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This episode of the AI Voice Bot Podcast takes aim at a big, uncomfortable truth: companies are pouring billions into AI but often have no idea whether it’s actually delivering value.

The core argument is simple and blunt — AI should be measured like labour, not magic. Businesses would never hire a sales team without tracking cost per sale, conversion rates, or ROI, yet many deploy AI systems and judge success on vanity metrics like conversation volume or “engagement.”

The episode breaks down why this happens:

• AI often sits in organisational limbo, with no clear owner.
• Dashboards focus on activity, not outcomes.
• “Cheaper than humans” is the wrong benchmark — cost per outcome is what matters.

Using voice AI as a sharp example, the discussion highlights the real risks of getting this wrong: lost leads, damaged trust, compliance issues, and hidden costs such as integration, maintenance, and monitoring. Cheap or “free” AI can end up being very expensive.

The solution is straightforward but rarely applied:

• Track real business metrics (cost per lead, booking, resolution, revenue influenced).
• Account for full costs, not just licensing.
• Assign clear ownership and governance.
• Define acceptable performance thresholds — and be willing to switch systems off if they don’t perform.

The takeaway is clear: the experimental phase of AI is over. AI isn’t free, it isn’t magic, and it shouldn’t be exempt from commercial accountability. If we wouldn’t tolerate a human team operating without performance metrics, we shouldn’t accept it from AI either.

📣 Get in Touch

Got a question about voice bots? Want to collaborate or see how they can work for your business? I’d love to connect.

• 🌐 Website: ai-voice.ai
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• 🔗 LinkedIn: Dave

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