A company-reported signal and an illustrative calculation
Klarna reports that AI contributed to a reduction in external marketing-supplier spending. From the purchaser’s side, that is a saving. From a supplier’s side, the same change can mean less revenue. The productivity story depends on where you sit.
The assumption worth revisiting.
Consider an illustrative service priced at £100 with £60 of delivery cost: £40 contribution. A 20% reduction in that cost takes it to £48. If price also falls by 20% to £80, contribution falls to £32. This is arithmetic to explore a sensitivity, not a forecast. The question is which party can retain the value of a productivity improvement.
How much of the productivity gain could we retain after customers change what they buy and pay?
Give the capacity a purpose.
Give Finance and Revenue time to explore pricing, scope and the customer’s alternatives alongside the delivery saving. A more capable customer may need a different offer.
How this fits the capacity allocation →
Use AI to challenge your first interpretation
Stress-test this productivity business case from the buyer’s perspective. How might price, scope, demand and our responsibilities change? Treat the alternatives as hypotheses and identify the customer evidence needed.
Treat the answers as possibilities to test with people and evidence.
Go deeper into the evidence.
Klarna Group plc · Company annual filing; company-reported attribution
Klarna reports a $7m Q1 2024 reduction in external marketing-supplier spending versus Q1 2023 and attributes 37% of that decrease to AI. Named services include translation, production, CRM and social agencies. The filing also describes workforce reduction alongside AI efficiency, cost optimisation and normal-course employee attrition.
Management attribution, not an experiment. Supplier reduction is not proof every service moved in-house. The filing does not establish that every leaver went unreplaced, that there were no layoffs, or that all workforce changes were caused by AI.
podcast
Agentic AI and the future of global business services
McKinsey · McKinsey Talks Operations
A useful prompt to reconsider the boundary of shared services: which decisions and activities could move closer to internal operating knowledge?
Listen or watch for: Would moving more work inside improve the complete process, or simply move a bottleneck?
About this resource
Consultancy examples and forecasts. The episode does not establish that insourcing is always cheaper or that predicted headcount reductions will occur.