Global AI Pulse Q1 2026
A · Strong evidence A large, documented executive survey (2,110 senior leaders, 20 countries) from a Big Four firm, with a stated method but self-reported outcomes and a consultancy interest in the operating-model conclusion.
Summary based on the full text·Original: about 45 minutes to read
In short
The first edition of KPMG International's quarterly Global AI Pulse (April 2026), based on an online survey of 2,110 C-suite and senior leaders in companies with revenue of at least US$100M. Its main finding is a gap between adoption and measured value: 95% have an AI strategy, 64% say AI delivers meaningful business value, but only 8% report established return on investment. KPMG labels about 11% of respondents "AI leaders" and argues the difference lies in operating model, governance and workforce readiness rather than spend or tools.
Key numbers
- 95% vs 8%organizations with an AI strategy vs organizations reporting established AI ROI
- US$186Maverage planned AI investment over the next 12 months (weighted mean)
- 77% vs 20%meaningful business outcomes reported by organizations confident vs not confident in their talent pipeline
- 9%organizations orchestrating multiple AI agents across workflows
As reported by the source.
English·PDF·opens assets.kpmg.com
What it reports
- Maturity split: 54% are in early stages (research 11%, experimentation 22%, strategic planning 21%), 39% are scaling or driving adoption, 8% have established ROI.
- Planned AI investment averages US$186M over 12 months; ASPAC US$245M, Americas US$178M, EMEA US$157M.
- Agent engagement: 22% exploring, 17% piloting, 14% deploying, 18% scaling across functions, 17% developing multi-agent systems, 9% orchestrating agents across workflows.
- Functions with agentic AI deployed (n=1,588): technology/IT 66%, operations 55%.
- Leaders vs non-leaders reporting meaningful value: 82% vs 62%. Leaders prioritise revenue growth (33% vs 28%); non-leaders prioritise cost reduction (32% vs 25%).
- Confidence in measuring revenue impact: 48% of leaders vs 27% of non-leaders "very confident"; profitability 50% vs 28%.
- Barriers: data privacy and cybersecurity 42%, data quality 34%, regulatory uncertainty 31%.
- Enterprise-scale deployment by region: Americas 35%, ASPAC 23%, EMEA 22%. Eight in ten expect human-level reasoning AI within five years.
How they got it
Online survey fielded 19 February to 17 March 2026 across 20 countries and 20+ sectors (EMEA 45%, Americas 27%, ASPAC 28%). Respondents were C-suite leaders and their direct reports. "AI leaders" are defined as organizations in the top two maturity stages and the top three agent-deployment categories. Investment averages are weighted by organization size and region.
Limits
- All outcomes are self-reported; "meaningful business value" and "established ROI" are not defined in financial terms.
- The leader definition already includes advanced agent deployment, so the finding that leaders deploy more agents is partly built into the segmentation.
- KPMG sells AI transformation and governance services, the same remedies the report recommends.
Why it matters for companies
The 64% vs 8% gap suggests most firms believe AI is useful but cannot yet prove it in their accounts. The measurement data is the practical takeaway: firms that track revenue, profitability and decision quality with confidence are the ones that report scale. Talent readiness shows the largest single association with reported outcomes. For a traditional company, building a measurement baseline before scaling agents is cheaper than retrofitting one later.
Summary based on the full text. Read the original for the full argument and data.Open PDF on assets.kpmg.com
- Tags
- AI adoption, Risk