Asger Risom
Europe is stuck between economic headwinds and a technological opening.
Europe is stuck between economic headwinds and a technological opening. Productivity remains sluggish, energy shocks linger, and demographics keep tightening. Yet artificial intelligence is advancing quickly enough to offer the continent a rare chance to pull ahead.
In an opinion column for Fortune, Dave McCann, managing partner at IBM Consulting for EMEA, argues that Europe can restore competitiveness not by winning model races, but by embedding AI deeply across its strongest industrial sectors.
Building Competitive Momentum
McCann points to rising adoption across European enterprises. In an IBM survey, 66% of senior executives reported measurable productivity gains from AI, and 41% expect a return on investment within a year.
He highlights examples already reshaping operations: a logistics provider using AI agents to forecast demand and redirect shipments automatically, and a pharmaceutical company speeding literature reviews and molecule screening from months to hours.
These cases, McCann argues, show how targeted AI can lift both efficiency and innovation — but he notes that Europe must scale adoption faster than its competitors abroad.
Europe’s Data Advantage
A central element of McCann’s argument is Europe’s reservoir of enterprise data. Only a small fraction of global proprietary data has been infused into AI systems so far.
He cites L’Oréal’s 16 terabytes of formulation data used to train models that speed development of new cosmetics. Similar archives exist across Germany’s manufacturers, Italy’s automakers, and Northern Europe’s life sciences firms.
High regulatory standards around data integrity, McCann writes, could become a differentiator for “Made in Europe” AI, boosting trust among customers and governments.
Coordinating AI at Scale
McCann also stresses the need for unified AI operations. Research he cites suggests centralized programs can deliver up to 34% higher ROI.
France’s Elior Group, building a “data and AI factory” to consolidate digital innovation, is offered as an example of coordination enabling faster deployment.
A Missing Piece: Workforce Fallout
But rapid adoption has also fueled difficult questions across Europe. Waves of AI-linked restructuring — from media and retail to software and gaming — have raised concerns about whether productivity gains come alongside job losses. Critics argue that any “industrial renewal” must consider labor protections, training access, and the uneven burden of automation on mid-skill roles.
McCann contends that AI works best when enhancing, not replacing, human work. He points to IBM’s own use of more than 3,000 AI assistants, which he says have boosted productivity by up to 50% on some tasks. Still, the wider European debate remains unsettled.
A Strategic Window
Despite the tension between opportunity and disruption, McCann maintains that Europe’s industrial depth and regulatory rigor can help it compete if leaders invest now — in data foundations, coordinated AI operations, and workforce literacy.
Those choices, he argues, will determine whether AI becomes a catalyst for renewal or a source of further inequality.
