Study Reveals AI Agents Potential and Adoption Challenges
Automation Anywhere's latest study, in collaboration with Forrester Consulting, explores the barriers and breakthroughs in AI agent adoption by businesses, highlighting the importance of automation platforms and human-AI collaboration.
A new study by Automation Anywhere, in collaboration with Forrester Consulting, sheds light on the key barriers and breakthroughs shaping the adoption of Artificial Intelligence (AI) agents by businesses. The research, based on a survey of global decision-makers overseeing organization-wide AI strategies, reveals critical insights into the future of AI-driven processes.
Key Findings
- 60% of respondents believe automation platforms and AI leaders are the most valuable foundation for managing AI-driven processes.
- 71% agree that automation solutions should enhance human capabilities rather than replace them.
- 74% recognize the promise of AI agents in deriving insights from vast data sets.
- 66% express concerns about data privacy, while 63% highlight skills gaps as a barrier.
- 61% cite integration complexity as a persistent challenge.
AI Agents in Action
Organizations are already piloting or implementing AI agents for:
- Internal employee support (53%)
- Customer service (48%)
Expert Insights
Mihir Shukla, CEO of Automation Anywhere, emphasized the importance of Agentic AI, describing it as an extension of conversational AI that autonomously makes decisions. He noted, "Leaders are clearly prioritizing AI-augmented workflows, recognizing the undeniable value of Agentic AI."
For more on Agentic AI, read Unlocking the Power of AI.
Conclusion
The study underscores the growing role of AI agents in business automation, while also highlighting the challenges that need to be addressed for widespread adoption. As Shukla put it, "Deep process automation expertise is critical to scale adoption and unlock meaningful impact."
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About the Author

Alex Thompson
AI Technology Editor
Senior technology editor specializing in AI and machine learning content creation for 8 years. Former technical editor at AI Magazine, now provides technical documentation and content strategy services for multiple AI companies. Excels at transforming complex AI technical concepts into accessible content.