With the growing demand for generative AI, the global AI model and platform market is expected to expand by more than 60% this year compared to the previous year. As corporate AI budget execution standards are reorganized around cost efficiency and performance measurement, it is analyzed that the position of vendors with usage-based management capabilities will be strengthened.

Gartner projected on the 21st that global end-user spending on AI models and platforms will reach $64 billion (approximately 95 trillion won) this year.

This represents a 63.4% increase compared to the previous year's $39 billion (approximately 58 trillion won).

By sector, spending on generative AI models is expected to surge by 117%, and spending on AI platforms is expected to increase by 36.9%.

Looking at the spending forecast by sector (unit: million dollars), the figures are as follows: Foundation Generative AI Models 11,438 in 2025 → 23,356 in 2026 (104.2%); Domain-Specific Language Models (DSLM) and Expert Generative AI Models 1,583 → 4,910 (210.0%); AI Application Development Platforms 6,885 → 9,541 (38.6%); and AI Platforms for Data Science and ML 19,405 → 26,444 (36.3%).
The total market is expected to expand from 39,311 to 64,252.

Among these, the 210% growth rate of the DSLM and professional generative AI model markets is the highest among all sectors.

Arunasree Cheparthi, a principal research analyst at Gartner, stated, “As companies rigorously review their AI budgets, they are prioritizing utilization efficiency, cost control, and measurable results,” adding, “Budgets are shifting to vendors that can demonstrate clear value across cost, latency, performance, and reliability.”

He continued, “Vendors that support the management and optimization of AI utilization by integrating evaluation, cost transparency, and usage tracking capabilities into customer workflows are"They occupy a dominant position," he said, adding, "but as spending shifts to a usage-centric model, suppliers face pressure to demonstrate actual implementation, continued utilization, and stable profitability."

Regarding the long-term outlook, analyst Cheparti stated, “As more models emerge in the market and usage-based pricing forecasts become more difficult, companies will seek platforms that support the selection of appropriate tools, performance monitoring, policy enforcement, and cost control,” adding, “Ultimately, vendors that help manage how AI is utilized across the business will benefit the most.”