Gartner: Small AI Models to Outpace LLMs 3-to-1 by 2027
STAMFORD, CT, 9th APRIL, 2025 – It is expected that in 2027, organizations will employ small models used for specific tasks nearly three times more than general-purpose large language models (LLMs), as forecasted by Gartner, Inc.
This demand is because enterprises now require performance at the levels of high accuracy, speed, and efficiency in their workflows, and such small contextualized models become cheaper in performance than that of larger models.
“The variety of tasks in business workflows and the need for greater accuracy are driving the shift towards specialized models fine-tuned on specific functions or domain data,”
Said Sumit Agarwal, VP Analyst at Gartner.
“These smaller, task-specific models provide quicker responses and use less computational power, reducing operational and maintenance costs.”
“As enterprises increasingly recognize the value of their private data and insights derived from their specialized processes, they are likely to begin monetizing their models and offering access to these resources to a broader audience, including their customers and even competitors,”
Said Agarwal.
“This marks a shift from a protective approach to a more open and collaborative use of data and knowledge.”
Organizations are now looking at such techniques as retrieval-augmented generation (RAG) and fine-tuning to build specialized models targeting their peculiar data.
As this strategic differentiator becomes enterprise data, organizations have to put a premium on the quality, structure, and management of data to support the customized use of AI.
Gartner expects a model where companies will offer their private models for commercial purposes to other enterprises and their customers or even competitors.
This corporate collaborative payoff differs from the typical proprietary perimeter approach to AI, and it opens up new revenue streams and builds a more connected ecosystem.
To prepare for this shift, Gartner recommends that businesses pilot small models in areas where LLMs underperform, consider composite model orchestration for complex tasks, and invest in upskilling teams across technical, compliance, and domain-specific roles.
Gartner believes this will be a decisive moment in AI strategy, as it claims that smaller, smarter, and more context-aware models will delineate the future of enterprise AI deployment.
More insights can be realized through Gartner’s “Predicts 2025: AI-Powered Analytics Will Revolutionize Decision Making.”
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