A new report from the Capgemini Research Institute reveals that enterprise adoption of generative AI is scaling faster than anticipated. According to the report, nearly 60% of global organizations expect AI to function not just as a tool, but as an active team member or supervisor for other AI systems within the next year. This marks a notable rise from the 44% reported earlier.
Despite the surge in adoption, many companies admit they are still not fully prepared. About two-thirds believe they must restructure internal teams to accommodate human-AI collaboration. While implementation is widespread, gaps remain in organizational readiness and governance practices.
Investment surges, but challenges grow
The third edition of Capgemini’s annual survey highlights that 30% of companies are now partially or fully scaling their GenAI initiatives—up from just 6% two years ago. Most enterprises, particularly in telecom, consumer goods, and aerospace, are applying GenAI across business functions like marketing, IT, and customer operations.
With this rapid uptake, 88% of companies have increased their GenAI investment in the past year, allocating around 12% of their IT budgets to the technology. However, over half have also reported unexpected cost spikes due to increased cloud consumption. In response, many are turning to smaller language models for better cost control.
AI agents are also gaining ground. About 90% of executives expect AI agents to take over at least one business process in areas such as product development, sales, or R&D within three to five years. Of those scaling AI agents, nearly half are already piloting or implementing multi-agent systems.
Governance remains a weak link
While optimism around AI remains high, only 46% of organizations say they have established formal governance policies for AI usage. Even fewer consistently follow them. Trust in autonomous AI agents is still limited, with 71% of organizations saying they are not ready to rely on such systems without human oversight.
The report emphasizes that enterprises must focus on responsible AI deployment by ensuring data security, regulatory compliance, and human-AI balance. Without clear frameworks, even the most advanced tools may fail to deliver meaningful value.
As the race to adopt GenAI continues, the focus is shifting from experimentation to accountability.
