In short:
As AI usage grows, costs need to be connected to teams, use cases and outcomes. But visibility isn't about using less AI – it's about directing AI towards greater value. That means measurement needs to be built in from the start and evolve as the way your organisation uses AI changes.
Three things to remember
- AI costs need to be connected to use cases, not just invoices.
- The goal is not to use less AI, but to direct AI usage towards greater business value.
- Measurement should be built in from the beginning – and evolve as the way people work evolves.
The hidden cost of AI
When AI consumption is not measured, costs cannot be allocated to the right teams or projects, nor linked to ownership and accountability. Instead, they become scattered across cloud invoices, software licences and Shadow AI, leaving no single budget line that reflects the full picture.
That is why AI often feels unpredictable – not because it is inherently expensive, but because it is invisible.
The goal is not to find one perfect KPI for every AI initiative. The goal is to measure whatever you are trying to improve. If your objective is quality, measure quality. If your objective is faster workflows, measure workflow performance. If your objective is risk reduction, measure risk.
A new KPI: How quickly can you change your KPIs?
|
KPI |
Question |
Why it matters |
|
KPI-agility |
How quickly can your organisation introduce, replace or retire a KPI? |
AI evolves faster than annual scorecards. If your measurement framework cannot evolve at the same pace, it will soon optimise for the wrong outcomes. |
Many organisations still rely on KPIs designed for a much slower world. AI changes both the way people work and the speed at which organisations evolve. Simply tracking yesterday's metrics is no guarantee that they still reflect today's reality.
One of the most important capabilities therefore becomes the ability to update your measurement framework. How quickly can you introduce a new KPI when an AI workflow changes? How quickly can you stop measuring something that no longer matters? How often do you review whether your KPIs are still encouraging the right behaviours?
Invisible AI spend is therefore about much more than the monthly invoice. It is about building a measurement framework that evolves at the same pace as AI adoption.
Estimating value (ROI Lite)
Building an initial business case does not have to be complicated. Start by asking three simple questions.
- What outcome are we trying to achieve?
- What does the solution cost?
- What assumptions need to be tested?
This could mean reducing processing times, improving the quality of decision-making, lowering operational risk or delivering better service to customers and employees.
Consider both implementation and ongoing operations, including data preparation, integrations, licences, infrastructure, change management, training and continuous monitoring.
Most AI initiatives are built on assumptions: how much value they will create, how frequently they will be used and whether they genuinely improve the work they are intended to support. Test those assumptions on a small scale before expanding and be prepared to change your KPIs as your understanding evolves.
Conclusion
Visibility is not a cost-cutting exercise. It is control. When AI costs can be linked to teams, use cases and business outcomes, they become easier to understand – and far easier to govern.
That governance must also be dynamic. AI is evolving too quickly for organisations to rely on the same KPIs year after year. A modern AI operating model requires not only better KPIs, but a better ability to create, replace and continuously evolve them.
