TLDR: A recent Capgemini Research Institute report, ‘Rise of agentic AI,’ indicates that a significant majority of organizations anticipate AI systems will evolve beyond mere tools to become active teammates or even supervisors to other AI systems by mid-2026. This shift is expected to drive substantial economic value, with projections of up to $450 billion by 2028, despite current challenges in trust, knowledge, and technological readiness.
A groundbreaking report from the Capgemini Research Institute, titled ‘Rise of agentic AI,’ highlights a transformative shift in how organizations perceive and integrate artificial intelligence. The study reveals that by mid-2026, six out of ten firms expect AI systems to operate as active teammates or even supervisors to other AI systems, marking a new era in enterprise productivity and human-AI collaboration.
The report, based on a global survey of 1,500 executives across 14 countries in April 2025, projects that AI agents could generate up to $450 billion in economic value through revenue uplift and cost savings by 2028. This includes benefits from semi- to fully autonomous AI agents (Level 3 or higher autonomy). ‘Competitive momentum is clearly building: 93% of leaders believe that those who successfully scale AI agents in the next 12 months will gain an edge over industry peers,’ the report states.
Currently, 14% of organizations have already implemented AI agents at partial or full scale, with another 23% running pilot programs. A further 61% are either preparing for or exploring deployment. This rapid adoption mirrors the trajectory seen with generative AI, which surged from 6% at-scale deployments in 2023 to 24% in 2024.
However, the journey towards widespread autonomous AI is not without its hurdles. The report indicates a decline in trust in fully autonomous AI agents, dropping from 43% 12 months ago to just 27% today. This erosion of trust is attributed to business realities setting in after initial enthusiasm, coupled with prevalent ethical concerns such as data privacy, algorithmic bias, and the ‘AI black box’ effect. ‘Trust is a major hurdle. Businesses need confidence in AI systems before granting them any level of autonomy,’ notes Dr. Walter Sun, SVP, Global Head of AI at SAP.
Furthermore, half of the surveyed organizations admit to insufficient knowledge of AI agent capabilities, and fewer than one in five report high levels of data-readiness. Over 80% lack mature AI infrastructure, significantly limiting their ability to scale agentic systems effectively. Franck Greverie, Chief Technology and Portfolio Officer at Capgemini, emphasizes, ‘If your data isn’t ready for AI, your business isn’t ready for AI.’
Despite these challenges, the vision for human-AI collaboration is strong. In one to three years, AI agents are expected to evolve into members within human-supervised teams. Nearly three-quarters of executives believe that the benefits of adding human oversight to AI agent-driven tasks will outweigh the costs, leading to outcomes such as 65% greater engagement in high-value tasks, 53% increased creativity, and 49% greater employee satisfaction. ‘Organizations that treat AI agents only as a productivity tool are missing the point. Those that don’t redefine roles, incentives, team structures, and leadership models may soon find themselves irrelevant,’ warns Marjolein Wenderich, Vice President, Global MD – Workforce and Organization at Capgemini.
Key functions expected to see the most extensive adoption of AI agents in the near term include customer service, IT, and sales, expanding into operations, R&D, and marketing over the next three years. ‘The fastest wins are in functions where processes are well-defined and outcomes are known and measurable, like customer service and sales,’ explains Dr. Suraj Srinivasan, Philip J. Stomberg Professor of Business Administration at Harvard Business School.
To fully harness the potential of AI agents, Capgemini advises organizations to:
Redesign processes with AI at their core, moving beyond incremental automation.
Transform the workforce and organizational structure, viewing AI agents as team members and redefining human roles.
Strike the right balance between agent autonomy and human involvement, categorizing decisions by risk and defining ‘autonomy boundaries.’
Strengthen data and technological foundations, including robust data governance and scalable infrastructure.
Ensure AI agents operate within defined scopes, remaining traceable and explainable to build trust.
Develop and integrate ethical AI principles, embedding ethical reasoning into design and establishing layered governance.
Also Read:
- Agentic AI Market Poised for Explosive Growth, Projected to Exceed $100 Billion by Early 2030s
- Google Cloud Report: Over Half of Executives Deploy AI Agents, Driving Significant Business Value
The report concludes that the future of enterprise operations lies in the seamless integration of AI agents working together with humans, under their control, to drive unprecedented levels of productivity, efficiency, and innovation.
