Featuring:
Craig Le Clair, VP and Principal Analyst and Christina McAllister, Senior Analyst
Show Notes:
What makes AI agents fundamentally different from agentic AI? And what real-world use cases are we seeing today for AI agents? VP and Principal Analyst Craig Le Clair and Senior Analyst Christina McAllister join the podcast to break down these critical questions.
The episode starts with the analysts providing some high-level differentiation, explaining that AI agents are systems designed to act on behalf of users, while agentic AI extends this by enabling systems to optimize tasks autonomously. Le Clair notes, “AI agents are applications that help achieve specific goals using predefined rules, while agentic AI introduces broader autonomy and adaptability.”
From there, they explore the various B2C and B2B use cases for AI agents, highlighting customer support as a major entry point for AI agents in the consumer-facing space. McAllister says, “The contact center remains one of the hottest domains for AI agents due to its clear ROI, but consumer trust is still a key challenge.” However, she adds that AI agents are already making strides in improving both efficiency and the customer experience.
On the B2B front, Le Clair focuses on enterprise automation use cases, including applications in mid-office and back-office tasks. “Whether it’s customer onboarding, or invoice processing and finance and accounting, all these … processes that really run companies, that’s where I’m seeing tremendous activity for AI agents,” he says.
The discussion also emphasizes how important trust is in the future adoption for AI agents. And the best way to build trust is to build guardrails, says Le Clair. “A lot of the engineering in the next few years is going to be around how do I build and embed guardrails into these systems to prevent it from having non-deterministic outcomes,” he says.
The episode closes with the analysts providing their perspective on some of the misconceptions about AI agent adoption, with Le Clair pointing out that enterprises should focus most on the outcome they’re seeking and apply the right technology to it rather than look across their organization for a use case that may not align with their core outcomes goals.
