Global AI Spending to Reach $297 billion by 2027 — Read Full Report
According to a recent report by Gartner, the global spending on AI software is expected to increase from US$124 billion in 2022 to US$297 billion by 2027, at a compound annual growth rate (CAGR) of 19.1%. This is because of the burgeoning rise in spending on generative AI software, expected to climb from 8% in 2023 to 35% in 2027.
This growth is driven by the integration of AI tools into enterprise software, facilitating widespread adoption of generative AI-based features and applications.
Key assumptions driving the AI market boom include the prediction that over 70% of independent software vendors (ISVs) will embed generative AI capabilities in their enterprise applications by 2026, a substantial increase from the current less than 1%.
By 2025, Gartner predicts that 39% of organizations will be in the experimentation phase of AI adoption, with 14% in the expansion phase. Additionally, by 2027, 36% of organizations in the experimentation phase are expected to adopt high-value, low-time-to-financial-impact use cases.
Gartner identifies key areas for AI tool integration, emphasizing marketing, product design, and customer service, reflecting a shift towards personalized and efficient operations. The forecast is based on an analysis of over 500 AI use cases.
The fastest-growing application areas for AI spending, according to Gartner, include financial management system (FMS) components and digital commerce applications. FMS vendors are leveraging AI to enhance forecasting, planning, and productivity, while digital commerce applications focus on streamlining operations through personalization and automation.
The survey further predicts generative AI will become a cornerstone of AI software spending, reaching 35% of worldwide revenues by 2027. The proliferation of AI copilots integrated into various enterprise systems is identified as a key driver for generative AI's growth, with Microsoft's Dynamics 365 Copilot cited as a successful example.
It also highlights the significance of large language models (LLMs) in the AI platform market's growth, particularly in the data science and AI platform. This market encompasses machine learning platforms and cloud AI developer services and is driven by the growth of AI and the democratization of technology.
LLMs, including natural language technologies, are identified as essential components fueling the growth of AI software platforms for the next three years.