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Legal departments that are getting the most productivity out of their AI tools may be the ones hit hardest by rising costs, as vendors move away from predictable per-user subscriptions toward consumption-based pricing models, according to research firm, Gartner.
Gartner is predicting that by 2028, consumption-based pricing will account for more than 35 per cent of net new corporate legal technology spend with major vendors, a shift that could catch unprepared general counsel off guard.
The pricing shift
The move represents a fundamental change from the flat-rate licensing models that legal departments have relied on to manage technology budgets. Under the emerging hybrid models, traditional licensing fees are combined with usage-based charges tied to how much AI computing power is consumed.
Senior Director Analyst in the Gartner Legal and Compliance Practice, Shannon Nakamoto, explained the pressure driving the change.
“As legal AI adoption grows, tools consume ever more computing power, putting vendors under increasing pressure to align pricing more closely with usage,” Nakamoto noted.
Success creates its own cost problem
The shift creates a paradox for legal departments: those achieving the greatest productivity gains from AI assistants and agents are likely to face the largest spending increases if consumption is not actively governed.
Legal departments have traditionally viewed technology spending through the lens of predictable user licensing costs. Linking costs to actual usage changes that equation entirely.
“The goal shouldn’t be to minimise AI spending,” Nakamoto commented. “It’s more important to ensure that AI spending is well-aligned to measurable business value.”
Traditional procurement methods falling short
Gartner warns that traditional software procurement methodologies will likely prove insufficient for evaluating AI-enabled legal technology. As vendors adopt combinations of subscriptions, credits, consumption allowances and overage charges, legal departments will need greater visibility into how costs are incurred and what activities drive spending.
“Pricing transparency should be a critical buying criterion for GC,” Nakamoto observed. “It’s essential to understand how AI consumption is measured, what drives costs and how spending will change as adoption grows.”
Managing by use case rather than tool
Different legal AI use cases can have dramatically different consumption patterns, costs and governance requirements. Contract summarisation, for example, may have a very different cost profile from autonomous diligence, investigations or negotiation workflows.
Gartner recommends implementing use-case-level approval thresholds and routing policies to ensure high-cost, advanced reasoning models are reserved for high-value legal tasks.
“GCs should stop asking, ‘How much AI are we using?’ and start asking, ‘Which legal outcomes justify the AI consumption required to achieve them?'” Nakamoto advised. “Doing that requires a solid understanding of how specific use cases drive AI spending.”
Last Updated on September 4, 2026 by Nick Ross
