A Capgemini study reveals that nearly 60% of businesses project AI will become an active collaborator or supervisor within the next year, highlighting rapid adoption challenges in governance and trust.
Nearly six in ten enterprises forecast that artificial intelligence (AI) will evolve beyond a mere tool to become an active team member or even a supervisor of other AI systems within the next year, according to Capgemini Research Institute’s recent analysis. Their study, titled “Harnessing the Value of AI: Unlocking Scalable Advantage,” underscores how the swift ascendancy of generative AI technologies is rapidly reshaping organisational dynamics but also outstripping preparedness in governance, cost management, and workforce adaptation.
Capgemini’s research reveals a significant leap in the scaling of generative AI deployment. While only 6% of organisations had fully or partially scaled generative AI applications in 2023, that figure has now soared to one-third. Furthermore, an overwhelming 93% of the enterprises surveyed indicated they are either piloting, deploying, or enabling AI capabilities for 2025 across sectors, notably telecommunications, consumer products, and aerospace & defence. The functions most impacted by AI integration include customer operations, marketing, risk management, and IT.
Franck Greverie, Chief Technology and Portfolio Officer and group executive board member at Capgemini, cautioned that “enterprise adoption of AI is scaling faster than almost any technology we’ve seen before,” but emphasised that such rapid adoption does not guarantee substantial returns on investment. Success, he noted, hinges on establishing a robust data foundation within a trusted, secure, and privacy-compliant environment. Moreover, Greverie highlighted the critical need to develop new operating models that strike a balance between human and AI collaboration, which he terms a “balanced human-AI chemistry,” to drive meaningful business outcomes.
Despite evident enthusiasm and growing investments—88% of companies surveyed reported increasing their generative AI spending by an average of 9% in the past year—the report flags some pressing challenges. Chief among them is the phenomenon of unexpected “bill shocks” due to escalating cloud costs, which has affected over half of the surveyed organisations. This financial strain is compelling many enterprises to explore smaller, more cost-effective language models to better manage expenses.
Trust and governance remain significant hurdles in the AI adoption journey. A striking 71% of companies reported reluctance to fully depend on autonomous agents, citing concerns over reliability and decision-making transparency. In tandem, fewer than half of organisations have established comprehensive AI governance frameworks, and adherence to existing policies is inconsistent. This governance gap presents risks at a time when multi-agent AI systems become more prevalent, necessitating clear guardrails to validate decisions and ensure accountability.
Sustainability considerations are also emerging in AI deployment strategies. The research indicates that only one in five organisations currently measures the environmental impact of generative AI use. Nevertheless, adopting measures like smaller, task-specific AI models is seen as a growing approach to mitigate environmental footprints.
Human resource strategies are under scrutiny as the integration of AI goes beyond mere automation. Two-thirds of surveyed organisations acknowledge the imperative to restructure teams for enhanced human-AI collaboration, signalling a shift towards new operating models where AI plays an augmenting or supervisory role in workflows.
The benefits of generative AI adoption have already begun to materialise, with reports indicating improvements in operational efficiency, customer experience, and sales growth. On average, organisations have noted a 6.7% increase in customer engagement and satisfaction within areas where generative AI has been piloted or deployed, demonstrating palpable value alongside the challenges.
In essence, while AI’s rapid proliferation in enterprise settings highlights enormous potential, it is concurrently revealing gaps in readiness, particularly in governance, cost management, trust, and workforce integration. Capgemini’s findings suggest that for AI to transition from pilot projects to scalable, ethical, and high-value deployments, organisations must prioritise building solid data architectures, cultivate comprehensive governance mechanisms, and foster collaborative human-AI environments. Only then can enterprises truly harness the transformative power of AI as a trusted team member or supervisor, rather than merely a tool.
Source: Noah Wire Services
