A Capgemini Research Institute report published today, AI in action: How Gen AI and agentic AI redefine business operations, finds that AI is now driving positive returns on investment (ROI), with the average being nearly a 1.7 times return.

The report highlights that this has now laid the groundwork for widespread agentic AI implementation. Among those early adopter organisations that have implemented genAI, around 30% have already integrated AI agents into their business operations.

Agentic AI projects are expected to rise by 48% by the end of 2025. The research also finds that one in five organisations already use AI agents or multi-agent systems, with genAI and agentic AI already delivering significant cost savings and operational efficiencies in business functions.

With businesses planning investments in AI infrastructure, some organisations had expressed concerns about achieving ROI from their large-scale AI and genAI rollouts.

However, the report finds that these initial concerns are fading fast, as enterprises are now seeing substantial returns, with those surveyed achieving a 1.7 times ROI from their genAI and AI investments. As a result, enterprises are increasing their genAI investments, with 62% of those surveyed growing their investment in genAI this year as compared to last year.

“GenAI and agentic AI can truly transform business services – enabling the shift from traditional cost-focused models towards an AI-enabled, value and insight driven business. Those that adopt an integrated approach with data and AI at its core will be set to achieve a truly connected, frictionless enterprise,” said Oliver Pfeil, CEO of Business Services at Capgemini and Member of the Group Executive Committee.

“While the research suggests increased adoption of AI agents, organisations still face numerous barriers to implementation at scale. Adopting a pragmatic approach, fostering trust in AI, and creating a strong data foundation will go a long way in transforming business services into a strategic powerhouse to fuel any enterprise.”

Gen AI adoption has laid the groundwork for agentic AI implementation

GenAI is expected to drive improvements in key metrics such as insight accuracy, productivity, time to market, and customer and employee experience over the next three years. As a result, more businesses are seeing the value of genAI, with 36% of organisations already implementing it, up from 20% last year.

Among those that have adopted genAI at a limited or full scale, around 30% have integrated AI agents into their operations.

The total number of AI agent projects in an average organisation are expected to grow 48% in 2025.

According to the report, AI agents are already delivering significant benefits across business functions, with agents and multi-agent systems reducing errors, improving customer satisfaction levels, increasing operational efficiency, and reducing operational costs. The top five industries adopting AI agents are high tech, industrial manufacturing, consumer products, energy & utilities, and pharma & healthcare.

Strong leadership and workforce transformation are key to faster returns

To achieve strong ROI on genAI investments, organisations should focus on developing strong leadership, governance, and AI readiness. According to the report, organisations who establish this foundation achieve ROI 45% faster. However, most enterprises currently lack this strong leadership, with only one in three leaders being a strong advocate of genAI.

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In addition, organisations must also transform their workforce to derive business value cites the report. In the past two years, enterprises that introduced automation and AI-based use cases have been able to automate 30% of operational tasks, and expect to automate further in the next two years.

As responsibilities evolve, organisational upskilling, reskilling, training and job role transitions will feature highly, with almost two-thirds of employees expecting to see their job descriptions altered by 2028. According to the report, employee interaction with AI agents is expected to increase by 2028, so training and upskilling will be needed to prepare workforces for effective human-AI collaboration.