- Business risks, transparency and compliance are the biggest obstacles to agent AI implementation
- Nearly half of organizations use siled AI agents
- Allowing AI to adapt to workload variables is key
Three in four (73%) organizations admit there is a gap between their ambitions and reality when it comes to deploying agent AI tools, and it’s because they lack confidence.
Just to get that message across, a report from Camunda reveals that despite 71% of organizations using AI agents, only 11% of use cases reached production last year.
Business risks (84%), transparency (80%), and regulatory and compliance concerns (66%) are the main obstacles, but companies are still betting on investments, resulting in a painfully low return on investment (ROI).
Agent AI is not taking advantage of its full potential
Four in five were found to be using AI agents only as chatbots or assistants, and almost half (48%) admitted that their agent systems operate in silos, without full context.
Many applications of AI agents also require human approval, which prevents them from being as effective as the technology suggests.
“Right now, being careful with agent AI means that many organizations are unable to go beyond pilots or isolated use cases,” wrote Kurt Petersen, senior vice president of customer success at Camunda. “Once a foundation of trust is established, agents can become powerful multipliers within governed processes rather than isolated co-pilots or chatbots.”
However, those that did use the full capabilities of agent AI saw strong results: 95% saw business growth from automation and nearly four in five (79%) plan to increase spending on automation as a result. As technology stacks become more distributed (76% agree), agent AI could be the key to bringing multiple systems together.
Camunda says the answer lies in agent orchestration, which means the combination of deterministic orchestration (fixed rules and workflows) and dynamic orchestration (agent AI can respond and adapt to variables).
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