A new survey by consulting firm BearingPoint finds that only 13 percent of companies are progressing on schedule with their artificial intelligence (AI) initiatives. The study also shows that regulatory barriers and difficulties integrating AI with legacy IT systems continue to significantly slow broader adoption.
Main obstacles to scaling
About 40 percent of respondents identified legal and regulatory issues as the primary obstacle to scaling AI solutions, while 34 percent pointed to challenges with integrating new technologies into existing IT landscapes. Frederic Gigant, a BearingPoint expert, noted that proving value from AI and scaling solutions are two distinct tasks: success in pilot phases does not automatically translate into large-scale operational deployment.
Financial effects: cost savings more visible than revenue gains
Nearly three quarters of surveyed companies reported positive financial outcomes from AI projects, yet only about one third moved beyond pilot phases. Specifically, 24 percent of companies achieved at least a 10 percent AI-driven cost reduction, whereas only 4 percent recorded comparable revenue increases. Meanwhile, almost two-thirds of companies estimated at least a 10 percent increase in headcount within their organizations.
Geographic differences and adoption levels
The survey shows China and the United States leading in implementations: 20 percent of Chinese companies and 18 percent of American companies reported comprehensive AI deployment, compared with 8 percent in Germany. Globally, the share of companies where AI is deeply embedded in operations rose from 7 percent in 2025 to 11 percent in 2026.
Why this matters
The findings indicate that AI can deliver substantial cost savings, but regulatory compliance and integration challenges impede widespread operational use. Companies therefore face a strategic task: not only running pilots but ensuring solutions can be scaled, integrated, and meet legal requirements.
Related event
Topics from the study will be addressed at the Portfolio AI & Digital Transformation conference on November 26.
(This article was prepared with assistance from an AI assistant; the final content was edited and verified by our journalist.)
