Enterprise firms are ramping up their investments in AI agents, with 96% planning to expand their use across multiple business areas over the next year, according to new research from Cloudera. 

The global software firm’s latest report, The Future of Enterprise AI Agents, found that half of global enterprise businesses are aiming for significant, organisation-wide expansion of AI agents, with 83% stating that investing in them is ‘crucial’ to maintaining their edge in the market.

Cloudera’s poll of nearly 1,500 enterprise IT leaders across fourteen countries revealed that more than half (57%) of enterprise IT leaders report they’ve implemented AI agents in the past two years – 21% in just the last year – signalling rapid momentum in rolling out emerging tech.

Two-thirds (66%) are building agents on enterprise AI infrastructure platforms, while 60% are leveraging agentic capabilities embedded in existing core applications, a hybrid approach that Cloudera said reflects a clear preference for scalable, secure, and close-to-data deployments.

According to the data, the most popular deployments of AI agents so far include performance optimisation bots (66%), security monitoring agents (63%), and development assistants (62%), although the study notes that top use cases vary by industry, shaped by the specific needs and priorities of different sectors.

For example, within finance and insurance, fraud detection (56%), risk assessment (44%), and investment advisory (38%) are the leading use cases, with AI agents used to flag suspicious transactions in real time, simulate market scenarios to evaluate risk, and support advisors with personalised investment suggestions.

Meanwhile, in the telecoms industry, customer support bots (49%), customer experience agents (44%), and security monitoring agents (49%) are the top deployments, with AI agents resolving service issues instantly, flagging at-risk customers using behavior data, and protecting networks from emerging threats. 

Enterprise organisations are still experiencing some pain points, however, with the top three barriers to a successful deployment of AI agents being data privacy (53%), integration with legacy systems (40%), and high implementation costs (39%), all stemming from a common need for more robust, unified data management and governance.

“AI agents have moved beyond experimentation—they’re now delivering real automation, efficiency, and business results,” said Abhas Ricky, chief strategy officer at Cloudera.

“We’re seeing enterprises run hundreds of models in production, all demanding high-fidelity, well-managed data to drive better outcomes.

“In 2025, agentic AI is taking centre stage, building on the momentum of generative AI but with even greater operational impact.”

Cloudera’s study adds to the raft of research that shows just how optimistic firms are about the rollout of AI agents.

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A survey from PagerDuty found that more than half (51%) of companies are already leveraging AI agents, with 94% of companies believing they will adopt AI agents more quickly than genAI and more than six in ten expecting over 100% ROI on their agentic AI investments.

Research from Malwarebytes earlier this year revealed that the expectations around AI agents stretch to security, too, with the introduction of AI agents potentially delivering the cybersecurity disruption that many expected after ChatGPT’s release in 2022.  

Despite these major benefits, workers have yet to fully trust agentic AI, as a study from Pegasystems found that a third (33%) of employees are worried about the quality of AI agents’ work, and three in ten do not trust the accuracy of the AI agent’s responses.