AI Market Forecast 2026–2030: Spending, Jobs & Growth Predictions

Last updated: June 2026. Reviewed by Report AI editorial. Every figure on this page is linked to its primary source.

AI FORECASTS 2026–2030 — KEY PROJECTIONS

$1T+

AI infrastructure spend
forecast by 2029
IDC

+78M

Net AI-era jobs by 2030
170M created / 92M lost
WEF

$15.7T

Global GDP impact by 2030
cumulative AI contribution
PwC

AI infrastructure spending trajectory, Q4 2025 → 2029 (IDC) · See all comparison charts →

Every major forecaster sees AI as the defining economic story of the next five years — with infrastructure spend exceeding $1 trillion by 2029, a net 78 million jobs added by 2030, and AI contributing up to $15.7 trillion to global GDP. All figures here are projections, clearly attributed to their forecasters, with the assumptions behind them. This page collects the most important primary-sourced AI predictions for 2026–2030.

Note on forecasts: Predictions are inherently uncertain and vary widely by methodology. We label every figure on this page as a forecast/projection and link to the source so you can review the assumptions.

Executive summary

• Fast Fact: IDC forecasts AI infrastructure spending of $487B in 2026 (~53% YoY), rising past $1 trillion by 2029.
• Labor market: WEF projects +78M net new jobs by 2030 (170M created, 92M displaced) with 22% workforce churn.
• Macro impact: PwC estimates AI could contribute up to $15.7 trillion to global GDP by 2030; McKinsey puts generative AI alone at $2.6–4.4T annually across 63 use cases.
• Energy: IEA base case projects data-center electricity roughly doubling to ~945 TWh by 2030, with AI-accelerated servers growing ~30% per year.

The forecast landscape

Forecast	Figure	Source (year)
AI infrastructure spending (2026)	$487B (~53% YoY)	IDC
AI infrastructure spending (2029)	>$1 trillion	IDC
Enterprise GenAI spend (2025)	$37B (3.2× YoY)	Menlo Ventures
AI agents in enterprise apps (2028)	33% (from <1% in 2024)	Gartner
Agentic AI projects canceled (by 2027)	40%+	Gartner
Net new jobs (by 2030)	+78M (170M / 92M)	WEF
Data-center electricity (2030, base)	~945 TWh	IEA
AI contribution to global GDP (2030)	up to $15.7T	PwC
Generative AI economic value (annual)	$2.6–4.4T across 63 use cases	McKinsey
Cloud revenues (2030)	~$2T, ~10–15% GenAI	Goldman Sachs

Deep dive: why forecasts diverge

Top-line market-size estimates for AI vary widely — from Statista’s ~$1.2T total AI market in 2031 to PwC’s $15.7T economic impact by 2030 — because they measure different things. Some count software and services revenue; others include the productivity gains and consumer surplus. When comparing forecasts, the key is to match scope (revenue vs. economic impact), geography, and AI definition (all AI vs. generative AI only).

Trends to watch (2026–2030)

• Agentic AI in production. 23% of organizations are already scaling agents (McKinsey); Gartner expects 33% of enterprise apps to embed them by 2028, but also that 40%+ of agentic projects will be canceled by 2027 amid governance and ROI pressure.
• The value gap closes — unevenly. Only 39% of organizations attribute EBIT impact to AI today; the next five years will sort “AI high performers” from the rest.
• Infrastructure as bottleneck. Energy, chips, and data-center capacity are the constraints; capex is projected at $600B+ in 2026 alone.
• Regulation in force. The EU AI Act becomes fully applicable in August 2026; US federal and state AI-related rules continue to multiply.

Frequently asked questions

How big will the AI market be by 2030?

Estimates vary by definition. IDC sees AI infrastructure spending alone exceeding $1 trillion by 2029. PwC estimates AI’s economic impact on global GDP at up to $15.7 trillion by 2030. McKinsey puts generative AI’s annual value at $2.6–4.4 trillion across 63 use cases.

Will AI create or destroy more jobs?

The WEF projects a net positive: 170 million new roles versus 92 million displaced by 2030 (+78M), with 22% workforce churn.

How much energy will AI use by 2030?

The IEA’s base case projects global data-center electricity at ~945 TWh by 2030 (just under 3% of global power), with AI-accelerated servers growing about 30% per year.

Data sources & methodology

1. IDC — AI Infrastructure Spending forecast, 2026.
   Verified data points: $487B AI infrastructure spend forecast (2026, ~53% YoY); >$1T by 2029 (~31% CAGR).
   Source: idc.com
2. Gartner — agentic AI forecasts, June 2025.
   Verified data points: 33% of enterprise apps embedding agentic AI by 2028 (from <1% in 2024); 40%+ of agentic projects canceled by end of 2027.
   Source: gartner.com
3. World Economic Forum — Future of Jobs Report 2025.
   Verified data points: +78M net jobs by 2030; 22% workforce churn; 39% of skills change.
   Source: weforum.org
4. IEA — Energy and AI, 2025.
   Verified data points: data-center electricity ~945 TWh by 2030 (base case); AI-server growth ~30%/yr.
   Source: iea.org/reports/energy-and-ai
5. PwC — Sizing the Prize AI macro forecast.
   Verified data points: up to $15.7T AI contribution to global GDP by 2030.
   Source: pwc.com
6. McKinsey — The Economic Potential of Generative AI.
   Verified data points: $2.6–4.4T annual generative-AI value across 63 use cases.
   Source: mckinsey.com
7. Goldman Sachs — AI infrastructure capex outlook 2026.
   Verified data points: hyperscaler capex projected $600B+ in 2026; cloud revenues ~$2T by 2030 with ~10–15% GenAI.
   Source: goldmansachs.com
8. Menlo Ventures — 2025: The State of Generative AI in the Enterprise.
   Verified data points: $37B enterprise GenAI spend in 2025 (3.2× YoY).
   Source: menlovc.com

Related pages: AI Investment & Funding Statistics 2026 · AI & Jobs Statistics 2026 · AI Infrastructure & Compute Statistics 2026