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# Agentic AI Could Make Inference Costs Soar More Than 5X by 2028: Gartner
- URL: https://www.theleftshift.com/agentic-ai-could-make-inference-costs-soar-more-than-5x-by-2028-gartner/
- Published: 2026-08-24T06:46:37.000Z
- Updated: 2026-08-24T06:46:37.000Z
- Description: Gartner said product leaders can no longer assume that falling model prices will automatically translate into lower AI costs.
- Author: The Left Shift Bureau
- Tags: Agentic AI

The cost of running AI agents could rise sharply even as the price of [AI models](https://www.theleftshift.com/deepseek-releases-new-experimental-model-claims-near-parity-with-anthropics-opus-4-8/) and individual tokens continues to fall, creating a growing challenge for enterprises increasingly looking to deploy Agentic AI systems. 

Gartner [predicts](https://www.gartner.com/en/newsroom/press-releases/2026-08-17-gartner-predicts-ai-inference-costs-per-agentic-workflow-will-increase-more-than-fivefold-through-2028?ref=theleftshift.com) that AI inference costs per agentic workflow will increase more than fivefold through 2028, highlighting what it calls the “Inference Paradox” — the phenomenon where improving unit economics ultimately drives higher overall AI spending.

As AI products move beyond simple chatbots and copilots toward systems capable of executing multistep tasks, the amount of computation and tokens required for each interaction is also increasing. Gartner said product leaders can no longer assume that falling model prices will automatically translate into lower AI costs.

*“Product leaders cannot rely on more efficient token economics to rationalize AI costs. Each successive generation of AI capability will necessitate more, and often more expensive, tokens. There is no reliable, economical one-size-fits-all model on the horizon. Producing competitive AI products will require developing and maintaining complex multimodel ecosystems,” said* [*Will Sommer*](https://www.linkedin.com/in/william-sommer-b517936b/?ref=theleftshift.com)*, Gartner Sr. Director Analyst.* 

Gartner identified three trends behind the rising costs. Foundation model economics are improving rapidly, but those efficiency gains are enabling companies to deploy more powerful models. At the same time, sophisticated agentic workflows consume significantly more tokens than conventional chatbot interactions.

Gartner said routing a task to an agentic reasoning model can increase provider [inference costs](https://blogs.nvidia.com/blog/ai-inference-economics/?ref=theleftshift.com) by at least five times compared with a basic chatbot interaction, with costs rising further as task complexity increases.

AI agents must reason through problems, evaluate alternatives, question their own outputs and potentially interact with multiple systems. Each additional step increases inference requirements.

Gartner said companies seeking returns from advanced AI will therefore need to generate significantly higher value from agentic systems or adopt strategies such as inference tiering, intelligent routing and workflow orchestration.

The consultancy warned that relying on generic autonomous intelligence could result in rapidly escalating costs.

Gartner has repeatedly highlighted both the opportunity and risks surrounding AI agents. In 2025, it [predicted](https://www.gartner.com/en/newsroom/press-releases/2025-08-26-gartner-predicts-40-percent-of-enterprise-apps-will-feature-task-specific-ai-agents-by-2026-up-from-less-than-5-percent-in-2025?ref=theleftshift.com) that 40% of enterprise applications would feature task-specific AI agents by the end of 2026, up from less than 5% in 2025.

The research firm also warned that more than [40% of agentic AI projects could be canceled](https://www.theleftshift.com/over-40-of-agentic-ai-projects-will-be-abandoned-by-2027-amid-hype-and-poor-roi/) by the end of 2027 because of rising costs, unclear business value and inadequate risk controls. 

Gartner further predicted that by 2028, 33% of enterprise software applications would incorporate agentic AI, while at least 15% of day-to-day work decisions could be made autonomously.