Trust and human oversight critical for 450B agentic AI opportunity
Agentic AI could deliver 450B in economic value by 2028 but trust is declining. Capgemini report finds human-AI collaboration essential for scaling adoption as only 2% of organizations have fully deployed AI agents.
Paris, July 16, 2025 – A new Capgemini Research Institute report reveals agentic AI could generate $450 billion in economic value by 2028, but widespread adoption faces significant hurdles. While 93% of executives believe scaling AI agents will provide a competitive edge, only 2% of organizations have fully deployed them, and trust in autonomous AI has plummeted from 43% to 27% in the past year.
Key Findings:
- Human oversight is non-negotiable: 74% of executives say human involvement benefits outweigh costs, with 90% viewing it as positive or cost-neutral.
- Trust grows with implementation: 47% of organizations in implementation phase trust AI agents vs. 37% in exploratory phase.
- Productivity gains: Effective human-AI collaboration could increase:
- High-value task engagement by 65%
- Creativity by 53%
- Employee satisfaction by 49%
The $450B Breakdown:
Metric | Value |
---|---|
Projected economic value by 2028 | $450B |
Organizations with scaled deployment | 2% |
Executives trusting autonomous AI | 27% (down from 43%) |
Processes at semi/fully autonomous level by 2028 | 25% |
Implementation Challenges:
- 80% lack mature AI infrastructure
- Fewer than 20% are data-ready
- Top concerns:
- Data privacy (51% concerned, only 34% addressing)
- Algorithmic bias
- Lack of explainability
Franck Greverie, Capgemini's Chief Portfolio & Technology Officer, emphasized: "Realizing AI's potential requires transforming people, processes and systems with an AI-first mindset while baking in ethics from the outset."
Read the full report: Rise of agentic AI
Methodology: Survey of 1,500 executives at billion-dollar companies across 14 countries (April 2025).
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About the Author

David Chen
AI Startup Analyst
Senior analyst focusing on AI startup ecosystem with 11 years of venture capital and startup analysis experience. Former member of Sequoia Capital AI investment team, now independent analyst writing AI startup and investment analysis articles for Forbes, Harvard Business Review and other publications.