Make AI Agents Actually Work

AI agents promise speed and automation. Most fall short because they don’t have the right data.

In this short video, Amperity CTO Derek Slager explains what makes AI agents effective in the enterprise and why trusted, unified customer data is essential for real-world results.

Watch the video to see how AI agents move from experimentation to execution.

What you’ll learn in this video:

• What makes AI agents effective in real enterprise environments

• Why customer identity and accuracy matter more than models alone

• How real-time data enables AI agents to act, not just observe

What is an AI agent?

An AI agent is a system that uses data and models to make decisions or take action automatically. AI agents only deliver reliable outcomes when they are grounded in accurate, unified, and up-to-date customer data.

Why do most AI agents fail?

Most AI agents fail because they rely on fragmented or outdated data. Without a clear understanding of who the customer is and what has changed, agents make assumptions that lead to inconsistent results and risk.

How trusted customer data makes AI agents work

Trusted customer data gives AI agents the context they need to act with confidence. When identity is resolved and data is continuously updated, AI agents can:

• Respond in real time

• Make consistent decisions across channels

• Turn insight into action, not just analysis

This is the difference between impressive demos and measurable business impact.

Why this matters now

AI adoption is accelerating, but ROI is uneven. The next phase of advantage will come from AI agents that operate on trusted customer reality, not guesswork.