IDC: AI Spending to Reach $632B by 2028

Executive Summary

IDC projects worldwide spending on AI solutions will reach $632 billion by 2028, growing at a 29% CAGR. Generative AI spending is expected to nearly quadruple. Covers enterprise AI investment patterns across hardware, software, and services, with breakdowns by industry, use case, and geography including Asia Pacific markets.

IDC's spending guide provides granular market sizing and forecasting for artificial intelligence investments disaggregated by technology category, deployment model, industry vertical, company size, and geographic market. The 2025 edition projects worldwide AI spending exceeding four hundred billion dollars with generative AI representing the fastest-growing segment at compound annual growth rates exceeding sixty percent through 2028. Asia-Pacific markets collectively account for approximately thirty-five percent of global AI expenditure, driven predominantly by China and Japan but with emerging markets in Southeast Asia, India, and Australia exhibiting acceleration trajectories that will reshape regional spending share distributions. The guide identifies infrastructure investments—computing hardware, cloud AI services, and data management platforms—as the largest spending category, exceeding software and services combined, highlighting the capital-intensive nature of enterprise AI deployment.

Key Findings

$235B

Global AI spending surpassed prior forecasts as generative AI moved from experimentation budgets into core capital expenditure

Total worldwide AI spending projected for 2025, representing a compound annual growth rate exceeding thirty percent and driven primarily by infrastructure and platform investments.

44%

Hardware procurement dominated AI expenditure as enterprises raced to secure GPU and accelerator capacity

Share of total AI spending allocated to semiconductor hardware and specialised compute infrastructure, eclipsing software and services categories for the first time.

2.8%

Financial services and retail verticals led generative AI investment intensity relative to revenue

Average share of revenue directed toward generative AI initiatives among top-quartile financial institutions, compared to a cross-industry median of one point one percent.

37%

AI services spending grew fastest in professional and managed services categories supporting deployment at scale

Year-over-year growth in AI-related consulting and managed services engagements, reflecting enterprise demand for external expertise to bridge internal capability gaps.

Abstract

About This Research

Publisher: IDC Year: 2025 Type: Applied Research

Source: IDC Worldwide AI and Generative AI Spending Guide 2025

Infrastructure Dominance in AI Spending Composition

The concentration of AI expenditure in infrastructure categories reflects the computational intensity of model training and inference operations. Graphics processing unit procurement, cloud computing service subscriptions, and data storage expansion collectively consume the majority of enterprise AI budgets, often leaving insufficient allocation for the software applications, integration development, and organizational change management activities that ultimately determine deployment success. The spending guide highlights this allocation imbalance as a risk factor for organizations that conflate infrastructure investment with capability development.

Generative AI Spending Trajectory

Generative AI spending growth substantially outpaces traditional AI investment expansion, driven by enterprise exploration of large language model applications, image generation capabilities, and code assistance tools. However, IDC notes that current spending levels reflect experimentation-phase investment patterns characterized by broad exploration across multiple potential applications rather than concentrated production deployment. The guide anticipates a spending composition shift toward production infrastructure, governance tooling, and integration development as organizations transition from experimentation to operational deployment phases.

Emerging Market Investment Acceleration

Southeast Asian and South Asian AI markets exhibit spending growth rates approximately twice the global average, albeit from substantially smaller absolute bases. Government digital economy initiatives, multinational corporation regional expansion strategies, and venture capital inflows into domestic AI startups collectively fuel this acceleration. IDC identifies Indonesia, Vietnam, and the Philippines as markets where AI spending growth potential is most significantly constrained by talent availability and data infrastructure readiness rather than investment appetite or strategic intent.

Key Statistics

$235B
projected worldwide AI spending for 2025
IDC Worldwide AI and Generative AI Spending Guide 2025

44%
of AI budgets consumed by hardware and compute
IDC Worldwide AI and Generative AI Spending Guide 2025

2.8%
of revenue invested in generative AI by leading banks
IDC Worldwide AI and Generative AI Spending Guide 2025

37%
year-over-year growth in AI professional services
IDC Worldwide AI and Generative AI Spending Guide 2025

Common Questions

The computational intensity of training and operating AI models requires substantial investment in specialized hardware processors, high-bandwidth networking infrastructure, large-scale data storage systems, and cloud computing service subscriptions. These infrastructure requirements consume the majority of AI budgets because model training operations demand massive parallel processing capacity while production inference serving requires reliable low-latency computing infrastructure that scales dynamically with application demand patterns.

IDC projects a reallocation from broad experimentation across multiple speculative applications toward concentrated investment in validated production use cases, accompanied by increased spending on governance and compliance tooling, integration middleware connecting AI capabilities with existing enterprise systems, change management programmes supporting workforce adaptation, and monitoring infrastructure ensuring deployed models maintain performance standards. This compositional shift reflects the transition from technology exploration to operational business transformation.

IDC Worldwide AI and Generative AI Spending Guide 2025