Google Cloud Study Suggests Early Agentic AI Adopters See Better ROI

• By David Ramel
• 09/23/25

Google Cloud has released its second annual ROI of AI study, finding that 52% of enterprise organizations now deploy AI agents in production environments. The comprehensive survey of 3,466 senior leaders across 24 countries highlights the emergence of a distinct group of "agentic AI early adopters" who are achieving measurably higher returns on their AI investments.

The study, conducted by Google Cloud and National Research Group between April and June 2025, surveyed executives from enterprises with over $10 million in annual revenue and existing generative AI deployments. Results indicate that AI agents — specialized large language models capable of independently planning, reasoning, and performing tasks — are rapidly becoming integral to business operations across industries.

Early Adopters See Significant ROI Advantage

The research identifies a cohort of "agentic AI early adopters" representing 13% of surveyed organizations. These companies allocate at least 50% of their future AI budgets to AI agents and have embedded multiple agents across their operations. The results show a clear performance advantage: 88% of early adopters report seeing ROI from generative AI on at least one use case, compared to 74% across all organizations surveyed.

"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."

The performance gap extends across specific use cases:

Agent Deployment Scales Rapidly Across Industries

The study reveals widespread AI agent adoption, with 39% of organizations reporting more than 10 AI agents deployed in production. Cross-industry applications center on customer service and experience (49%), marketing (46%), security operations and cybersecurity (46%), and tech support (45%).

Industry-specific patterns emerge in the data:

• Financial services: Fraud management and detection (43% adoption rate)
• Retail and consumer packaged goods: Quality control applications (39%)
• Telecommunications: Network and equipment configuration automation (39%)

Regional variations also surface in deployment priorities. European organizations lead with AI-enhanced tech support, Japan-Asia Pacific executives focus primarily on customer service applications, and Latin American companies emphasize marketing use cases.

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

Financial Returns Remain Consistent Across Key Areas

The study confirms sustained financial performance from generative AI investments. Seventy-four percent of executives report achieving ROI within the first year, maintaining consistency with 2024 findings. Over half (56%) cite business growth from generative AI, with 71% of that group reporting increased revenue.

Revenue growth patterns show stability year-over-year:

The research identifies five primary areas where organizations see the most significant value from generative AI:

1. Productivity (70%): Organizations report improved employee productivity, with 39% of executives indicating productivity has at least doubled as a result of generative AI implementation
2. Customer Experience (63%): Up from 60% in 2024, with retail and consumer packaged goods organizations showing particularly strong gains (68% vs. 57% in 2024)
3. Business Growth (56%): Unchanged from 2024, with consistent revenue impact across industries
4. Marketing (55%): New to the top five in 2025, reflecting increased adoption of AI-driven marketing workflows
5. Security (49%): Organizations report improved threat identification capabilities and reduced resolution times

Or, for visual learners:

Investment Patterns Shift Toward Agent-Focused Budgets

AI spending continues to increase as technology costs decline. Seventy-seven percent of executives report their organizations have increased generative AI spending as costs fall, while 48% are reallocating non-AI budgets toward AI investments, up from 44% in 2024.

Organizations now allocate an average of 26% of total annual IT spend to AI initiatives. Early adopters demonstrate even higher commitment, dedicating 39% of their IT budgets to AI compared to the overall average.

The study reveals evolving investment priorities for accelerating AI adoption:

• Aligning business and technology for change management and user adoption (42%)
• Enhancing data quality and knowledge management (41%)
• Upskilling staff and developing talent partnerships (40%)
• Providing appropriate tooling and compute resources (37%)
• Governing and managing AI risk (33%)
• Deploying AI agents (31%)

Security and Privacy Concerns Rise to the Forefront

As AI adoption accelerates, enterprise concerns shift toward foundational requirements. Data privacy and security emerged as the top consideration when evaluating LLM providers, cited by 37% of respondents. This represents a notable change from previous focus areas, with integration capabilities (28%) and cost considerations (27%) following as secondary priorities.

"The biggest hurdles for most organizations are rooted in foundational data security and systems integration," Parker noted. "The solution is to adopt a modern data strategy with strong governance from the start."

C-suite sponsorship continues to correlate strongly with AI success. Organizations with comprehensive executive backing report ROI rates of 78%, compared to 72% for those without such support. The alignment between generative AI adoption and C-suite sponsorship increased from 69% in 2024 to 73% in 2025.

Implementation Challenges Persist Despite Progress

While ROI figures remain strong, organizations continue facing implementation hurdles. The study identifies systems integration complexity and data security requirements as primary obstacles to broader AI agent deployment.

The research suggests that successful organizations focus on foundational data governance and security frameworks before expanding AI agent capabilities. Early adopters demonstrate this approach by maintaining human oversight while granting AI agents secure access to enterprise systems including CRM platforms and document repositories.

Time to market for AI initiatives shows improvement, with 51% of organizations now moving from idea to production use case within 3-6 months, compared to 47% in 2024. This acceleration reflects growing organizational maturity in AI implementation processes.

Google said the study provides a framework for organizations developing AI agent strategies, emphasizing executive sponsorship, robust data governance, clear ROI demonstration, secure system integration, and comprehensive risk management as critical success factors.

Here's the exact survey methodology for the report: "This report is based on a survey of 3,466 senior leaders and executives of global enterprises with generative AI deployment within their organizations, conducted by Google Cloud and National Research Group. The survey respondents represent organizations from 24 countries in North America, Latin America, EMEA, and JAPAC, and across key industries including Financial Services, Manufacturing & Automotive, Retail & Consumer Packaged Goods, Telecommunications, Healthcare & Life Sciences, Media & Entertainment, and the Public Sector. The breakdown of roles surveyed includes CEO, CIO, CFO, CMO, CTO, CISO, CDO, CSO, COO, and directors of digital strategy, IT, and marketing, VPs of IT, heads of innovation, and marketing directors."

The full report is available here on the Google Cloud site (registration required).