Businesses are increasingly exploring the transformative potential of AI agents to enhance customer service interactions, provide real-time employee support, and adapt to fluctuating customer demands. However, the transition from traditional, scripted approaches to more complex, generative systems raises several challenges. Key questions include how to test systems that do not yield consistent responses, how to maintain a balance between safety and flexibility when integrating AI with core business infrastructure, and how to effectively manage costs, transparency, and ethical considerations while pursuing substantial outcomes.
Addressing these challenges will be crucial for companies aiming to advance in the field of customer experience technology. The narrative surrounding customer experience automation has shifted over the past decade, emphasizing the need for adaptability and resilience in business practices. Organizations are now tasked with re-evaluating their strategies for risk mitigation, the implementation of safety measures, and the methods used to assess success metrics.
The future of customer experience automation may favor those companies that prioritize outcome-oriented design, creating tools that operate transparently, efficiently, and on a large scale. According to expert Verma, organizations that implement applied AI solutions tailored to specific use cases are likely to emerge as leaders in this evolving landscape.
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Source: https://www.technologyreview.com/2025/09/16/1123592/de-risking-investment-in-ai-agents/