Covering Disruptive Technology Powering Business in The Digital Age

Rackspace Technology®, a leading end-to-end, multicloud technology solutions company, today announced a new research report that finds that while Artificial Intelligence (AI) and Machine Learning (ML) are on nearly every organisation’s radar, much work remains to be done to tap their full potential. Rackspace Technology polled 1,870 global IT leaders, across industries, including manufacturing, financial services, retail, government and healthcare to understand the dynamics of AI/ML uptake. A total 187 Singapore correspondents participated in the survey.

99% of Singapore respondents said that AI/ML is a priority for their organization, and 72% of all respondents reported positive impacts on brand awareness, 68% reported revenue generation and expense reduction. However, 42% 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 organisation, and it’s clear that the AI/ML is advancing in its importance and visibility,” said Jeff DeVerter, Chief Technology Evangelist at Rackspace Technology. “At the same time, the research makes clear that many organisations 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. A total of 69% of respondents say they are employing AI/ML as part of their business strategy and 62% for IT their strategy, while 68% 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 the overall budget) of between 1% and 10% in last year’s survey.

AI/ML Projects are Accelerating

AI/ML are being used by Singapore organisations in an increasingly wide variety of contexts, including improving the speed and efficiency of processes (52%), understanding marketing effectiveness (45%); increasing revenue, gaining competitive edge, predicting performance (42%); and personalising content and understanding customers (41%).

In an indication of the increasing maturity of the technologies, 67% of respondents said their AI/ML projects have gone past the experimentation stage and are now either in the “optimising/innovating” or “formalising” states of implementation. Most organisations are also citing a wider range of use cases, including computer vision applications, automated content moderation, customer relationship management and biomedical applications.

Progress and Challenges

With regard to AI/ML adoption, 35% of Singapore respondents cite difficulties aligning AI/ML strategies to the business. In addition, the cost of implementation rose to 28%, while 37% of respondents of nascent AI/ML technologies as a barrier.

“The fact that many organisations 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.”

Organisational 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, 77% of Singapore respondents say IT staff grasp AI/ML benefits as compared to 48% in R&D, 46% in operations, customer service, senior management and boards understand the technologies. Sales, HR and marketing departments are considered by respondents to be the least AI/ML-savvy.

For more information on the trends that will shape AI/ML in 2022 and to download a copy of the full report, visit https://www.rackspace.com/lp/solve-ai-ml-research-report-2022.

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