---
id: "lib-2026-04-00-global-ai-pulse-q1-2026"
type: "library"
title: "Global AI Pulse Q1 2026"
lang: "EN"
org: "KPMG"
source_type: "Report"
date: "2026-04-01"
week: "2026-W14"
url: "https://nosov.ai/library/lib-2026-04-00-global-ai-pulse-q1-2026/"
original_url: "https://assets.kpmg.com/content/dam/kpmgsites/xx/pdf/2026/04/global-ai-pulse.pdf.coredownload.inline.pdf"
tier: "A"
tier_name: "Strong evidence"
tier_reason: "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_basis: "full-text"
original_minutes: "45"
tags: ["ai adoption", "enterprise survey", "risk"]
---

# Global AI Pulse Q1 2026

Tier 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.

## 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$186M: average 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

## 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.

Original: https://assets.kpmg.com/content/dam/kpmgsites/xx/pdf/2026/04/global-ai-pulse.pdf.coredownload.inline.pdf