[Global] AI coding costs predicted to surpass average developer’s salary by 2028

New research suggests that AI coding costs will overtake the average developer’s salary by 2028, as a result of rising large language model (LLM) token consumption and the shift to consumption-based licensing models.

AI tokens are the units of data processed by generative AI models. Token consumption directly affects the cost of AI coding tools, particularly under consumption-based pricing models.

The cost warning came from business and technology insights company Gartner, Inc.

Nitish Tyagi - Senior Principal Analyst at Gartner - said, “Organisations are rapidly moving from experimentation to scaled deployment of AI coding agents, but many are underestimating the financial impact of rising token consumption.

“Token discipline will not emerge through developer choice alone, as developers tend to optimise for speed and convenience over cost efficiency. Without a governed engineering operating model, costs can escalate faster than the productivity gains these tools are designed to deliver.”

According to Gartner, the shift from seat-based licensing to consumption-based pricing among AI coding agent vendors is introducing highly variable cost structures for software engineering workloads. Vendors who don’t have transparency into how token consumption is calculated and billed limit enterprises’ ability to forecast and control costs accurately.

Organisations that lack clear visibility into token usage across development tasks risk budget overruns and reduced ability to track cost-to-value outcomes.

“Most organisations still lack the maturity and frameworks to effectively measure cost versus business impact,” Mr Tyagi said. “Software engineering leaders are increasingly concerned as token-driven AI spend becomes harder to justify, with budgets often being depleted earlier than expected.”

Source: Gartner

(Quotes via original reporting)

New research suggests that AI coding costs will overtake the average developer’s salary by 2028, as a result of rising large language model (LLM) token consumption and the shift to consumption-based licensing models.

AI tokens are the units of data processed by generative AI models. Token consumption directly affects the cost of AI coding tools, particularly under consumption-based pricing models.

The cost warning came from business and technology insights company Gartner, Inc.

Nitish Tyagi - Senior Principal Analyst at Gartner - said, “Organisations are rapidly moving from experimentation to scaled deployment of AI coding agents, but many are underestimating the financial impact of rising token consumption.

“Token discipline will not emerge through developer choice alone, as developers tend to optimise for speed and convenience over cost efficiency. Without a governed engineering operating model, costs can escalate faster than the productivity gains these tools are designed to deliver.”

According to Gartner, the shift from seat-based licensing to consumption-based pricing among AI coding agent vendors is introducing highly variable cost structures for software engineering workloads. Vendors who don’t have transparency into how token consumption is calculated and billed limit enterprises’ ability to forecast and control costs accurately.

Organisations that lack clear visibility into token usage across development tasks risk budget overruns and reduced ability to track cost-to-value outcomes.

“Most organisations still lack the maturity and frameworks to effectively measure cost versus business impact,” Mr Tyagi said. “Software engineering leaders are increasingly concerned as token-driven AI spend becomes harder to justify, with budgets often being depleted earlier than expected.”

Source: Gartner

(Quotes via original reporting)