Ask a boardroom in Paris or London how their AI rollout compares to a rival in Boston or Toronto, and until this week the honest answer was a shrug. Accenture has just put a number on it, and the number cuts two ways at once: Europe is closing the gap with North America faster than North America is widening it, and yet within Europe itself, a much larger gap is quietly opening between the continent’s giants and everyone else.
The consulting firm’s first AI Progress Barometer, published June 29, scores roughly 3,000 of the world’s largest companies on their readiness to scale artificial intelligence, and tracks how that readiness shifts every six months. The inaugural edition covers the six months from late 2025 through the first half of 2026, and it is less a snapshot than the start of a running scoreboard Accenture intends to update twice a year.
KEY DEVELOPMENTS
- Accenture launched its inaugural AI Progress Barometer, tracking AI readiness across roughly 3,000 of the world’s largest companies on a 0-100 scale.
- European companies improved their readiness scores by 1.6 points over six months, outpacing North America’s 1.1-point gain, though North America still leads overall at 48.9 versus 43.1.
- A sharp divide is opening inside Europe: large European firms trail North American peers by just 2.1 points, while smaller European firms lag by 7.6 points.
- Insurance, travel and consumer goods posted the fastest sector-level gains, with France, the UK and Spain leading country-level improvement.
What Happened
Accenture’s AI Progress Barometer scores companies from 0 to 100 across four pillars: strategic direction, technology foundation, people and skills, and process reinvention. European companies improved their average score by 1.6 points over the past six months, compared with a 1.1-point gain for North American companies. Despite the faster pace of improvement, North America still holds a clear overall lead, with an average score of 48.9 against Europe’s 43.1.
The more striking finding sits a layer beneath the headline regional comparison. Among the largest companies in each region, those with annual revenue above $10 billion, Europe’s largest firms now trail their North American counterparts by just 2.1 points, 47.4 versus 49.5. Among smaller companies, the gap balloons to 7.6 points, 40.5 versus 48.1. Accenture frames this as a widening “long tail” risk: Europe’s AI progress is increasingly a story about its biggest companies pulling away from its mid-sized and smaller ones, not a uniform regional advance.
The Mechanism: What the Score Actually Measures
The Two Datasets Behind the Score
The Barometer is not a survey of AI sentiment or spending intentions; it combines two existing Accenture datasets into a single comparable score. The AI Index supplies an outside-in assessment of each company’s demonstrated capability to scale AI, built from observable signals like cloud and data maturity, R&D partnerships, and AI-related hiring patterns, a methodology that sits alongside Accenture’s own earlier work with Carnegie Mellon on an AI adoption maturity model published earlier this year. The Pulse of Change survey supplies the inside-out half, a CXO-level poll Accenture runs three times a year that captures how executives themselves describe their AI investment plans, workforce reskilling, and governance posture. Blending the two is meant to catch the gap between what companies say about their AI ambitions and what their underlying technology and talent base can actually support.
The Four Pillars
Each company’s score moves along four pillars: strategic direction (AI investment plans and responsible AI focus), technology foundation (cyber, cloud and data maturity), people and skills (reskilling and workforce adaptation), and process reinvention (how far a company has gone in redesigning workflows around AI agents rather than simply layering AI onto existing processes). A company scoring well on process reinvention, in Accenture’s framing, is one where AI has changed how work actually gets done, not merely added a chatbot to an unchanged workflow.
The Backstory: A Familiar Transatlantic Gap, With a New Twist
Europe trailing the United States on enterprise AI readiness is not news; consulting firms and think tanks have documented the pattern for several years, typically attributing it to lighter venture capital flows, more fragmented digital infrastructure across EU member states, and a regulatory environment, chiefly the EU AI Act, that some executives describe as slowing experimentation even as it provides clearer rules of the road. A separate study from the Linux Foundation on Europe’s AI jobs market has documented a related strand of the same gap: European employers report deeper shortages of AI-skilled talent than their North American peers, which dovetails with the Barometer’s own “people and skills” pillar as one of the four scored dimensions. What is new in this data is the direction of travel: for the first time in this kind of cross-regional tracking, Europe’s pace of improvement is outrunning North America’s, even though the absolute gap remains wide.
The sector detail reinforces a separate, longer-running theme in Accenture’s research: process-heavy, claims-driven industries are increasingly where AI readiness gains concentrate fastest. Insurance led all 18 sectors tracked in the Barometer with an 8-point improvement to 48.6, followed by travel at plus-5.7 to 46.7 and consumer goods at plus-5.2 to 43.7. Gavin Stephenson, Accenture’s Data & AI lead for EMEA, pointed to claims automation as the clearest example: straightforward claims now move through automated damage assessment and payment, while only complex cases route to a human expert, a redesign Accenture argues is only possible once the underlying data is clean and accessible enough to trust an agent with the decision.
Reactions
Mauro Macchi, Accenture’s CEO for Europe, the Middle East, and Africa, framed the European improvement as a function of scale rather than universal momentum, crediting the continent’s largest companies with driving the gain through what he called “enter prise-wide reinvention, not just plug-and-play adoption.” That phrasing, rethinking operating models and redesigning how work gets done rather than bolting AI tools onto unchanged processes, echoes language Accenture has used elsewhere this year to describe the difference between companies experimenting with AI and companies actually capturing value from it.
Stephenson’s comments on the insurance sector’s lead carried a similar emphasis on infrastructure over enthusiasm: insurers are not simply deploying AI on top of existing processes, he said, but redesigning the processes themselves, a shift he described as only possible with a properly trained workforce and clean, integrated data underneath. The emphasis on execution gaps tracks with a separate IBM study on the AI control gap among CIOs and CTOs, which similarly found that technology leaders consistently rate their organization’s underlying AI governance and data maturity well below their stated AI ambitions, a pattern Accenture’s own four-pillar scoring system was explicitly designed to surface rather than paper over.
Why It Matters
The widening gap between large and small European companies is the detail with the longest tail of consequences. If Accenture’s reading holds, the next phase of Europe’s AI competitiveness story will not be decided primarily by its position relative to North America, but by whether its smaller and mid-sized companies, the bulk of European employment, can close a 7.6-point gap that is currently moving in the wrong direction relative to their larger domestic peers. That labor-market dimension echoes findings in PwC’s own AI Jobs Barometer, which has separately tracked how AI-exposed wage and productivity gains concentrate disproportionately at large employers. It also has direct implications for European competitiveness debates already underway around the EU AI Act and digital sovereignty, since a barometer that only tracks the continent’s largest 3,000 companies may be flattering Europe’s true position by design.
What Happens Next
Accenture has committed to updating the Barometer every six months, which means the next edition, due around the end of 2026, will be the first real test of whether Europe’s faster pace of improvement is a genuine trend or a single-period anomaly Accenture itself flagged as needing confirmation. The more consequential number to watch in that next release may not be the regional headline gap at all, but whether the long-tail divide between large and small European companies narrows or widens further, since that is the metric Accenture’s own EMEA leadership has identified as the real risk to the region’s AI competitiveness.
Sources
Accenture AI Progress Barometer, published via Business Wire and Accenture newsroom, June 29, 2026. Additional context from Accenture’s Pulse of Change CXO survey series.
One caveat worth keeping in view: the Barometer’s universe is limited to roughly the 3,000 largest companies in the world by design, meaning the regional and national averages it reports describe how the biggest enterprises in each market are faring, not the broader corporate population. That scope is precisely what makes the long-tail finding inside Europe so pointed, since even within that already-large-company sample, a 7.6-point gap separates the smaller end of the dataset from the largest. Extending the same measurement to companies below the Barometer’s size threshold would likely show a wider gap still, which is part of why Accenture’s EMEA leadership has framed the long-tail divide, rather than the transatlantic one, as the more urgent competitiveness risk for the region heading into the Barometer’s next six-month update.
