Gartner projects 15% IT spend rise driven by AI infrastructure and software

Global technology expenditure is set to expand significantly as artificial intelligence becomes a central driver of corporate investment, according to a new forecast from research firm Gartner. The organisation predicts that worldwide IT spending will reach $7.35 trillion in 2027, representing a 15% increase from the previous year. This growth is largely attributed to the industrialisation of AI deployment, with organisations increasingly focusing on building and monetising AI infrastructure at an unprecedented scale, rather than merely adopting software.

The surge in spending is being shaped by specific market forces that reinforce investment in AI infrastructure, AI-enabled cloud platforms and advanced software ecosystems. According to Gartner, these areas represent the most attractive opportunities in global IT spending. However, the firm also noted that hardware markets are facing growing pressure from memory-related inflation. This economic friction highlights the complex environment in which technology leaders must operate as they seek to balance rapid innovation with rising operational costs.

What we know

John-David Lovelock, a distinguished vice-president analyst at Gartner, stated that the growth of the digital economy is now determined by the ability to finance and build AI infrastructure. He made these comments at the Gartner IT Symposium/Xpo 2026 in Orlando, Florida. The analyst group also shared its annual tech predictions list, which was first published at a previous event in Australia. These predictions are distinct from Gartner’s top 10 tech trends list and focus on broader market shifts expected in 2027 and beyond.

Daryl Plummer, another distinguished vice-president analyst and Gartner Fellow, outlined additional challenges arising from this shift. He noted that AI is making application development so accessible that employees will increasingly create temporary applications for short-term business needs. This trend introduces new governance, security and compliance challenges, particularly when these applications influence decisions or access sensitive data. Organisations must therefore adapt their management strategies to handle this decentralised development model.

Furthermore, the surging electricity demand from AI and data centres is driving enterprises to invest heavily in energy generation, storage and management assets. This shift blurs the traditional line between energy consumers and power providers. As energy becomes a strategic, software-defined asset, organisations will need new capabilities to optimise production, storage and consumption. This indicates that infrastructure planning will extend beyond traditional IT hardware into broader energy management domains.

Defender's checklist

• Monitor internal development tools to identify shadow applications created by non-technical staff
• Review data access permissions for temporary applications that handle sensitive information
• Assess energy consumption metrics to understand the impact of AI workloads on power budgets
• Establish governance frameworks for short-term applications that influence business decisions

The background in plain language

Organisations are moving from experimenting with artificial intelligence to embedding it into core operations. This shift requires substantial investment in specialised hardware and software platforms. As employees gain easier access to development tools, they create their own applications, which can bypass traditional security checks. Simultaneously, the power requirements for running these systems are forcing companies to manage energy resources more actively. Teams usually need to align technical investments with broader operational capabilities, ensuring that new tools do not introduce unmanaged risks or unsustainable costs.

What to do and how to stay safe: Gartner

• Audit existing application development policies to ensure temporary tools meet security standards
• Evaluate energy usage patterns to anticipate infrastructure costs associated with AI workloads
• Implement governance controls for applications that access sensitive data or influence decisions
• Monitor hardware market trends to prepare for potential inflation in memory and server costs

Step-by-step guide: AI Governance for Small Teams: Practical Controls and Cost

General security guidance from the TechWire Beat newsroom. It is not confirmed advice from the organisations named in this story.

Frequently asked questions

How much will global IT spending grow by 2027?

Gartner forecasts that worldwide IT spending will reach $7.35 trillion in 2027, which is a 15% increase from 2026.

What are the main drivers of this spending growth?

The growth is driven by spending on AI-optimised servers, AI-optimised infrastructure as a service and AI software platforms.

What new challenges do organisations face with AI adoption?

Organisations face governance and security challenges as employees create temporary applications, and they must manage surging electricity demands.