Agentic AI ROI Enters Delivery Phase
Google Cloud Report

Google Cloud and the National Research Group (NRG) released the second annual "ROI of AI 2025" report, revealing that the era of agentic AI has moved from experimentation to measurable value delivery. 88% of early adopters now report positive returns on generative AI investments, signaling a structural shift in how enterprises deploy intelligent systems.

Survey Methodology and Scope

The comprehensive study surveyed 3,466 senior leaders and executives from global enterprises with over $10 million in annual revenue and existing generative AI deployments. Fieldwork was conducted between April and June 2025 across 24 countries spanning North America, Latin America, EMEA, and Japan-Asia Pacific. Respondents represented key industries including financial services, manufacturing & automotive, retail & consumer packaged goods, telecommunications, healthcare & life sciences, media & entertainment, and the public sector.

The Rise of AI Agents

AI agents — specialized large language models capable of independently planning, reasoning, and performing tasks — are proliferating rapidly across organizations. The study found that more than half (52%) of executives report their organization is actively using AI agents, with 39% reporting their company has launched more than ten agents in production. The most common cross-industry applications include customer service and experience (49%), marketing (46%), security operations and cybersecurity (46%), and tech support (45%).

The Early Adopter Advantage

A distinct group of "agentic AI early adopters" — representing 13% of surveyed executives — emerged as the standout performers. These organizations dedicate at least 50% of their future AI budget to AI agents and have agents deeply embedded across operations. The performance gap is striking: 88% of these leaders report seeing ROI from generative AI on at least one use case, compared to a 74% average across all organizations surveyed.

The advantage extends across key use cases. Early adopters consistently outperform the average in customer service and experience (43% vs. 36%), boosting marketing effectiveness (41% vs. 33%), strengthening security operations (40% vs. 30%), and improving software development (37% vs. 27%).

Top Drivers of AI Value

The study identifies three primary drivers of generative AI value-add across all organizations. Productivity leads at 70%, reflecting AI's ability to automate routine tasks, accelerate document creation, and streamline workflows. Customer experience follows at 63%, as organizations deploy AI to enhance personalization, response times, and service quality. Business growth rounds out the top three at 56%, with 53% of executives reporting 6-10% revenue growth attributable to generative AI.

Additional areas showing strong returns include marketing (55% reporting impact) and security operations (49% reporting improvements), where generative AI accelerates threat detection, response speed, and ticket volume reduction.

Investment Trends and Organizational Readiness

Investment in generative AI continues to accelerate. 77% of executives report their organization has increased spending on generative AI as technology costs fall, and 48% are reallocating non-AI budgets toward generative AI initiatives. The data also shows an increase in speed-to-value: 51% of organizations now take an AI application from idea to production within 3-6 months, up from 47% in 2024.

Executive sponsorship emerges as a critical success factor. The report found that 78% of companies with active C-suite support report ROI from their AI investments, compared to just 43% without it. This underscores the importance of top-down commitment and cross-departmental governance in scaling AI initiatives from pilot programs to enterprise-wide deployments.

Industry and Regional Nuances

Adoption patterns vary meaningfully across sectors and regions. In financial services, the top agentic AI use case is fraud management and detection (43%). Retail and consumer packaged goods organizations lead with quality control applications (39%), while telecommunications companies prioritize network and equipment configuration automation (39%). Regionally, European executives report AI-enhanced tech support as the top use case, Japan-Asia Pacific leaders focus on customer service, and Latin American companies emphasize marketing applications.

The Agentic Era: From Experimentation to Value Delivery

"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," said Oliver Parker, vice president of Global Generative AI Go-To-Market at Google Cloud. "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 securing dedicated budgets, they are providing a clear roadmap for any organization looking to scale, solve complex challenges, and achieve more consistent ROI."

Carrie Tharp, vice president and head of Strategic Industries and Solutions at Google Cloud, added: "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."

As AI investment grows, a new set of priorities is emerging. Data privacy and security now top the list of LLM provider considerations for 37% of respondents, followed by integration with existing systems and cost. This suggests organizations are increasingly focused on foundational enterprise requirements before evaluating more advanced capabilities.