AI Readiness Assessment
Answer 18 questions across 6 key pillars to see how prepared your business is for AI adoption. Get a score, identify gaps, and know where to focus.
Is your business data centralised and easily accessible?
AI models need clean, accessible data. Siloed spreadsheets and disconnected systems make it nearly impossible to extract meaningful insights.
Do you have data quality processes in place (deduplication, validation, cleansing)?
Garbage in, garbage out. AI is only as good as the data it's trained on — poor quality data leads to unreliable outputs and bad decisions.
Is your sensitive data classified and labelled (e.g. with Microsoft Purview)?
Before deploying AI tools like Copilot, you need to know where your sensitive data lives and ensure it's properly protected from unintended exposure.
Are you using cloud platforms (Microsoft 365, Azure, AWS) that support AI workloads?
AI tools like Copilot, SageMaker, and Azure AI require modern cloud infrastructure. Legacy on-premises systems limit what's possible.
Do your systems integrate well, or are they mostly disconnected?
AI thrives on connected systems. If your CRM, finance, HR, and operations tools don't talk to each other, AI can't deliver cross-functional insights.
Do you have the licensing and platform access needed for AI tools (e.g. Copilot, Power Platform)?
Many AI capabilities are included in existing licences but not activated. Others require specific plans or add-ons to unlock.
Does your team have experience using AI tools (Copilot, ChatGPT, etc.) in their daily work?
AI adoption depends on people actually using it. Teams that experiment and build habits get far more value than those with unused licences.
Is there leadership support and enthusiasm for AI adoption?
AI initiatives without executive sponsorship tend to stall. Leadership needs to champion the change and allocate time and budget.
Have you invested in AI training or prompt engineering skills for your staff?
Knowing how to write effective prompts and understand AI outputs is a critical skill. Without training, teams underuse or misuse AI tools.
Do you have a documented AI strategy or roadmap?
A clear strategy prevents ad-hoc tool purchases and ensures AI investments align with actual business goals and measurable outcomes.
Have you defined success metrics for AI initiatives (time saved, cost reduced, etc.)?
Without measurable KPIs, it's impossible to know if AI is delivering value or just adding complexity. Define what success looks like upfront.
Is there a dedicated budget allocated for AI tools and implementation?
AI projects that compete with BAU budgets rarely get the focus they need. Dedicated funding signals commitment and enables proper planning.
Do you have policies governing how AI tools can be used in your organisation?
Without an acceptable use policy, staff may paste sensitive data into public AI tools, creating compliance and security risks.
Are you confident that AI tools won't expose sensitive or regulated data?
Data loss prevention, access controls, and sensitivity labels are essential before deploying AI across your business — especially in regulated sectors.
Do you monitor or audit AI usage and outputs within your organisation?
Responsible AI requires oversight. Monitoring usage patterns and reviewing outputs helps catch bias, errors, and shadow AI.
Have you identified specific business processes that AI could improve?
The most successful AI projects start with a clear problem to solve — not a tool looking for a use case. Focus on high-impact, repeatable tasks.
Have you run any AI pilots or proof-of-concept projects?
Small pilots with measurable outcomes build confidence and generate internal champions. They're the fastest way to prove value before scaling.
Can you quantify the time or cost your team spends on tasks AI could automate?
Understanding where manual effort is highest helps prioritise AI deployment and build a compelling business case for investment.
Your AI Readiness Score
Pillar Breakdown
Need help building your AI strategy?
Our AI Enablement programme takes you from assessment through to adoption — with Microsoft Copilot, data governance, and hands-on training.