Global AI spending set to hit $2.7 trillion in 2026, up 49.5 pc

Global spending on artificial intelligence (AI) is forecast to reach $2.7 trillion in 2026, a 49.5 per cent increase (year-over-year), according to a Gartner report on Wednesday.

Demand for AI infrastructure to support anticipated future workloads remains strong and inelastic to pressures from memory-related pricing increases.

“The buildout of AI data centre capacity is the largest infrastructure project humanity has even undertaken. The capacity growth from hyperscalers and service providers purchasing AI-optimized servers will continue to be the largest single area of spending,” said John-David Lovelock, Distinguished VP Analyst at Gartner.

Meanwhile, the short-term outlook for AI application development platforms has increased from 28 per cent growth in 2026 in the previous forecast to 39 per cent in this quarter’s forecast, as enterprises, software providers and services firms seek to develop custom AI applications tailored to their individual needs.

Enterprises are looking to their providers to help them manage their costs and embed usage tracking into their workflows to evaluate success.

For model providers, the pressure to offer more cost-efficient models that are aligned to enterprise use cases is opening a small but growing opportunity for domain-specific language models (DSLMs).

As a result, the 2026 growth rate for generative AI models has increased from 110 per cent growth in the previous forecast to 117 per cent growth in the current forecast, said the report.

Enterprises are turning to service providers less often to help them manage the business transformation, and more often for the smaller indirect projects to exploit AI features of their incumbent software system, said Lovelock.

The combination of transformation and indirect projects are forecast to drive a $1.2 trillion opportunity in AI services by 2030, Lovelock noted.

Global spending on artificial intelligence (AI) is forecast to reach $2.7 trillion in 2026, a 49.5 per cent increase (year-over-year), according to a Gartner report on Wednesday.

Demand for AI infrastructure to support anticipated future workloads remains strong and inelastic to pressures from memory-related pricing increases.

“The buildout of AI data centre capacity is the largest infrastructure project humanity has even undertaken. The capacity growth from hyperscalers and service providers purchasing AI-optimized servers will continue to be the largest single area of spending,” said John-David Lovelock, Distinguished VP Analyst at Gartner.

Meanwhile, the short-term outlook for AI application development platforms has increased from 28 per cent growth in 2026 in the previous forecast to 39 per cent in this quarter’s forecast, as enterprises, software providers and services firms seek to develop custom AI applications tailored to their individual needs.

Enterprises are looking to their providers to help them manage their costs and embed usage tracking into their workflows to evaluate success.

For model providers, the pressure to offer more cost-efficient models that are aligned to enterprise use cases is opening a small but growing opportunity for domain-specific language models (DSLMs).

As a result, the 2026 growth rate for generative AI models has increased from 110 per cent growth in the previous forecast to 117 per cent growth in the current forecast, said the report.

Enterprises are turning to service providers less often to help them manage the business transformation, and more often for the smaller indirect projects to exploit AI features of their incumbent software system, said Lovelock.

The combination of transformation and indirect projects are forecast to drive a $1.2 trillion opportunity in AI services by 2030, Lovelock noted.

Global spending on artificial intelligence (AI) is forecast to reach $2.7 trillion in 2026, a 49.5 per cent increase (year-over-year), according to a Gartner report on Wednesday.

Demand for AI infrastructure to support anticipated future workloads remains strong and inelastic to pressures from memory-related pricing increases.

“The buildout of AI data centre capacity is the largest infrastructure project humanity has even undertaken. The capacity growth from hyperscalers and service providers purchasing AI-optimized servers will continue to be the largest single area of spending,” said John-David Lovelock, Distinguished VP Analyst at Gartner.

Meanwhile, the short-term outlook for AI application development platforms has increased from 28 per cent growth in 2026 in the previous forecast to 39 per cent in this quarter’s forecast, as enterprises, software providers and services firms seek to develop custom AI applications tailored to their individual needs.

Enterprises are looking to their providers to help them manage their costs and embed usage tracking into their workflows to evaluate success.

For model providers, the pressure to offer more cost-efficient models that are aligned to enterprise use cases is opening a small but growing opportunity for domain-specific language models (DSLMs).

As a result, the 2026 growth rate for generative AI models has increased from 110 per cent growth in the previous forecast to 117 per cent growth in the current forecast, said the report.

Enterprises are turning to service providers less often to help them manage the business transformation, and more often for the smaller indirect projects to exploit AI features of their incumbent software system, said Lovelock.

The combination of transformation and indirect projects are forecast to drive a $1.2 trillion opportunity in AI services by 2030, Lovelock noted.

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