A recent report by Capgemini highlights the significant economic potential of AI agents, projecting they could generate up to $450 billion in economic value by 2028 through revenue growth and cost savings.
The report defines AI agents as “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.” These agents are characterized by their ability to break down tasks, reason through potential solutions, and present successful outcomes, with their capabilities rapidly increasing and operational costs declining. AI agents are identified as a top technology trend for 2025.
Currently, the adoption of AI agents, while accelerating, remains at a low maturity level. Only 2% of organizations have deployed AI agents at scale, with 12% at partial scale. A significant 23% have launched pilot projects, and 61% are still exploring deployment. Despite this, 15% of business processes are expected to achieve semi- or full autonomy within the next 12 months. However, fewer than one in five organizations report high maturity in the data and technology infrastructure required for agentic AI implementation.
The projected economic impact of AI agents is substantial. Beyond the $450 billion global potential, organizations with scaled implementation are expected to generate approximately $382 million (or 2.5% of annual revenue) on average over the next three years. In contrast, those without scaled implementation are projected to generate around $76 million (or 0.5% of annual revenue), based on an average organization with $15 billion in annual revenues. Capgemini anticipates surveyed organizations will collectively achieve $19 billion in gains within the next 12 months, a figure projected to rise to $92 billion by the third year.
Other industry predictions corroborate the significant economic influence of AI. Goldman Sachs forecasts that Generative AI will boost US GDP by 6.1% over the next decade, which translates to roughly $540 billion in the US by 2028. IDC predicts that AI technologies overall will influence 3.5% of global GDP by 2030, implying an impact of approximately $1.9 trillion globally by 2028. MIT research further estimates that AI capabilities could automate around one-fifth (slightly over 20%) of value-added tasks.
Business confidence in AI agents is high, with a substantial 93% of organizations anticipating that those successfully scaling AI agent implementation within the next 12 months will gain a competitive advantage. The pace of AI agent adoption mirrors that of generative AI, with 23% of organizations having initiated pilot projects and 14% having progressed to partial or full-scale implementation. Another 30% are exploring AI agents, and 31% are preparing for experimentation or deployment within the next six to 12 months.
While many organizations claim to be implementing AI agents, a significant portion of deployed solutions still have limited autonomy. As many as 85% of business processes are expected to operate at low levels of autonomy in the next 12 months across various industries, including automotive, financial services, life sciences, telecom, and retail. To overcome implementation challenges, 62% of companies prefer partnering with solution providers, such as Salesforce and system integrators, leveraging the ready availability of in-built agents and pre-existing integrations.
The development of future roadmaps for AI agents is evolving. Only 16% of organizations have a defined strategy and roadmap for implementing agentic AI. However, 39% without a formal strategy are pursuing multiple initiatives across functions to develop innovative scalable solutions. The need for dedicated leadership in this area is also emerging, with 26% of organizations appointing new leaders specifically for AI agents, while 59% delegate this responsibility to existing AI or Gen AI leadership.
Regarding pricing models, over half of organizations (55%) prefer consumption-based pricing for AI models within AI agents. Platform-based (43%) and license-based (37%) models are also preferred among organizations for agentic AI solutions.
Customer-facing business functions are most likely to adopt AI agents early. Executives predict that AI agents will actively perform at least one process or sub-process daily within the next 12 months in customer services and support, IT, and sales. These functions are often characterized by high volumes of interaction, a need for responsiveness over precision, and depend on contextual, conversational engagement.
Achieving fully autonomous business capabilities is seen as a longer-term journey. Within three years, 58% of business functions are likely to have AI agents handling at least one process or sub-process daily. Over the next 12 months, AI agents with Level 3 autonomy or higher are expected to manage 15% of processes and sub-processes in each business function, rising to 25% within one to three years. Fully autonomous AI agents (Level 5) are projected to handle approximately 4% of business processes within three years. Capgemini also anticipates AI agents will make 6% of day-to-day decisions in the next 12 months, increasing to 8% in one to three years, with 25% of processes within a business function expected to be handled by AI agents with Level 3 or higher autonomy by 2028.
Trust in AI agents is identified as crucial for accelerating adoption. Nearly half (47%) of organizations in the implementation phase report an above-average level of trust in AI agents, compared to 37% in the exploration phase, confirming the strong correlation between trust and adoption. However, only 22% of executives now trust fully autonomous AI agents for enterprise applications, a significant decrease from 43% in 2024, indicating a widening gap in trust. This decline is not limited to AI agents but extends to AI and Generative AI more broadly.
A key contributing factor to this trust deficit is insufficient knowledge, with half of organizations having inadequate understanding of AI agents’ capabilities. Employee skills and AI infrastructure maturity also play a role, as 82% of organizations report low-to-medium maturity across critical dimensions such as computing, integration, orchestration, fine-tuning, and cybersecurity.
The Capgemini report concludes with a powerful message: “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.” The report suggests that AI agents may represent the most significant technological impact on businesses ever, marking a shift towards a “new world” of autonomous businesses with hybrid workforces where humans and digital labor, leveraging AI agents, augment and upgrade human capabilities. Autonomous businesses are expected to utilize AI agents for both cognitive transfer and cognitive upgrade opportunities, positioning themselves to best leverage new stability-performance business operating models.
