Agentic AI in CX: Definition, benefits, and examples of AI agents for today and the future


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Mar 10 2025 24 mins  

Agentic AI in CX: Definition, Benefits, and Real-World Applications. Artificial intelligence is evolving—and agentic AI is leading the charge. Unlike traditional AI tools, AI agents can autonomously make decisions and take action to complete tasks without constant human oversight. But what does this mean for businesses today?

In this episode, we break down:

  • What agentic AI is and how it differs from traditional AI and chatbots
  • How AI agents improve customer experience (CX) through automation, personalization, and predictive decision-making
  • Real-world examples, including Bosch PowerTools and AI-powered sales assistants
  • The future of multi-agent systems, where AI works seamlessly across departments
  • Key challenges and ethical considerations, from governance to security risks

AI isn’t just answering questions anymore—it’s actively solving problems. Tune in to discover how businesses can leverage AI agents to enhance efficiency, customer satisfaction, and profitability.

What You’ll Learn in This Episode:

  • The fundamental definition and mechanics of agentic AI
  • How AI agents transform CX by automating complex workflows
  • Examples of real-world businesses successfully deploying AI agents
  • The future potential of AI-driven automation across industries
  • The risks and best practices for integrating AI agents responsibly

Key Takeaways:

  • AI agents aren’t just chatbots. They operate autonomously, learning and making decisions to optimize business processes.
  • Customer experience is being transformed. AI agents handle complex service requests, predict customer needs, and provide seamless interactions.
  • Sales and e-commerce are evolving. AI-powered assistants help sales teams retrieve critical information instantly and enhance the online shopping experience.
  • Businesses must act now. With 82% of organizations planning AI agent adoption within three years, companies that delay risk falling behind.
  • Governance and ethics matter. Companies need to implement safeguards to prevent AI misuse and ensure responsible deployment.

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