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As legal AI vendors transition to consumption-based pricing, unprepared legal departments risk facing unexpected budget surprises.
New research from technology insights company Gartner has found that general counsel are navigating a major transition from predictable, per-user software subscriptions to hybrid pricing structures, which blend standard licensing fees with usage-based costs linked to AI consumption.
Highlighting the growing importance of usage-based pricing models, Shannon Nakamoto, senior director analyst of research at Gartner legal and compliance practice, noted the shift in vendor strategies.
“As legal AI adoption grows, tools consume ever more computing power, putting vendors under increasing pressure to align pricing more closely with usage,” Nakamoto said.
“Therefore, Gartner is predicting that by 2028, consumption-based pricing will account for over 35 per cent of net new corporate legal technology spend with major vendors.”
This comes as arguments have surfaced that while lawyers remain responsible for verifying AI-generated legal work, legal AI vendors should share that burden by designing transparent tools that make sources, search scope, gaps, contradictions, and verification easy to inspect.
Historically, corporate legal teams have evaluated software expenditure using predictable, fixed per-user license models.
Gartner warned that tying expenses directly to usage fundamentally reshapes this dynamic, noting that in-house legal divisions deriving the highest productivity from AI tools could face sharp cost increases if they are carefully monitored.
As such, lawyers have put forward solutions in which firms should absorb AI costs as overhead rather than separately billing clients, using AI-driven efficiency to shift from hourly billing towards value-based, fixed-fee, and hybrid pricing models to balance pricing certainty with the unpredictable nature of legal matters.
“The goal shouldn’t be to minimise AI spending,” Nakamoto said.
“It’s more important to ensure that AI spending is well-aligned to measurable business value.”
Nakamoto highlighted that traditional software procurement methodologies will likely prove to be inadequate for evaluating AI-enabled legal technology, with legal departments requiring clearer visibility into vendor costs and spending drivers.
“Pricing transparency should be a critical buying criterion for general counsel,” Nakamoto said.
“It’s essential to understand how AI consumption is measured, what drives costs, and how spending will change as adoption grows.”
The evolution of AI for in-house legal teams is palpable, with the technology becoming a necessity for in-house teams, improving speed and efficiency, while allowing lawyers to focus on the more complex matters of the legal profession.
Different legal AI usages can have extremely different operational patterns, costs, and governance requirements.
For example, contract summarisation may typically be cheaper and have a drastically different expense pattern than autonomous diligence, investigations, or negotiation workflows.
Nakamoto recommended that general counsel should reframe how they analyse the cost and value distribution of AI usage.
“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 said.
