Agentic AI is driving investment

90% of U.S. IT executives say they have business processes that would be improved by agentic AI.

  • Friday, 31st January 2025 Posted 1 year ago in by Phil Alsop

UiPath has released a new report that reveals 90% of IT executives have business processes that would be improved by agentic AI, while 77% state they are prepared to invest in agentic AI this year.

The UiPath 2025 Agentic AI Report—based on a survey of more than 250 U.S. IT executives at companies with revenue over $1 billion and qualitative interviews with senior technology leaders—also found that 37% of respondents say they are already using agentic AI, and 93% are either extremely or very interested in exploring it. An AI agent is a software entity that uses AI techniques to perceive its environment, process information, and take actions to achieve specific goals or objectives. AI agents can operate autonomously or semi-autonomously and are designed to mimic human decision-making or problem-solving processes in a given domain.

While most IT leaders have seen value from their automation and AI deployments to date, they have also experienced challenges – namely, security, development complexity, integration, and data quality.

When asked which benefits of agentic AI would be most appealing to their businesses, respondents cited improved oversight of business workflows (58%), increased integration among applications (53%), and the automation of complex business workflows (52%). According to the report, the top limitation with existing AI tools is lack of integration with other business applications, with 87% stating that interoperability between different AI technologies is essential or significant to their organisations.

“Agentic AI is a transformative approach that greatly expands and enhances the ability to automate larger, more complex business processes. For agentic AI to have meaningful impact, organizations need to provide agents with the needed foundation to intelligently plan and synchronize actions across robots, agents, people, and systems, all within enterprise-grade governance and security,” said Daniel Dines, Chief Executive Officer and Founder of UiPath. “The most powerful use cases for agents will be those that can orchestrate across business systems.”

Businesses continue to face substantial challenges in driving AI transformation, especially when dealing with complex workflows across multiple systems. Many have yet to see the promised productivity gains materialise and don’t trust AI in their most critical enterprise processes.

In fact, respondents identified IT security issues (56%) and integration with existing systems (35%) as their top concerns with agentic AI, along with cost of implementation (37%). When asked what capabilities would be most critical to effective implementation of agentic AI workflows, the top-ranked response was to “safety and privacy,” followed by “seamless integration with existing systems.” Executives see business value from agentic technology that can operate autonomously, so long as it is governed, secure, and trustworthy, the report found.

To address the safety, privacy, ethical, and regulatory concerns that IT leaders have with agents, automation-enabled orchestration will be essential. “I expect that robotic process automation will orchestrate the agents. For larger scale processes, you need clear orchestration and governance, and that means a deterministic technology like RPA,” said Max Ioffe, Director of the Global Intelligent Automation Center of Excellence at Wesco Distribution.

“As AI systems become more autonomous, enterprises must strike a balance between autonomy and human oversight to prevent unintended consequences and guarantee that AI-driven actions align with ethical, compliance, and legal standards,” said Dines. “A new era of agentic automation is going to address the challenges with orchestration, governance, and value derived from agentic AI.” 

Nearly half of European organisations spend up to €5 million a year on cloud – yet a quarter of capacity sits idle.

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