Global spending on artificial intelligence (AI) is projected to catapult to $2.7 trillion in 2026, a staggering 49.5% year-over-year increase, according to a new report released by business and technology insights firm Gartner Inc.
Driving the surge is massive investments in infrastructure. Hyperscalers and technology service providers are pouring capital into AI-optimized servers, semiconductors, network fabrics, and Infrastructure-as-a-Service (IaaS) to meet the demand for future workloads.
“The buildout of AI data center capacity is the largest infrastructure project humanity has ever undertaken,” said John-David Lovelock, Distinguished VP Analyst at Gartner. Lovelock noted that demand for AI infrastructure remains strong and largely inelastic, even amidst pricing pressures from memory components.
As Generative AI (GenAI) enters what Gartner terms the “Trough of Disillusionment” in 2026, corporate buying habits are shifting.
Rather than building sweeping custom models from scratch, enterprises are leaning heavily on embedded agentic AI within their existing software platforms to boost operational efficiency, automate workflows, and enhance decision-making.
Software vendors are aggressively adding these autonomous agent capabilities to maintain market relevance and counter competition from emerging cross-functional tools. Concerns over data sovereignty, potential vendor lock-in, and unpredictable costs have done little to slow adoption.
Consequently, enterprise reliance on external service providers has pivoted toward smaller, indirect integration projects. Gartner estimates that this trend will fuel a $1.2 trillion AI services opportunity by 2030.
“The increase in 2026 AI spending tracks how much capacity is being built,” said Mitch Ashley, vice president and practice lead for Software Lifecycle Engineering and AI-Native Software Engineering at The Futurum Group. “What enterprises get for it is a different question. More than half of the $2.7 trillion is infrastructure, and tech providers account for 35% of the spend, buying ahead of workloads that have not arrived.”
“For CIOs, much of the rest is a price increase on software they already own,” Ashley said. “Watch which enterprises reorganize around verification, integration, and governance, because that is where the spend converts.”
Gartner also revised its near-term growth projections upward across key sectors.
AI application development platforms are expected to grow by 39% in 2026, up from a previous forecast of 28%, as organizations seek tailored applications with built-in cost-tracking features.
Generative AI models, meanwhile, are forecast to grow 117%, buoyed by market demand for cost-efficient, domain-specific language models (DSLMs).
Looking further ahead, Gartner modified its long-term reporting structure by separating cross-functional agents and assistants from traditional software, while incorporating consumer-focused AI agents to capture emerging market dynamics.
