Majority of executives see ROI as AI agents drive business growth

More than half of surveyed executives say their organisations have already deployed AI agents, according to a new global study commissioned by Google Cloud.

The study, part of Google Cloud's annual research into the return on investment (ROI) from artificial intelligence, involved 3,466 senior leaders across 24 countries whose enterprises have adopted generative AI. Findings indicate that 52% of executives report active use of AI agents within their operations, while 39% say their companies have launched in excess of ten agents.

Agent adoption expands

The surveyed group includes a distinct segment referred to as "agentic AI early adopters", who represent 13% of those polled. These businesses are allocating at least half of their future AI budgets to agent-based projects and have embedded such agents extensively within their processes. Among these early adopters, 88% indicate their organisations are seeing ROI from generative AI for at least one application, compared with a 74% average across all surveyed organisations.

Rates of reported ROI from agentic AI use cases are higher among the early adopters, particularly in specific business areas. These include customer service and experience (43% compared to a 36% average), marketing effectiveness (41% compared to 33%), security operations (40% compared to 30%), and software development (37% compared to 27%).

"This year's research shows we're entering the next chapter of the AI wave. The conversation has moved from 'if' to 'how fast,' and the new differentiator is agentic AI. Early adopters of agents are not just automating tasks; they are also redesigning core business processes. By championing AI as a core engine for competitive growth and thus securing dedicated budgets, they are providing a clear roadmap for any organization looking to scale, solve complex challenges, and achieve more consistent ROI," said Oliver Parker, vice president, Global Generative AI Go-To-Market, Google Cloud. 

Industry and regional variation

The study identifies that AI agent use cases are present across various departments, with the most common applications listed as customer service and experience (49%), marketing (46%), security operations and cybersecurity (46%), and tech support (45%). While adoption is broadly consistent across industries, there are some variations; for instance, Healthcare and Life Sciences are reported to be marginally behind other sectors.

Industry-specific examples include fraud management and detection in financial services (43%), quality control in retail and consumer packaged goods (39%), and network or equipment configuration in telecommunications (39%). The report also highlights notable regional differences in AI agent prioritisation. Executives in Europe were most likely to prioritise tech support, while those in the Japan-Asia Pacific region focused on customer service, and Latin America prioritised marketing applications.

"We're seeing organizations around the world use agentic AI to tackle complex industry-specific tasks – from fraud detection in financial services to quality control in retail. This isn't just about efficiency; it's about embedding intelligence directly into the business," said Carrie Tharp, vice president, Head of Strategic Industries and Solutions, Google Cloud. 

Financial outcomes and focus areas

Results show that the financial return from generative AI initiatives remains at levels consistent with the previous year: 74% of executives report realising ROI within the first 12 months of implementation, and 56% say generative AI has directly contributed to overall business growth.

Within the group that saw business growth from AI, 71% experienced an increase in revenue, and 53% of those estimate the rise was in the 6-10% range. The factors attributed to these gains include improved productivity (70%), customer experience (63%), and business growth (56%). The report also notes an uptick in organisations progressing AI applications from concept to production in three to six months – cited by 51% of respondents, up from 47% the previous year.

As generative AI spending continues to grow – 77% of executives report increased investment and nearly half are reallocating budgets from non-AI areas – new priorities and challenges are emerging. The chief concern, cited by 37% of respondents, is data privacy and security in evaluating large language model providers. Other top considerations include integration with existing systems and cost efficiency, with fewer organisations naming features or customisation as primary differentiators.

"2024 proved that generative AI works; 2025 is all about compounding that success. The biggest hurdles for most organizations are rooted in foundational data security and systems integration. The solution is to adopt a modern data strategy with strong governance from the start," added Parker. 

The survey included senior leaders from multiple sectors, covering roles such as CEO, CIO, CFO, CMO, CTO, CISO, CDO, CSO, COO, as well as directors and vice presidents in IT, innovation, digital strategy, and marketing.