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Cisco: AI Readiness Index in Saudi Arabia 

by Madaline Dunn

Cisco’s AI Readiness Index in Saudi Arabia has been released, developed in response to the accelerated adoption of AI. 

The Index was based on a double-blind survey of 8,161 private sector business and IT leaders across 30 markets, and conducted by an independent third-party surveying respondents from companies with 500 or more employees. 

It assessed respondents’ AI readiness across six key pillars: 

  • Strategy, 
  • Infrastructure, 
  • Data, 
  • Talent, 
  • Governance, and 
  • Culture.

Companies were examined across 49 different metrics under these six pillars to determine a readiness score for each and an overall readiness score for the respondents’ organisation. 

Each indicator was assigned an individual weightage based on its relative importance to achieving readiness for the applicable pillar. 

Based on their overall score, Cisco has identified four groups at different levels of organisational readiness – Pacesetters (fully prepared), Chasers (moderately prepared), Followers (limited preparedness), and Laggards (unprepared). 

While the report found that 93 per cent of organisations in KSA have an AI strategy in place or under development, just 8 per cent consider themselves fully prepared to deploy and leverage AI.

The Index found that the top outcomes companies are looking to drive through the adoption of AI are increasing efficiency and productivity.

Opening new revenue streams was the lowest on the list of expectations, as ranked by 30 per cent of respondents.

Elsewhere, 31 per cent of KSA respondents ranked comprehension and proficiency of AI tools and technologies as the primary skill gap. 

However, 82 per cent say they are investing in training employees in this area.

Likewise, on infrastructure, the survey shows that just 12 per cent of local organisations in KSA have networks that are fully flexible to handle the complexity of AI workloads. 

Cybersecurity also needs increased focus, it was shared, with 70 per cent of respondents falling short of being “fully equipped” to detect and prevent adversarial attacks on AI models.

Read the full report here.

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