Global AI Performance Study: Germany's AI Readiness Ahead of the U.S., Behind China

Globally, 74 percent of AI-driven value creation comes from just 20 percent of companies. This is shown by PwC’s global AI Performance Study, for which 1,217 executives across 25 industries were surveyed. The PwC AI Fitness Index, developed for the study, evaluates a total of 60 management and investment practices in the areas of AI fundamentals and AI usage on a scale of 1 to 10. Germany scored 5.6 points—slightly above the global median (5.5) and ahead of the U.S. (5.2), the U.K. (5.5), and Japan (4.8). China leads the way with a score of 6.9, closely followed by Hong Kong (6.7) and Saudi Arabia (6.2). The international AI leaders—the top 20 percent of surveyed companies with the highest AI-driven performance—achieve a score of 6.8.

Germany’s position is better than is often assumed. The gap between Germany and the leaders lies not in the fundamentals, but in the application of AI: Only 25 percent of the German executives surveyed are using AI to drive revenue growth. Among AI leaders, the figure is 31 percent. Instead, 52 percent of German respondents use AI primarily to improve efficiency—four percentage points above the global average.

Usage Lags Behind the Fundamentals

In terms of AI fundamentals, Germany scores 5.8 points, which is above the global median (5.4) but still 1.1 points behind the AI leaders. The strongest individual area is governance and risk management, with a score of 6.3 compared to the AI leaders’ score of 7.0. Here, systematic data management, high security standards, and regulatory maturity prove to be competitive advantages.

There is a significant gap in AI adoption—that is, the level of maturity at which AI is integrated into core processes, recurring decisions, and scalable solutions. Germans score 5.4 points in this area, trailing the AI leaders (7.1) by 1.7 points. The study does not measure the number of tools, but rather whether AI is noticeably permeating workflows and improving decision-making.

„Germany's AI capabilities are internationally competitive,
especially because of the solid groundwork that has been laid. Now it's time to,
”to translate this foundation into AI-driven revenue growth."

Nico Reichen,
Lead Data and AI,
PwC Germany

What AI Leaders Do Differently

AI leaders achieve 7.2 times higher AI-driven performance than the remaining 80 percent—measured in terms of AI-driven revenue, as well as efficiency and cost savings relative to the respective industry median. The global study shows that the strongest single factor driving this outperformance is not efficiency, but rather the ability to leverage AI to capitalize on growth opportunities across industry boundaries. While 59 percent of AI leaders report having fundamentally transformed their business model with the help of AI, the figure in Germany is only 21 percent—even slightly below the global average (23 percent). The gap is similarly wide when it comes to the development of new products and services (25 percent vs. 62 percent). The potential of this type of reinvention is particularly evident at the intersections between industries: Here, AI leaders outperform the German average by a factor of 1.54 (4.6 vs. AI leaders: 7.1).

From Pilot to Scaling

What matters is not the number of AI projects, but their depth. According to the global study, AI leaders are 1.8 times more likely than German companies to use AI to perform multiple tasks within defined parameters. Autonomous, self-optimizing systems are used 1.7 times more frequently by the top performers. At the same time, these pioneers ensure this automation through stronger governance: Compared to German companies, AI leaders are 1.4 times more likely to have a documented Responsible AI framework and 1.5 times more likely to have a cross-functional AI governance board. The result: Their employees trust AI outcomes more than twice as often (60 percent vs. 27 percent)—a prerequisite for ensuring that AI-supported decisions are actually adopted within the organization.

For Germany, this presents a concrete opportunity: Regulatory maturity and strong governance are precisely the foundations that AI leaders use to scale automation safely. (Source: PwC)