Where is AI actually being used in recurring work?
WAIA is for organisations that need evidence of what AI is doing to work.
WAIA is relevant when AI use, local guidance, learning and examples from real work are hard to see together. Managers need a clearer basis for deciding what to do next.
Organisational signals
Use WAIA when these questions are becoming unavoidable.
Is that work getting better, worse or simply more active?
How much checking or rework is AI introducing?
Which AI value claims are anecdotes and which are stronger evidence?
Where does the evidence support a defensible indicative capacity signal?
Where should management invest, intervene or gather more evidence?
Are several people describing the same workflow in ways that risk double counting?
Buyer routes
Different roles need the same answer.
We’re spending time and money on AI. What evidence do we have that it’s improving work?
AI investment is visible, but evidence of workplace value is still too anecdotal.
- See where AI is being applied to work.
- Establish accountability.
- Distinguish confidence from wishful thinking.
- Review evidence and decide the next move.
Practical AI learning is needed, but completion alone doesn’t show whether work improved.
- Connect learning to workplace judgement.
- Publish practical guidance.
- See acknowledgement and learning participation as context.
- Create evidence from real application, not extra admin.
AI-assisted work is entering live processes with unclear value and inconsistent review habits.
- Identify checking, rework and workflow drag.
- Improve manager visibility.
- Agree what needs checking before work is used.
- Use evidence to decide where to intervene.
AI activity is visible, but evidence of what changed in the work is fragmented and difficult to defend.
- Use AI Baseline to review reported concerns.
- Keep learning participation separate from workplace evidence.
- Identify evidence that is ready for review.
- Keep conclusions current after launch.
Managers need to see how AI is being used and give people clear guidance without monitoring every prompt.
- Make approved guidance visible.
- Record acknowledgement.
- Support clearer escalation and review behaviour.
- Provide workplace evidence without replacing governance functions.
Good fit
Use WAIA when you need to know whether AI is improving work.
- AI use is already happening in real work.
- You have or need an AI policy, but need behaviour to match it.
- Managers need clearer review expectations.
- You need evidence of workflow impact, not only activity.
- You want people to use AI well without heavy enterprise governance.
Not the right fit
WAIA is intentionally not a catch-all AI product.
- You need a full enterprise GRC platform.
- You want technical model monitoring.
- You need employee surveillance.
- You need a precise financial ROI calculator.
- You only want a prompt library or one-off inspirational workshop.
- You need legal or regulatory certification.
Employee boundary
Evidence should not feel like surveillance.
WAIA captures lightweight examples from real work alongside learning. Employees aren’t asked to become analysts, and WAIA doesn’t monitor prompts, score individual productivity or turn every task into a time study.
Practical for participants
People describe real workflows in plain workplace terms, including what changed, what needed checking and what still feels uncertain.
Useful for managers
Managers see evidence quality and review signals without being asked to inspect private prompt histories or infer individual productivity.
Owned by humans
Validated conclusions require accountable management review. WAIA supports the judgement, it doesn’t make the judgement alone.
Starting questions
Questions to ask internally before a fit conversation.
Current use
Where is workplace AI already being used, and who is accountable for AI-assisted output quality?
Shared standard
What guidance can employees actually apply, and what happens when use falls outside the expected standard?
Evidence
Can managers see whether evidence is reported, observed, repeated or validated, and what conclusion it supports?
Early customers
Start with a clear management question.
WAIA is a young product. The right founding customers should want a close implementation relationship, practical feedback and regular review of evidence from real work rather than a finished case-study library.
Direct implementation support
Start with an agreed group, named administrators and a practical first evidence priority.
Closer product feedback
Work directly with the WAIA team as the product is refined around real operating questions and management review needs.
Structured evidence review
Use early examples to understand what evidence is strong, what is weak and where further observations are needed.
Future case study only if justified
A public story should only be agreed if outcomes genuinely support it and both organisations approve the wording.
Next step
Ask to see whether WAIA fits your organisation.
The first conversation is used to connect your current management questions with an agreed group and first evidence priority.