Cloudera, the only true hybrid platform for data, analytics, and Artificial Intelligence (AI), released the findings of its latest survey report, “The Future of Enterprise AI Agents”. The survey polled nearly 1,500 enterprise IT leaders across 14 countries to understand their adoption patterns, use cases, and sentiments around AI agents. Results show an overwhelming 96% of respondents have plans to expand their use of AI agents in the next 12 months, with half aiming for significant, organisation-wide expansion. The applications for this deployment include performance optimisation bots (66%), security monitoring agents (63%), and development assistants (62%).
For business and IT leaders alike, agentic AI marks a new frontier—moving beyond traditional automation to systems that can reason, act, and adapt in real-time. When implemented effectively, these intelligent agents unlock operational agility, drive cost savings, and dramatically improve customer engagement. As a result, AI agents are quickly becoming a key source of competitive advantage, with 83% of organisations stating that investing in them is crucial to maintaining their edge in the market.
Closer to home, 91% of Australian and New Zealand (ANZ) organisations believe it vital to invest in AI Agents to maintain a competitive edge, with most (97%) planning to expand usage in the next twelve months. Notably, a vast majority (89%) say their prior investments in generative AI prepared them well to implement agentic AI.
Even with ongoing preparation and adoption, concerns like AI bias (69%), data privacy (54%), and lack of expertise (38%) continue to highlight the urgent need for unified data management and governance.
In addition to the benefits of the technology, Cloudera’s survey answered some of the biggest questions around agentic AI, including:
- How widely is this being adopted? Adoption is already underway. A majority (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 that’s only expected to grow.
- How are organisations deploying agents? Two-thirds (66%) are building agents on enterprise AI infrastructure platforms, while 60% are leveraging agentic capabilities embedded in existing core applications. This hybrid approach reflects a clear preference for scalable, secure, and close-to-data deployments.
- What’s getting in the way? The top three barriers are data privacy (53%), integration with legacy systems (40%), and high implementation costs (39%). These pain points all stem from a common root: the need for robust, unified data management and governance.
- Where should companies begin? Start with a contained, high-impact project—such as an internal IT support agent. These “fast-to-value” use cases help teams prove ROI, build internal confidence, and lay the foundation for broader, scaled deployments.
“AI agents have moved beyond experimentation—they’re now delivering real automation, efficiency, and business results. We’re seeing enterprises run hundreds of models in production, all demanding high-fidelity, well-managed data to drive better outcomes,” said Abhas Ricky, Chief Strategy Officer, Cloudera. “In 2025, agentic AI is taking centre stage, building on the momentum of generative AI but with even greater operational impact. Cloudera is enabling this transformation through a robust Enterprise AI Ecosystem, helping global organisations design secure, scalable, and integrated AI workflows that turn data into action.”
Local Australian and New Zealand Regional Vice President at Cloudera, Keir Garrett (pictured), added, “AI Agents have the potential to transform the operational landscape of ANZ organisations. Their ability to think, act and adapt at speed doesn’t just make processes better, they open up endless opportunities for innovation, smarter data-driven decisions and achieving faster results. But of course, we need guardrails in place. At Cloudera, we believe that trusted AI starts with trusted data. Our tools help ANZ organisations deploy AI models right where their data lives, keeping data privacy intact and ensuring they stay competitive in today’s fast-paced market.”
Cloudera’s report also addresses what global enterprises are actually doing with AI agents. The top use cases vary by industry, shaped by the specific needs and priorities of each sector:
- Finance & Insurance: Fraud detection (56%), risk assessment (44%), and investment advisory (38%) are the leading use cases. AI agents are flagging suspicious transactions in real time, simulating market scenarios to evaluate risk, and supporting advisors with personalised investment suggestions.
- Manufacturing: Top applications include process automation (49%), supply chain optimisation (48%), and quality control (47%). Agents are monitoring production lines to catch defects early, rerouting logistics to avoid delays, and streamlining repetitive tasks to improve efficiency.
- Healthcare: Appointment scheduling (51%), diagnostic assistance (50%), and medical records processing (47%) are the most common use cases. AI agents are reducing admin burden by coordinating schedules, surfacing relevant EMR data, and helping clinicians identify conditions in imaging data.
- Telecommunications: The telecoms industry is seeing substantial innovation fuelled by AI. Customer support bots (49%), customer experience agents (44%), and security monitoring agents (49%) are key deployments. Agents are resolving service issues instantly, flagging at-risk customers using behaviour data, and protecting networks from emerging threats.
Meanwhile, the top use cases for AI agents by industry vertical across ANZ are as follows:
- Finance & Insurance: The leading use cases include fraud detection (41%), risk assessment (59%), and portfolio management (41%)
- Manufacturing: Top applications are process automation (39%), quality control (48%), and inventory management (42%).
- Healthcare: The most common use cases are appointment scheduling (48%), diagnostic assistance (52%), and care coordination (43%).
- Telecommunications: Key deployments include customer experience (50%), infrastructure maintenance (50%), performance monitoring (50%), and security monitoring (50%).
To download the full report, click here.
