Generative AI Matures Businesses Mobilize The Race for Collaborative Advantage

Generative AI (Gen AI) is a branch of artificial intelligence that leverages advanced models to generate novel content like images, code, or text based on user input. The technology is no longer confined to experimental stages but is rapidly gaining mainstream acceptance, with businesses expanding their Gen AI implementations across various sectors. A recent report by Capgemini titled “Harnessing the value of AI: Unlocking scalable advantage” reveals that nearly six out of ten organizations anticipate AI to function as an active team member or even supervise other AI systems within the next year.

For readers of eeNews Europe, this development signifies a pivotal moment in the maturation of enterprise AI. The expectation underscores the potential benefits as well as the technical hurdles associated with scaling AI systems responsibly.

Generative AI scaling outpaces readiness

Capgemini’s study indicates a fivefold increase in enterprise adoption of generative AI over the past two years, with 30% of organizations (up from 6% in 2023) now expanding their Gen AI initiatives. In 2025, approximately 93% of companies are either exploring or implementing Gen AI capabilities. Key sectors leading the way include telecommunications, consumer products, and aerospace and defense, with applications ranging from marketing and customer service to risk management and IT operations.

Despite this rapid growth, concerns persist regarding preparedness. The report highlights that two-thirds of organizations feel the need to restructure their teams to facilitate effective collaboration between humans and AI. It also cautions that the enthusiasm for AI often surpasses the development of adequate governance and strategy.

Investments, agents, and governance challenges

The report underscores a significant financial commitment to Gen AI, with 88% of organizations boosting their AI budgets by an average of 9% in the past year. Currently, 12% of IT budgets are allocated to Gen AI, and 61% of companies plan further budget increases in the upcoming year. However, scaling AI initiatives can lead to unforeseen expenses, as more than half of enterprises have encountered unexpected spikes in cloud spending, commonly referred to as “bill shocks.” To mitigate these costs, many are turning to small language models (SLMs).

Moreover, the prevalence of AI agents, autonomous systems designed to perform specific tasks, is on the rise. The report indicates that around 90% of executives anticipate AI agents handling one or more business processes within the next three to five years, with nearly half of those scaling AI agents experimenting with multi-agent systems. Despite this trend, trust remains a significant barrier, as 71% of organizations express reservations about fully relying on autonomous AI systems for enterprise purposes, and less than half have established governance protocols.

For engineers and technologists, Capgemini’s insights emphasize the critical balance between innovation and control. As AI transitions from pilot projects to full-scale deployment, the primary challenge shifts from creating intelligent systems to establishing trustworthy ones.