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Rackspace Technology Study uncovers AI and Machine Learning knowledge gap in the UAE

Rackspace Technology Study uncovers AI and Machine Learning knowledge gap in the UAE

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As companies in the UAE scale up their adoption of Artificial Intelligence (AI) and Machine Learning (ML) implementation, a new report suggests that UAE organisations are now on par with their global counterparts in boasting mature capabilities in these fields.

Nonetheless, the vast majority of organisations in the wider EMEA region—including the UAE—are still at the early stages of exploring the technology’s potential (52%) or still require significant organisational work to implement an AI/ML solution (36%).

These are the key findings of new research from Rackspace Technology Inc, an end-to-end, multi-cloud technology solutions company, which revealed that the majority of organisations lack the internal resources to support critical AI and ML initiatives.The survey, ‘Are Organisations Succeeding at AI and Machine Learning?’,indicates that while many organisations are eager to incorporate AI and ML tactics into operations, they typically lack the expertise and existing infrastructure needed to implement mature and successful AI/ML programmes.

This study shines a light on the struggle to balance the potential benefits of AI and ML against the ongoing challenges of getting AI/ML initiatives off the ground. While some early adopters are already seeing the benefits of these technologies, others are still trying to navigate common pain points such as lack of internal knowledge, outdated technology stacks, poor data quality or the inability to measure ROI.

Other key findings of the report include the following:

  • AI/ML implementation often fails due to lack of internal resources — Half (50%) of respondents in the UAE report AI research and development initiatives have been tested and abandoned or failed. The failures underscore the complexities of building and running a productive AI and ML programme. The top causes for failure include lack of data quality (46%), lack of expertise within the organisation (36%), poorly conceived strategy (30%) and lack of production ready data (46%)
  • Successful AI/ML implementation has clear benefits for early adopters — As organisations look to the future, IT and operations are the leading areas where they plan on adding AI and ML capabilities. The data reveals that organisations in the UAE see AI and ML potential in a variety of business units, including IT (49%), finance (39%) operations (41%), and customer service (50%). Further, organisations that have successfully implemented AI and ML programs report increased productivity (44%) and improved customer satisfaction (38%) as the top benefits
  • Defining KPIs is critical to measuring AI/ML return on investment — Along with the difficulty of deploying AI and ML projects comes the difficulty of measurement. The top key performance indicators used to measure AI/ML success in the UAE include revenue growth (72%), data analysis (65%), profit margins (56%), and customer satisfaction/net promoter scores (46%)

“Countries across EMEA, including the UAE, are lagging behind in AI and ML implementation, which can be hindering their competitive edge and innovation,” said Simon Bennett, Chief Technology Officer, EMEA, Rackspace Technology. “Globally we’re seeing IT decision-makers turn to these technologies to improve efficiency and customer satisfaction. Working with a trusted third-party provider, organisations can enhance their AI/ML projects moving beyond the R&D stage and into initiatives with long-term impacts.”

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