Baseline
Understand the current AI operating reality.
How WAIA turns AI activity into workplace evidence that management can use.
WAIA connects baseline, guidance, workplace learning, real-work application evidence, evidence strength and accountable review so management can see what AI is doing to work.
Operating model
Six steps from adoption to evidence-led decision.
The loop keeps enablement and evidence connected. Learning helps people use AI better, and the application flow shows whether that use is improving work.
Usage tells you AI is being used. Training tells you people have been taught. Surveys tell you what people think. WAIA helps you establish what is actually happening to the work.
Evidence mechanics
WAIA separates evidence strength from value direction.
That separation is what keeps the product credible. A workflow can have strong evidence that AI is helping, strong evidence that AI is adding burden or insufficient evidence to decide yet.
Reported → Observed → Repeated → Validated
A single structured observation can become observed. Repeated evidence needs observations across time. Validated requires accountable human management review.
Positive, neutral, negative, mixed or unclear
WAIA doesn’t assume AI is creating value. Negative and mixed signals help management see where AI may be increasing checking, rework or risk.
Capacity discipline
Indicative capacity is evidence dependent.
Where evidence is strong enough, consistent and current, WAIA can show conservative indicative capacity ranges. Weak evidence, stale evidence, unclear outcomes or unsuitable workflow frequency can prevent calculation.
Indicative capacity released.
No material capacity change evidenced.
Indicative additional capacity required.
Capacity isn’t automatically a financial saving.
Illustrative example
A realistic evidence journey.
This is an illustrative scenario, not a customer case study. It shows the kind of operating question WAIA is designed to make visible.
AI is already in use
An organisation has introduced Copilot, while some teams also use ChatGPT for drafting, meeting notes and first-pass research. Usage spreads unevenly.
Evidence enters the flow
Learners record recurring workflows, frequency, net time change, checking and rework burden, outcome signal and plain workplace context.
Strength and direction separate
WAIA distinguishes Reported, Observed, Repeated and Validated evidence from whether the result is positive, neutral, negative, mixed or unclear.
Managers review what holds up
Stronger evidence can be grouped into organisation workflows, reviewed by accountable managers and used to decide what needs investment, intervention or more evidence.
Capacity stays conservative
Where the evidence supports it, WAIA can show indicative capacity. Where it is weak, mixed or stale, the product keeps that uncertainty visible.
Organisation journey
A practical start, not a transformation programme.
WAIA begins with the organisation's current situation and turns it into a manageable first rollout that can produce useful workplace evidence.
Fit conversation
Discuss current AI use, the operating concern and who needs to be involved.
Confirm scope
Agree the eligible population, administrators, sponsor and first rollout priorities.
Configure the organisation
Set the organisation view, guidance, baseline and initial learning pathway.
Establish the baseline
Create the initial operating picture before conclusions about value get ahead of evidence.
Publish guidance
Make practical expectations visible to the people who need to apply them.
Invite participants
Bring learners, managers and administrators into the first controlled rollout.
Review signals
Use progress, acknowledgement, evidence strength and attention signals to decide the next action.
Experience
What learners, managers and admins experience.
For learners
Practical workplace AI learning connected to local guidance.
- Scenario-based judgement practice.
- Visible organisation guidance.
- Guidance acknowledgement.
- Lightweight application evidence from real work.
- Reminders and progress.
For managers and admins
A current view of workplace evidence and the follow-up that matters.
- Baseline and attention signals.
- Learner progress.
- Guidance acknowledgement.
- Evidence strength and review signals.
- Practical rollout toolkit.
Product screenshots
The product connects the operating picture to next action.
Baseline
From result to action
The baseline points back to practical improvement areas inside WAIA.
Toolkit
Support uneven adoption
Managers and rollout leads get practical resources for check-ins, review habits and rollout conversations.
Guidance
Make standards visible
Organisation guidance gives people a local reference point for responsible use.
Product boundaries
What WAIA doesn’t replace.
WAIA supports evidence-led AI management. It doesn’t take ownership away from the organisation.
Advice and assurance
WAIA doesn’t replace legal advice, regulatory advice, HR advice or compliance certification.
Governance ownership
WAIA doesn’t replace internal governance ownership, risk decisions, management conclusions or human judgement.
Technical monitoring
WAIA isn’t enterprise GRC, technical AI model monitoring or employee surveillance. It’s also not an autonomous ROI engine.
Next step
Ask to see WAIA in the context of your organisation.
The first conversation is used to understand the current evidence gap, the eligible population and the first rollout scope.