Capability
AI Readiness Diagnostics
The evidence work behind an AI readiness assessment: data profiling, a review of systems and integrations, process walkthroughs and structured interviews, scored on six axes. Leadership gets a baseline built on what the data and systems actually show, not on opinion alone.
A readiness score is only as good as the evidence behind it. We collect that evidence directly from your data, systems and teams.
01Architecture
Reference architecture
A typical arrangement of the components. Every implementation is adapted to your systems, data-residency and security requirements.
Evidence sources
- Structured interviews
- Policies and documents
- Data samplesSQL
- System inventory
Analysis
- Data profilingpandas · ydata-profiling · Great Expectations
- Process mappingBPMN
- Architecture reviewC4 model
Scoring
- Six-axis maturity scale
- Evidence register
Outputs
- Readiness reportPower BI
- Gap and action list
02Components
What this capability covers
01
Data profiling
Samples from priority sources checked for completeness, consistency, ownership and usable history.
02
Systems and integration review
A map of core systems, interfaces and hosting constraints, including where data may and may not go.
03
Process walkthroughs
Time with the people who do the work, to see where decisions, delays and manual effort really sit.
04
Evidence-based scoring
Each of the six axes scored on a five-level scale, with the evidence behind every score recorded so it can be challenged and repeated.
03Implementation
How we implement it
We agree the axes, the scale and the evidence each score needs before the first interview. Data and system reviews run in your environment or on samples you approve, so nothing leaves your control without agreement.
- Interviews follow a structured guide per axis, so answers can be compared across departments.
- Data profiling runs on approved samples, and the scripts are handed over with the findings.
- Scores and the evidence behind them are kept in one register your team can update later.
04Deliverables
What you receive
Readiness baseline on six axes
Data profiling findings and scripts
Systems and integration map
Evidence register and prioritised actions
Technology
Technologies we work with
- Python
- pandas
- ydata-profiling
- Great Expectations
- SQL
- BPMN
- C4 model
- Power BI
Chosen per project and aligned with your existing standards. Listed as technologies we use, not as partnerships or endorsements.
05Use cases
Typical applications
Patterns this capability is designed for, not a list of delivered projects.
01
Baseline before an AI programme
An agreed starting point, so progress on each axis can be measured in the following year.
02
Data check before a pilot
Confirms whether the data a proposed use case relies on exists, is accessible and is good enough.
03
Review of running initiatives
Pilots already under way assessed on one scale, so leadership can decide which to expand, fix or stop.
06Related
Where to go next
Industry contexts
More in Advisory & Assessment
- AI Roadmap & Target Architecture
Turns a scored opportunity portfolio into a sequenced plan: which initiatives come first, what they depend on, the target architecture that supports them and the business case for each.
Next step
Scope AI Readiness Diagnostics for your organisation
Share your process, data and constraints. We will propose an approach, the evidence to collect first and a realistic plan.