New survey data from CrewAI indicates large enterprises are moving rapidly from testing AI agents to embedding them into core business workflows.
Security, integration and reliability emerged as the top concerns as businesses expand adoption. CrewAI provides software for building and managing AI agents inside enterprise systems.
In its “2026 State of Agentic AI” report, CrewAI said all 500 senior executives it surveyed plan to expand their agentic AI use this year. Nearly three-quarters described deploying AI agents into production as a “critical priority” or “strategic imperative.”
The survey included C-suite and senior leaders at organizations with more than $100 million in annual revenue and at least 5,000 employees across seven global regions. The findings suggest that agentic AI is shifting from experimentation to operational use inside large enterprises.
Agentic AI refers to artificial intelligence that’s capable of autonomously executing tasks across systems and applications. It’s the underlying concept behind agentic commerce, in which those AI agents can make purchases on users’ behalf. The levels of agentic commerce capabilities vary in maturity.
Enterprises to expand use of AI agents
65% of respondents said their enterprises are already using AI agents today. Meanwhile, 81% reported that adoption is either fully scaled or actively expanding across teams. On average, companies said they have automated 31% of workflows using agentic AI and expect to increase adoption by another 33% in 2026.
Three-quarters of respondents reported a high or extremely high impact on time savings. 69% cited significant reductions in operational costs, while 62% pointed to revenue generation and 59% to reduced labor costs.
“Organizations aren’t just experimenting — they’re building, shipping and scaling agents into production,” said João Moura, founder and CEO of CrewAI.
The survey also found a shift in how enterprises evaluate AI agent platforms. The top factor respondents cited was security and governance (34%). Ease of integration with existing systems and data sources followed at 30%, and reliability and performance at 24%.
Only 2% ranked time-to-value and return on investment as the primary consideration.
That response suggests enterprises assume AI agents can deliver value but are focused on whether they can deploy the technology safely and reliably within complex IT environments.
Senior executives’ preferences for agentic AI adoption
More than half of respondents (57%) said they prefer building on existing or open-source tools rather than creating agent frameworks from scratch.
This preference was strongest in industries where integration with legacy systems is often complex:
- Construction (73%)
- Financial services (71%)
- Manufacturing (63%)
- Retail and ecommerce (60%)
Despite broad adoption plans, respondents identified obstacles to scaling agentic AI.
35% cited data readiness and integration challenges as the top barrier, followed by insufficient internal skills or talent (33%). Respondents also noted technology limitations (27%) and budget constraints (25%).
Only 23% identified a lack of clear use cases as a barrier, indicating most organizations see where they can apply AI agents but face implementation hurdles.
The benefits of agentic AI were reported across departments.
IT was cited by 52% of respondents as seeing meaningful impact, followed by operations (44%), customer support (39%), sales and marketing (39%), and research and development (38%). No respondents reported zero benefit from using AI agents.
CrewAI said the report reflects a broader shift as enterprises move AI agents from pilot programs into operational systems.
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