OpenAI recently cut prices for two of its models, while the BBC recently reported that companies are struggling to set prices for their AI services.

KPMG’s Q2 Global AI Pulse revealed that as organizations are moving from experimentation toward broader deployment, they are also shifting their focus towards accountability, AI economics and value.

Managing spending, measuring value and deciding where to invest next are becoming critical issues. Here are five things you need to know:

Majid Makki

Partner and Head of Management Consulting and Technology Advisory

KPMG in Kuwait

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1. AI costs are becoming harder to predict

Many organizations are used to buying technology through fixed subscriptions or licences. AI is changing that model. Increasingly, providers charge based on usage, often measured in “tokens” that measure units of information processed by an AI model and can directly affect usage costs.

This means costs can fluctuate significantly as usage grows. A successful AI tool that employees use more frequently may also become more expensive to operate. As businesses develop AI agents and embed AI into everyday workflows, many organizations are still building the capabilities required to forecast, monitor and manage AI spending effectively.

The result is that AI economics is becoming a new management discipline, requiring organizations to monitor how AI is used and how those costs translate into business outcomes.

2. Organizations are paying attention to value, beyond just adoption

The conversation around AI is changing. Early discussions focused on experimentation and deployment. Today, leaders are increasingly asking whether AI investments are delivering measurable results.

According to KPMG’s Q2 Global AI Pulse survey, 76% of senior leaders say AI is delivering meaningful business value, while “relatively few” have reached the stage of established return on investment (ROI).

This gap highlights an important distinction. As AI investments remain substantial, boards and investors are placing greater emphasis on leaders being able to demonstrate clear financial returns.

3. Rising costs are influencing AI strategy

AI costs are no longer an afterthought. They are increasingly shaping strategic decisions about what technologies businesses adopt and how quickly they expand deployments.

KPMG’s Q2 Global AI Pulse survey found that access to lower-cost, high-performance AI models is now one of the fastest-growing influences on AI strategy. Concerns about energy use, sustainability and broader economic conditions are also becoming more important factors in decision-making.

Notably, 49% of organizations say they have delayed, paused or scaled back AI agent deployments because expected costs began to outweigh anticipated benefits. Around a quarter report narrowing deployments, while a similar proportion have delayed further rollout.

These decisions do not necessarily indicate declining confidence in AI. Instead, they suggest organizations are becoming more selective, focusing investment on use cases where business value appears strongest.

4. Most business still lack visibility into AI spending

Managing AI economics depends on understanding where money is being spent. Yet many organizations remain at an early stage in developing that capability.

Only 35% of organizations report having full visibility into their AI operating costs and actively monitoring them. The remainder rely on partial, delayed or fragmented information, making it harder to evaluate performance and make informed investment decisions.

The survey also found that many organizations have not yet implemented the controls needed to manage AI spending effectively. Just over half include cost reviews as part of AI approval processes, while only 40% use token or usage budgets. Fewer than four in 10 have architecture or prompt-design standards aimed at improving efficiency.

As AI adoption expands, visibility into usage and cost is increasingly being viewed as a core business capability rather than a technical reporting exercise.

5. Organizations with better cost visibility achieve better outcomes

One of the strongest findings from the research is the relationship between cost visibility and established return on investment. Organizations that fully understand and monitor their AI costs are significantly more likely to report established ROI.

The difference is substantial. Businesses with full visibility into AI operating costs are five times more likely to report established ROI than organizations without that visibility, with 15% reporting established ROI compared with just 3% of those lacking clear cost insight.

This does not mean visibility alone creates value. However, it gives leaders the information needed to allocate resources, manage trade-offs and identify which AI investments deserve further expansion. As AI becomes more deeply embedded across organizations, understanding the economics behind it may become a competitive advantage in its own right.

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Majid Makki

Partner and Head of Management Consulting and Technology Advisory

KPMG in Kuwait

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