### AI Cost Management Moves Into Focus

AI token costs are falling, but enterprise AI spending is still rising. In this Techstrong AI Leadership Insights conversation, Mike Vizard talks with Jon Knisley, Director of AI Value Management at ABBYY, about why lower token prices do not always translate into lower operating costs.

The issue is not just the price of a single model call. It is the larger system around AI. Agents, workflows, tools, integrations and repeated reasoning steps can consume far more tokens than a simple chatbot response. That changes the way teams need to measure value.

### AI Agents Change the Cost Equation

Knisley explains that AI agents can create a version of Jevons Paradox for enterprise technology teams. As each unit of AI becomes cheaper, organizations often use more of it. That can drive total spending higher, even when the cost per token keeps dropping.

This makes AI cost management more important for leaders who are trying to move beyond experiments. Teams need to understand when an AI agent is useful, when a simpler model is enough and when automation adds too much complexity. The goal is not to avoid AI. The goal is to apply it where the return is clear.

### Workflow Value Matters More Than Model Choice

The conversation also explores why many AI projects struggle to show business value. Knisley points to workflow design as a major factor. A powerful model may not improve outcomes if the process, data and measurement strategy are weak.

One example involved contract lease extraction. The organization needed hundreds of data points from thousands of complex documents. Accuracy problems were not solved by simply sending the work to a large language model. Better structure, process understanding and domain-specific design mattered more.

### Practical Takeaways for Enterprise AI Leaders

For technology leaders, the message is direct. AI token costs should be tracked, but they are only one part of the bigger picture. Teams should also measure utilization, accuracy, workflow impact and the cost of missed business opportunities.

AI cost management can help organizations decide where agents make sense and where lighter automation will do the job. As AI becomes part of everyday operations, the winners will be the teams that connect technical choices to measurable value.