized: Racksapce

Skills, Data Quality and Lack of Organizational Buy-In Cited as Barriers; AI/ML Top IT Priority for Businesses, Alongside Cybersecurity  

 Rackspace Technology announced a new research report that finds that while 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.  

Jeff DeVerter, Chief Technology Evangelist, Rackspace Technology, said, “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,” “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.”   

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%).  

Progress, and Challenges  
With regard to AI/ML adoption, 45% of respondents cite difficulties aligning AI/ML strategies to the business. In addition, the cost of implementation rose to 38%, while 40% of respondents of nascent AI/ML technologies as a barrier.    

“The fact that many organizations are having trouble aligning AI/ML strategies to the business and navigating the plethora of new tools available indicates that projects are often falling victim to poor strategy,” added DeVerter. “Garnering support from the right stakeholders, coming to consensus on deliverables, understanding the resources necessary to get there, and setting clear milestones are critical components to keeping projects on track and seeing the desired return on investment.”  

Organizational Understanding  
From a talent perspective, more than half of respondents said they have necessary AI/ML skills within their organization. At the same time, more than half of all respondents say that bolstering internal skills/hired talent and improving both internal and external training are on their agenda.  

Comparing departments, 67% of respondents say IT staffs grasp AI/ML benefits while 45% say that operations, 46% R&D, 48% customer service, 49% senior management and boards understand the technologies. Sales, HR and marketing departments are considered by respondents to be the least AI/ML-savvy.  

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