Knowing you spend £2M on AI is the start. Knowing which department spent it, on what, and whether it generated value — that's the conversation that changes behaviour.
When AI spend sits in a central IT budget, every department benefits but none bears the cost. The result is predictable: over-provisioning, low engagement, and no mechanism to redirect spend toward the use cases that actually deliver value. Finance asks which AI investments are working. The honest answer is nobody knows — because nobody has the attribution data to tell them.
Chargeback changes the conversation. When Engineering sees a £40K monthly line item for code-assist tools, and Marketing sees a £28K attribution for generative content, both questions change — which features are being used, which aren't, and whether the next renewal should look different. Cost visibility at department level is the governance lever that spend management alone cannot pull.
The challenge is data integration. AI vendors report at the seat or tenant level. Mapping consumption to cost centres requires connecting SSO identity data, usage telemetry, HR org charts, and finance allocation rules — none of which was designed to talk to each other. That integration is what we build.
Every Usage Analytics & Chargeback engagement covers these areas — scaled to the complexity of your vendor landscape, org structure, and finance processes.
Usage Analytics & Chargeback engagements typically run six to ten weeks from kick-off to first live reporting cycle, depending on vendor count and integration complexity.
We map your AI vendor landscape, identify the data sources available per tool, review your finance and HR system architecture, and agree the chargeback model boundaries with finance stakeholders before a line of integration code is written.
Vendor API connections built, identity mapping configured, and the first round of attribution data validated against known spend figures. Discrepancies investigated and allocation logic refined until numbers reconcile to within agreed tolerance.
Allocation rules signed off by finance. Dashboards deployed. First live chargeback period run end-to-end — period-close pack produced, reviewed with finance, and distributed to business unit leads. Adjustments made before second cycle runs.
Governance model documented. Internal team trained on dashboard navigation and monthly close process. Optional ongoing managed service for data quality monitoring, new vendor onboarding, and quarterly allocation rule review.
Usage Analytics gives you the attribution layer. AI Spend Management gives you the optimisation levers. Most enterprises deploy both within the same programme.
Once you know where spend is going by department, the next question is how to reduce it. Estate discovery, contract risk review, dormant-licence harvesting, and vendor consolidation — the optimisation engine that sits alongside attribution.
Learn moreChargeback shows cost by department. Adoption measurement shows value by use case. Together they give the CFO both sides of the ROI equation — cost attributed and outcomes tracked against investment.
Learn moreMost finance teams we speak with are reconciling AI costs manually in a spreadsheet — or not reconciling them at all. The free consultation covers your current vendor landscape, the integration complexity for your specific stack, and a realistic view of what chargeback reporting would look like in your environment within eight weeks.