Businesses are increasing spend on AI in 2025 — here’s how they’ll spend it

The rapid growth of artificial intelligence spending and investment across industries signals a transformative shift in enterprise technology strategies, with companies preparing for widespread AI adoption despite uncertain returns on investment.

Key spending forecasts: IDC projects worldwide AI technology spending will reach $337 billion in 2025 and surge to $749 billion by 2028, driven by enterprise adoption of AI capabilities across core business operations.

• Two-thirds of projected AI spending in 2025 will come from enterprises integrating AI into their core business operations
• Companies are prioritizing both quick wins through SaaS vendor solutions and long-term infrastructure investments
• The spending trajectory suggests AI investments may eventually rival traditional cloud computing expenditures

Early adopter implementations: Major organizations are already demonstrating successful AI deployments across various business functions, setting precedents for wider industry adoption.

• Marsh McLennan has deployed approximately 40 generative AI applications in production
• JP Morgan Chase has integrated AI across its investment businesses, travel services, contact centers, and credit card operations
• Dairyland Power Cooperative is using large language models for document summarization and power grid management during storms

Cloud provider dynamics: Cloud platforms are emerging as the preferred pathway for enterprise AI adoption, offering reduced risk and easier access to cutting-edge capabilities.

• Amazon Web Services, Microsoft Azure, and Google Cloud Platform are facilitating extensive AI experimentation
• Cloud providers offer flexible starting points without requiring significant upfront investments
• The relationship between AI and cloud computing is increasingly symbiotic, with each technology enhancing the other’s potential

Implementation strategies: Organizations are taking varied approaches to AI deployment, with most favoring pre-built solutions over custom development.

• 34% of organizations plan to utilize AI capabilities built into existing enterprise applications
• 53% intend to start with pretrained models and enhance them with enterprise data
• Only 13% are planning to build AI models from scratch

Governance and risk management: Companies are establishing comprehensive frameworks to manage AI deployment and mitigate potential risks.

• Organizations are forming internal AI committees and governance structures
• There is growing focus on preventing unauthorized “shadow AI” usage
• Companies are implementing security measures to protect sensitive data and ensure AI models operate within intended parameters

Future trajectory: While initial AI investments focus on foundational capabilities and infrastructure, organizations are preparing for more sophisticated applications that could fundamentally transform business models.

• Current emphasis is on automation and productivity use cases
• Higher-value applications involving new business models will require significant organizational changes
• The technology’s rapid evolution necessitates flexible architectures and regular evaluation of AI strategies

Market evolution: The enterprise AI landscape continues to mature rapidly, with companies balancing immediate opportunities against long-term strategic considerations and risk management.