AI Spending to Hit $2.7 Trillion in 2026, Up 50% Year-Over-Year

AI spending accelerates despite economic headwinds

Global spending on artificial intelligence will reach $2.7 trillion in 2026, marking a 49.5% increase from the previous year, according to new forecast data from Gartner. The research firm attributes this growth to two converging forces: massive infrastructure investment and the rapid integration of AI capabilities into existing enterprise software.

AI infrastructure—encompassing optimized cloud services, servers, network fabric, semiconductors, and devices—represents the largest spending category. John-David Lovelock, Distinguished VP Analyst at Gartner, characterized the expansion of AI data center capacity as "the largest infrastructure project humanity has even undertaken." Demand for this infrastructure remains strong despite pricing pressures in memory components, with hyperscalers and service providers continuing to purchase AI-optimized servers at unprecedented scale.

Software vendors race to embed AI features

As generative AI enters what Gartner identifies as the "Trough of Disillusionment" in 2026, enterprises are gravitating toward simpler, embedded AI features from their existing software vendors rather than pursuing standalone GenAI projects. Software companies across categories are rapidly incorporating agentic AI into their products to maintain market relevance and defend against emerging cross-functional agents.

These embedded capabilities are helping organizations improve operational efficiency, automate workflows, enhance customer engagement, and support decision-making processes. The AI software market is projected to reach $461.6 billion in 2026, up from $288.2 billion in 2025.

Services shift from transformation to implementation

The AI services market, forecast to reach $576.5 billion in 2026, is experiencing a strategic shift. Enterprises are engaging service providers less frequently for large-scale business transformation initiatives and more often for targeted projects that exploit AI features within their incumbent software systems. According to Gartner's analysis, the combination of transformation and indirect projects will create a $1.2 trillion opportunity in AI services by 2030.

Concerns about vendor lock-in, data sovereignty, and escalating costs have not significantly deterred enterprise adoption of proprietary AI capabilities, the research indicates.

Forecast adjustments reflect market evolution

Gartner revised its near-term outlook for AI application development platforms upward, now projecting 39% growth in 2026 compared to a previous 28% estimate. This adjustment reflects increased demand from enterprises, software providers, and services firms developing custom AI applications for specific use cases.

The forecast for generative AI models also increased, from 110% to 117% growth in 2026, driven by pressure on model providers to deliver more cost-efficient solutions aligned with enterprise needs. This dynamic is opening opportunities for domain-specific language models tailored to particular industries or functions.

In its updated forecast methodology, Gartner separated cross-functional agents and assistants from the broader AI software category and added consumer agents to better capture emerging market segments.

Why it matters

The scale of AI infrastructure investment—approaching $1.5 trillion in 2026 alone—signals that major technology providers are betting on sustained demand growth despite current economic uncertainties. For business leaders, the shift toward embedded AI features in existing software represents a lower-risk path to adoption than standalone GenAI projects, potentially accelerating practical AI deployment across enterprises. The forecast suggests that organizations prioritizing incremental AI integration over transformational initiatives may achieve faster returns while managing vendor and cost risks.

These projections were first reported by Gartner in a September 2026 press release accompanying its quarterly AI spending forecast.