SINGAPORE – Media OutReach – 28 June 2021 – AI Singapore (AISG) has launched its AI Readiness Index (AIRI), a comprehensive and easy-to-implement business-focused framework that helps organisations to self-assess the status of their artificial intelligence (AI) adoption readiness.
AIRI, Singapore’s first-of-its-kind, will help these businesses to measure their latest AI adoption and enable them to seek strategies and solutions in their AI pursuits.
The move is part of Singapore’s National AI Strategy, a whole-of-nation effort comprising Singaporeans, businesses, researchers and movement to work closely together to foster a Smart Nation.
Once businesses undertake this self-test at https://aisingapore.org/airi/, they will be able to identify the gap between their current and desired states.
A system-generated report will categorise their organisations into one of the following four categories: AI Unaware, AI Aware, AI Ready, and AI Competent.
Subsequently, they can leverage appropriate programmes to embark on a journey to improve their AI readiness.
AISG envisages that for organisations that are AI Unaware, the focus will be on increasing their AI literacy. For entities that are AI Aware, the goal would be to prepare them to adopt AI solutions. For organisations that are AI Ready, the aim is to help them to accelerate their AI adoption. Finally, AI Competent organisations will be encouraged to deepen their organisational AI capabilities.
These approaches will enable an organisation to ascertain the next steps, principally how it can move forward with a targeted approach to improve its organisational AI readiness. Businesses can also choose to continue the discussion with AISG on mapping their next steps forward towards AI adoption.
“AI is going to be pervasive in all aspects of life in the near future. AISG has worked hard to develop this index by translating the learning points and outcomes from our engagements with hundreds of companies,” says AISG Executive Chairman Professor Ho Teck Hua.
“The index is a critical and practical tool that will enable Singaporean businesses to benchmark their AI preparedness. It will also give companies a baseline they can use to further their adoption and use of AI,” he adds.
Dr Chng Zhenzhi, Director, National AI Office, Smart Nation and Digital Government Office, said: “AIRI is a useful tool for organisations to assess where they stand in their AI journey. AISG has been supporting Singapore’s National AI Strategy by growing a pipeline of local AI talent … AIRI will enable AISG to better tailor its suite of programmes to each organisation’s needs, and be more effective in helping organisations use and benefit from AI.”
As part of AISG’s effort to seed greater awareness of AIRI, it will collaborate with various industry partners and trade associations to get their customers and members to undergo the AIRI assessment. Some of the leading partners on board include Dell Technologies Singapore, Microsoft Singapore, Singapore Polytechnic and SGTech.
AI Readiness Index Framework
The AI Readiness Index consists of four main pillars which map to nine dimensions of assessment.
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Pillars (4) |
Dimensions (9) |
Assessments |
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Organisational Readiness
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AI Literacy
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Whether the employees could identify potential AI use cases and be savvy consumers of AI solutions
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AI Talent
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Whether the organisation has the capabilities to develop, integrate, and maintain AI models
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AI Governance
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Whether the organisation has policies to guide the development and application of trustworthy AI solutions
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Management Support
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Whether the organisation has allocated resources for AI initiatives
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Business Value Readiness
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Business Use Case
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Whether the organisation has identified suitable AI use cases and assessed their value propositions |
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Data Readiness
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Data Quality
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Whether the organisation has processes to ensure the quality (accuracy, completeness) of data collected |
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Reference Data
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Whether there is a single source of truth, consistency of data format, and reliable metadata |
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Infrastructure Readiness
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Machine Learning Infrastructure
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Whether the organisation has appropriate and sufficient ML infrastructure (e.g., GPU, memory) to support AI model training and deployment |
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Data Infrastructure
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Whether the organisation is using appropriate data infrastructure (e.g., data lake) as a central repository of data |
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