The demo was perfect. Then deployment happened.
If your contact center AI “worked” in a pilot but fell apart in production—this episode explains why.
Max Clark sits down with Jim K. Tennant (VP, Channel Sales at Observe.AI) to unpack the real reasons contact center AI projects fail after approval: weak data foundations, missing guardrails, messy knowledge sources, agent adoption breakdowns, and bots that can’t recover when customers go off-script. They also dig into what actually works—call analytics → automated QA → agent assist → targeted automation—and how to reduce churn and handle time without wrecking CSAT.
Watch this before your AI pilot turns into an expensive failure.
Use this if you’re making an IT decision and want to avoid a costly mistake. Answer four quick questions and we’ll route you to the right next step—strategy, sourcing, contract review, or optimization.
If it’s a fit, you’ll be able to book time immediately.
