Business Objectives
Are AI initiatives linked to measurable outcomes — revenue, cost, cycle time, quality — or just to "doing AI"?
Flagship Service · AI Readiness
AI Readiness Assessment for SMEs.
Know where AI will create value before you invest.
Most organisations are asking "How do we start with AI?" The better question is: "Are we actually ready for AI?" Our AI Readiness Assessment identifies the workflows, data, processes and organisational factors that determine whether AI initiatives succeed or fail.
Example AI Readiness Scorecard
What an AI readiness score looks like
An anonymised example output. Every assessment produces a clear, defensible score across the six dimensions that actually predict whether AI initiatives ship.
AI Readiness Radar
Sample output
What we assess
Six dimensions that predict AI success
Our AI readiness framework looks beyond technology. We evaluate business, operational and governance readiness — the factors that actually decide whether AI projects deliver.
Data Readiness
Is your data accessible, usable and trustworthy? We audit sources, structure, quality, ownership and gaps.
Process Suitability
Which workflows are genuine candidates for automation or augmentation — and which are better left alone?
Technology Readiness
Can current systems, integrations and cloud footprint support AI deployment on Azure, AWS or hybrid?
Governance & Risk
Are security, data protection, model oversight and compliance in place — or being left until "later"?
People & Team Readiness
Do staff understand how AI will affect their work? Is there capacity, capability and appetite to adopt it?
Why AI projects fail
The five reasons SME AI initiatives stall
Most failed AI projects fail for non-technical reasons. A structured readiness assessment surfaces these risks before you spend.
No Clear Business Case
Technology looking for a problem. AI is adopted because the board asked, not because a measurable outcome was defined.
Poor Data Quality
AI cannot compensate for incomplete, inconsistent or untrustworthy data. Quality issues invalidate outputs and erode trust.
Lack of Ownership
Nobody is accountable for outcomes. The project lives between IT, operations and the executive team — and quietly dies there.
Governance Gaps
Security, compliance and model oversight are left until "later". A single incident then halts the entire programme.
Starting Too Large
Ambitious enterprise-style programmes attempted before proving value. By month six, momentum and budget are gone.
People Not Brought Along
Adoption is treated as a tooling decision, not a change programme. Staff resist or quietly bypass the new system.
Assessment to roadmap
From Readiness Assessment to AI Roadmap
The same path every client follows — from honest evaluation to production AI you can rely on.
- 1Assessment
- 2Readiness Score
- 3Opportunity Mapping
- 4Prioritised Use Cases
- 5Implementation Roadmap
- 6Production AI Solutions
Typical assessment deliverables
What you receive at the end
A practical, board-ready package — not a slide deck. Everything is written so it can be acted on by your team next week.
AI Readiness Score
A structured evaluation across the six key business areas, with overall and per-dimension scores.
Opportunity Matrix
Ranked AI opportunities plotted by business impact vs. implementation effort — so the first move is obvious.
Risk Assessment
Security, governance and operational considerations identified up front — with mitigation recommendations.
Implementation Roadmap
Practical next steps for the next 3, 6 and 12 months — including build vs. buy guidance and indicative budgets.
Executive Summary
Clear, jargon-free recommendations for leadership teams and the board — ready to circulate.
Leadership Walkthrough
A 60-minute working session with your leadership team to walk through findings, score and recommendations.
Designed for SMEs
Built for SMEs, not slide-ware
Most AI readiness frameworks are built for large enterprises — with the cost, complexity and timelines to match. Our approach is designed for SMEs and mid-sized organisations that need practical answers, realistic budgets and achievable implementation plans.
No enterprise jargon. No 80-page strategy documents nobody reads. Just a clear view of where AI will create value, what to do first, and what to leave alone.
Quick wins
Operational efficiency
Revenue improvement
Practical implementation
Realistic budgets
Frequently asked
AI readiness assessment FAQs
What is an AI Readiness Assessment?
A structured evaluation of whether your organisation is genuinely prepared to adopt AI. We score strategy, data, processes, technology, governance and people, then map the workflows where AI is most likely to create value. The output is a written AI implementation roadmap your team can act on.
How long does the assessment take?
Two weeks end to end. Week 1 is discovery — stakeholder interviews, data and process review. Week 2 is scoring, opportunity mapping and roadmap. Delivered with a 60-minute leadership walkthrough.
How much preparation is required?
Very little. We need 4–6 short stakeholder interviews and a look at how data and key workflows are run today. You do not need to prepare documents in advance.
Will we receive a readiness score?
Yes — an overall AI readiness score out of 100 plus individual scores across the six dimensions. Each score includes a written explanation and recommended next steps, not just a number.
Can you help implement the recommendations?
Yes, but you are under no obligation. Many clients move from assessment into AI strategy consulting, custom AI development or AI automation with us. Others execute internally. Both are fine.
What happens after the assessment?
You leave with a prioritised AI implementation roadmap covering the next 3–12 months. The typical next step is to design and build the top-ranked use case, then deploy it into production under our managed hosting and support model.
Can you support deployment and hosting?
Yes. We deploy and operate AI systems on managed Azure and AWS infrastructure — CI/CD, monitoring, backups and security included. Your team does not need DevOps headcount.
Do you work with Azure and AWS?
Yes. We work with Azure OpenAI, Azure ML and AWS Bedrock, plus open-source models hosted in your own cloud tenant. We recommend the right platform based on your data, compliance requirements and existing infrastructure.
Final step
Before you build AI, make sure you’re ready
The fastest way to waste money on AI is to start without understanding where it will create value. A structured AI readiness assessment gives you a practical roadmap, reduces implementation risk and aligns your leadership team around what to do first.