Rising expenditure, uncertain returns
The report found that 47% of managers and senior leaders expect AI spending to rise by more than 10% over the next year. However, higher budgets do not necessarily translate into stronger financial outcomes.
Only 28% of managers and senior leaders reported strongly positive returns on their AI investments. While many organisations are using AI to improve productivity and reduce operating costs, the report suggests that converting these benefits into substantial financial gains remains difficult.
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The cost of AI tools, computing resources and software licences is one constraint. Token consumption and application programming interface (API) charges can also increase as businesses expand their use of AI applications, potentially making ongoing expenditure harder to predict.
For companies deploying AI across multiple teams and business processes, controlling these recurring expenses is becoming an important part of investment decisions.
Productivity gains need to justify spending
Businesses also face a measurement challenge. According to the report, 40% of managers and senior leaders whose departments measure AI returns use hours saved per employee as a key performance indicator. Reducing error rates is tracked by 37%, while 34% measure lower operational costs.
By contrast, only 27% track net-new revenue generated by AI-enabled products, services or features.
AI spending: Key findings
|
Indicator |
Key finding |
|---|---|
|
AI budget outlook |
87% expect AI budgets to increase over the next 12 months |
|
Higher spending |
47% expect AI budgets to rise by more than 10% |
|
Cost barriers |
34% cite the cost of tools, computing and licences as a barrier to stronger returns |
|
Strong ROI |
Only 28% report strongly positive returns on AI investments |
|
Hours saved |
40% of organisations measuring ROI track hours saved |
|
Error reduction |
37% measure reductions in error rates |
|
Operational savings |
34% track reductions in operational costs and overheads |
|
New revenue |
27% measure revenue from AI-enabled products and services |
|
Workflow transformation |
Only 20% of departments have fully transformed workflows using AI |
Source: The Adaptive Advantage: Who’s Winning with AI and How, Wharton Human-AI Research and GBK Collective, October 2026.
This emphasis on efficiency can make it difficult to determine whether AI is creating additional business value or simply helping employees complete existing tasks faster. Companies seeking stronger returns may need to assess whether productivity improvements lead to higher output, better customer satisfaction, increased sales or new revenue streams.
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From adoption to accountability
The report suggests that successful AI implementation requires more than expanding budgets or introducing new tools. Companies must integrate AI into core business processes, redesign workflows and establish clear measures of financial performance.
For business leaders, the challenge is to distinguish between spending that supports meaningful operational improvements and expenditure that produces limited measurable benefits.
As AI budgets continue to rise, cost management and return-on-investment tracking are likely to become increasingly important. The ability to demonstrate measurable gains, rather than simply report higher adoption, will determine whether growing AI expenditure can be justified over the longer term.