EFFICIENCYAI

AI Readiness & Data Foundations

No AI without data. No data without assessment. Before any AI project begins, we assess your organisational readiness and audit your data landscape. The essential groundwork that makes AI actually deliver.

The problem

AI is only as good as the data behind it - and that's where most projects come unstuck.

We don't assume you're ready - we assess it. Most businesses have data scattered across multiple systems: spreadsheets, CRMs, project management tools, email inboxes, and paper records. When they try to deploy AI, the model has nothing reliable to learn from.

Our AI Readiness Assessment evaluates your organisation across five pillars: Strategy, Data, Technology, People, and Governance. Then our Data Foundations work ensures your infrastructure is ready before a single model is trained. It's not glamorous work - but it's the difference between AI that performs and AI that gets shelved.

AI Readiness Assessment (5 Pillars)

Evaluate organisational readiness across: Strategy, Data, Technology, People, Governance
Identify structural, organisational, and technical barriers to successful AI adoption
Documentation analysis of existing business logic
Inventory of under-utilised AI features in current vendor tools
Clear, jargon-free readiness report with actionable next steps

Agentic AI Preparation

Assess workflow suitability for agentic automation
Define bounded autonomy requirements
Escalation path design and human-AI handoff mapping
Governance framework recommendations aligned with UK AI regulatory landscape and EU AI Act

Data Quality & Readiness Audit

Data landscape mapping and quality scoring
Data quality and taxonomy audit
API accessibility and integration analysis
Data structure and integration mapping for system integration points

Data Pipeline & Infrastructure

Data pipeline design and architecture
Integration architecture for connecting disconnected systems
Data governance frameworks and documentation
Ongoing data health monitoring

Who this is for

SMEs that want to understand their AI readiness before committing budget
Companies with data scattered across multiple systems and no single source of truth
Organisations preparing for agentic AI integration
Businesses that have been told they need 'better data' but don't know what that means

Transparent pricing guidance

AI Readiness Assessment (1–2 weeks)£3,000–£6,000
Data Quality Audit (2 weeks)£4,000–£8,000
Data pipeline & governance projects£10,000–£30,000
Combined Readiness + Roadmap£8,000–£15,000

Exact pricing depends on the number of systems, data volume, and complexity. We'll scope it clearly before any work begins.

Frequently asked questions

What does an AI readiness assessment actually involve?

We evaluate your organisation across five pillars: Strategy, Data, Technology, People, and Governance. This includes stakeholder interviews, documentation review, data quality analysis, and technology audits. You get a clear, jargon-free report with a prioritised action plan.

How long does a data audit take?

A typical data readiness audit takes 2 weeks. We review your systems, interview key stakeholders, assess data quality, and deliver a clear report with recommendations and next steps.

What if our data is mostly in spreadsheets - can we still use AI?

Yes - many of the most valuable AI applications work with modest datasets. What matters is data quality, consistency, and accessibility, not volume. We'll help you build a path from spreadsheets to structured, governed data at a pace that works for your team.

Do you help implement data governance or just recommend it?

Both. We design the governance framework and then stay alongside your team to implement it. We believe in embedded delivery, not just report-writing.

What's the difference between data readiness and AI readiness?

Data readiness is one component of AI readiness. AI readiness also covers strategy alignment, technology infrastructure, people and skills, and governance. You can have good data but still not be ready for AI if the other pillars aren't in place.

Let's talk about your AI readiness

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