Agentic AI is one of the fastest-emerging technologies in business, with the potential to generate $450 billion in economic value through revenue uplift and cost savings across surveyed countries by 2028, according to the Rise of agentic AI: How trust is the key to human-AI collaboration. The new report from Capgemini Research Institute reveals insights from a survey of 1,500 senior executives across 14 countries on the emergence of AI agents as a transformative force in business.
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Key findings from the Capgemini report
- A $450 billion opportunity: By 2028, AI agents could generate up to $450 billion in economic value through revenue growth and cost savings across surveyed markets.
- Adoption is accelerating, but maturity remains low: Only 2% of organizations have deployed AI agents at scale, 12% at partial scale, 23% have launched pilots, and 61% are exploring deployment. Fifteen percent of business processes are expected to reach semi- or full autonomy in the next 12 months. However, fewer than one in five organizations report high maturity with respect to the data and technology infrastructure needed to implement agentic AI.
- Trust in fully autonomous AI agents is declining: It dropped from 43% to 27% in one year. Ethical concerns, lack of transparency, and limited understanding of agentic capabilities are key barriers. Ethical concerns around AI, such as data privacy, algorithmic bias, and the “AI black box,” are prevalent, but few organizations act decisively to mitigate them.
- Human-AI collaboration is the future: By 2028, 38% of organizations will have AI agents as team members within human teams. Blended teams — where humans and AI agents collaborate — will become the norm, driving productivity and innovation. This means that in three years, organizations expect to have AI agents as members within human-supervised teams; AI agents must be seen not as tools, but as part of the team.
What are AI agents and agentic AI?
Here is Capgemini’s definition: “AI agents are programs/platforms/software that are connected to the business environment with a defined boundary, make decisions autonomously, and act to achieve specific goals with or without human intervention. With the latest advances in reasoning AI models, AI agents are able to break down tasks, ‘reason’ through potential pathways to find solutions to the given problem, try those solutions, and present successful outcomes.”
Capgemini notes that the capabilities of AI agents are increasing fast, and the costs to operate and develop AI agents is declining. AI agents are one of the top technology trends for 2025.
My 10 key takeaways from Capgemini’s research
- AI agents’ impact on the economy
- AI agents’ impact on the economy
AI agents could generate around $450 billion in total economic value in the 14 countries surveyed by 2028. Organizations with scaled implementation are projected to generate around $382 million (2.5% of annual revenue) on average over the next three years, while we expect others to generate around $76 million (0.5% of annual revenue). This applies to an average organization with $15 billion in annual revenues. Capgemini expects that surveyed organizations will collectively achieve $19 billion in gains over the next 12 months, with this figure projected to increase to $92 billion by the third year.
Other predictions outside of Capgemini include:
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Goldman Sachs predicts that Gen AI will drive a 6.1% rise in US GDP over the next decade — by 2028, this translates to around $540 billion in the US.
IDC forecasts that AI technologies overall will influence 3.5% of global GDP by 2030 — by 2028, this implies an impact of around $1.9 trillion globally.
MIT research estimates that a combination of AI capabilities could automate around one-fifth (slightly over 20%) of value-added tasks.
2. Business confidence in AI agents
A substantial 93% anticipate that organizations that have successfully scaled the implementation of AI agents within the next 12 months will achieve a competitive advantage.
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3. Adoption of AI agents is on the rise
Currently, 23% of organizations have initiated AI agent pilot projects, while 14% have progressed to partial or full-scale implementation. About 30% are exploring AI agents, and another 31% are preparing for experimentation or deployment within the next six to 12 months. In fact, the pace of AI agent adoption mirrors the rapid trajectory seen with generative AI.
4. Businesses on on their way to becoming autonomous
Many organizations that claim to be implementing AI agents are deploying solutions with limited autonomy. As many as 85% of business processes are expected to be at low levels of autonomy in the next 12 months. Industries noted in the Capgemini report include automotive, financial services, life sciences, telecom, and retail — with specific company examples and use cases.
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The report noted that 62% of companies prefer to partner with solution providers, such as Salesforce and system integrators, to implement or tailor already available AI agents. The ready availability of in-built agents, pre-existing integrations with legacy systems, and staff fluency in using these tools likely contribute to the preference.
5. AI agent future roadmaps are evolving
Capgemini found that 16% of organizations have developed a strategy and roadmap to implement agentic AI. Research found that 39% of organizations don’t have a strategy, but have multiple initiatives across functions to develop innovative solutions that can be scaled up.
6. AI leadership is key to accelerating AI agent roadmaps
The need for dedicated leadership to oversee AI agent initiatives is also a priority, with 26% appointing new leaders specifically for AI agents and 59% delegating this responsibility to existing AI or gen AI leadership.
7. Preferred agentic AI pricing models vary
Over half of organizations prefer consumption-based pricing for AI models within AI agents. Consumption-based (55%), platform-based (43%), and license-based(37%) models are the preferred pricing models among organizations for agentic AI solutions.
8. Customer-facing business functions most likely to adopt AI agents
Customer services and support, IT, and sales are the functions where most executives predict that AI agents will be actively performing at least one process or sub-process daily within the next 12 months. These functions often involve high volumes of interaction, require responsiveness over precision, and depend on contextual, conversational engagement.
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9. Fully autonomous business capabilities are a longer journey
Digital labor will handle one process by 2028, as 58% of business functions are likely to have AI agents handling at least one process or sub-process daily within three years. Over the next 12 months, we expect AI agents with Level 3 autonomy or higher to manage 15% of processes and subprocesses in each business function. This will rise to 25% within the next one to three years. Fully autonomous AI agents (Level 5) are expected to handle around 4% of business processes within three years. Capgemini noted that in the next 12 months, it expects AI agents to make 6% of day-to-day decisions, increasing to 8% in one to three years. And 25% of processes within a business function are expected to be handled by AI agents with Level 3 or higher autonomy by 2028.
10. Trust in AI agents is key to accelerating adoption
Almost half (47%) of organizations in the implementation phase report above average level of trust in AI agents, compared with 37% that are still in the exploration phase. This strong correlation between trust and implementation confirms that trust plays a crucial role in the adoption of AI agents. Only 22% of executives trust fully autonomous AI agents for enterprise applications, down from 43% in 2024. The gap is widening in the wrong direction.
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The decline in trust is not limited to AI agents; it extends to AI and gen AI as well. Capgemini noted that half of organizations have insufficient knowledge of AI agents’ capabilities. Employee skills and AI infrastructure maturity add to the trust deficiency. Over four in five (82%) organizations report low-to-medium maturity across dimensions such as computing, integration, orchestration, fine-tuning, and cybersecurity.
The Capgemini report concludes with this powerful reminder:
“The winners in this next wave of AI will not be those who simply deploy more AI tools. Rather, they will be those who rethink their business, reimagine workflows, reskill their workforces, restructure their organizations, and embed ethical safeguards from the outset.”
I believe AI agents may represent the biggest technological impact on businesses ever. This is not about new technology. This is about a new world. The most successful and resilient businesses of the future will be autonomous. Autonomous businesses will have a hybrid workforce — humans and digital labor, leveraging AI agents to augment and upgrade human capabilities. AI agents will be used for both cognitive transfer and cognitive upgrade opportunities. Autonomous businesses will also position themselves to best take advantage of the new stability-performance business operating models.
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To learn more about the Rise of agentic AI: How trust is the key to human-AI collaboration report from the Capgemini Research Institute, you can visit here.
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