For organisations adopting or scaling AI, this self-assessment shows how ready you are to govern it responsibly. It builds a structured view across seven capability groups and nineteen capabilities — spanning governance and accountability, data, trusted development, human oversight, safety and security, transparency, and using AI for the public good — all aligned to Singapore's Model AI Governance Framework.
Many organisations are expanding their use of AI faster than their ability to govern it. Responsibility for AI decisions is often unclear, data and oversight controls lag behind the technology, and leaders hold very different views of how ready the organisation really is. Existing dashboards and controls rarely show these governance gaps, so weaknesses stay hidden until an incident, a complaint, or a regulator brings them to light.
This diagnostic is built for organisations adopting or scaling AI, and for the leaders who answer for it. That includes risk, legal and compliance, data and analytics, technology, and operations functions who need a shared, structured view of AI governance readiness rather than competing opinions. It suits organisations in any industry that want to compare where their leadership team agrees and where their views of readiness diverge.
The assessment is organised as a two-tier framework. Each capability group brings together the specific capabilities that determine whether your organisation can adopt and live up to Singapore's Model AI Governance Framework in practice.
How your organisation directs and controls its use of AI — setting who is responsible, how risks are weighed, and how decisions are recorded and owned.
Nobody owns AI decisions, so risks go unmanaged.
How your organisation looks after the data that feeds AI — where it comes from, how good it is, how privacy is respected, and how copyright is handled.
Poor data makes AI inaccurate, unfair, or unlawful.
How you build, test, and release AI responsibly — with good development habits, honest evaluation, and careful, staged rollout you can control.
Untested AI released too fast fails in public.
How you keep people meaningfully in control of AI — matching human involvement to the risk of each decision and letting people step in when needed.
Unchecked AI decisions cause harm nobody caught in time.
How you keep AI safe from attack, aligned with its purpose, and ready to recover — protecting systems, checking behaviour, and responding fast to incidents.
An attacked or misaligned AI causes damage unchecked.
How open you are with the people affected by AI — disclosing how it is used, making AI-generated content clear, and giving people a way to raise concerns.
Hidden AI use breeds suspicion and lost trust.
How you use AI to benefit society and your people — applying it to genuine public value and building the skills your workforce needs to use it well.
AI that ignores people leaves everyone behind.
You get a clear, structured read-out of your organisation's AI governance readiness, with strengths, blind spots, and weaknesses set out plainly and the practical next steps to close the gaps.
The diagnostic turns a broad governance framework into specific, answerable capabilities. Instead of asking whether you are "compliant", it asks focused questions about the everyday practices that make responsible AI real — from who owns AI decisions to how you test models and how you tell people when AI is involved.
The following examples illustrate typical situations where organisations use this playbook. They are intended to show when the assessment is most valuable and how it can help leadership teams identify capability gaps, build consensus, and prioritise improvement initiatives.
Business challenge: The group is rapidly expanding its use of generative AI, but the leadership team holds very different views of how ready the organisation is. There are concerns about weak AI governance and oversight, unclear decision rights, and fragmented data, with no shared picture of where the real gaps sit.
How SuccessOf.ai and the playbook are used: The Chief Risk Officer runs the assessment with a cross-functional leadership group from risk, legal, data, and technology. Using the capability groups Governance and Accountability, Data Governance and Management, and Safety, Security and Incident Response, the team creates a common structure, compares perspectives, and establishes a shared view of strengths and gaps.
Beneficial result: The group gains a clearer shared view of its capability gaps and improved leadership alignment. It can sequence improvement work more deliberately, focus attention on governance, data, and oversight, and set a baseline for future reassessment before scaling AI further.
Business challenge: The agency is under pressure to deploy AI for public services but faces unclear responsible AI controls, a digital and AI skills gap, and weak human oversight of automated decisions. Leaders are unsure where capability weaknesses are constraining progress and how to prioritise limited resources.
How SuccessOf.ai and the playbook are used: The Chief Technology Officer uses the playbook with a cross-functional leadership group to compare perspectives across Human Oversight and Decision-Making, Transparency and Stakeholder Trust, and AI for Public Good and Workforce. The assessment helps the team establish a shared view and understand where weaknesses are holding delivery back.
Beneficial result: The agency reaches a more deliberate prioritisation of its AI work, with a stronger focus on skills, human oversight, and public value. It is better prepared before scaling AI initiatives and has a shared baseline it can revisit as capabilities improve.
It is built for organisations adopting or scaling AI and the leaders answerable for it, including risk, legal and compliance, data and analytics, technology, and operations functions who need a shared view of readiness.
It assesses your organisation across seven capability groups and nineteen capabilities, aligned to the focus areas of Singapore's Model AI Governance Framework, covering governance, data, development, human oversight, safety and security, transparency, and public good.
You receive a dashboard scored across all nineteen capabilities, with blind spots and weaknesses flagged explicitly, and prioritised recommendations across five action types: Leverage Technology, Deploy Training, Re-engineer Processes, Recruit Talent, and Outsource.
Yes. Colleagues can respond independently and compare perspectives in a shared team view, so you can see where leaders agree on AI governance readiness and where their views diverge.
The capability groups and capabilities are mapped to the focus areas of Singapore's Model AI Governance Framework, so your results follow a consistent structure you can compare over time and reassess as your AI use matures.